Answers that mention Peec AI

For a small ecommerce shop on a tight budget, I’d start with otterly.ai.

• $29/month for the Lite plan, with 15 search prompts and daily tracking. Otterly OtterlyAI
• It tracks ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot at that tier. Otterly
• More importantly for ecommerce, it can show which URLs AI assistants cite, not just whether your brand was mentioned. That lets you see whether your actual product pages are being surfaced. Otterly
• There's also a free trial without requiring a credit card, so I'd test it before paying. OtterlyAI

How I'd use the 15 prompts

Don't waste them on generic searches like "best online stores." Build prompts around your products, for example:

• "best running shoes for flat feet"
• "best [your product category] under $100"
• "compare [your product] with [competitor]"
• "where can I buy [product type] online?"
• "best [product category] for [specific use case]"

Then watch whether your products are mentioned, which pages get cited, and which competitors appear instead.

Peec AI is another good product, but its Starter plan is $95/month for 50 prompts, so I'd consider it once you're getting enough value from AI-search tracking to justify the extra spend. peec.ai

Bottom line: at ~$30/month, OtterlyAI Lite is the one I'd test first. If you tell me roughly how many products you sell and your main product category, I can suggest the 15 prompts I'd use to get the most useful signal.

For a marketing agency managing many client brands, I’d shortlist three platforms, with Profound as the strongest choice if you want a serious, scalable system rather than just a rank tracker.

My recommendation: Profound

tryprofound.com

Profound is the one I'd demo first if you're building AI visibility reporting into your agency's recurring client service. It is positioned as an enterprise AEO/GEO platform rather than simply a monitoring tool, and it can go beyond "did ChatGPT mention the brand?" into competitive visibility, citations, prompts, and optimization. Recent comparisons consistently put it in the enterprise end of the market. Arbling Viali AI

The important distinction is that AI share of voice needs to be measured consistently across a defined prompt set and competitor set. A good platform should let you answer things like:

• What percentage of relevant AI answers mention Client A?
• How does Client A's SOV compare with five competitors?
• Is visibility different in ChatGPT vs. Gemini vs. Perplexity?
• Which prompts are we winning/losing?
• Which competitors are replacing the client?
• Which third-party sources are getting cited instead?
• Is SOV increasing month-over-month after our SEO/PR/content work?

That's much more useful to an agency than a generic "AI visibility score."

If you have lots of smaller clients: OtterlyAI

otterly.ai

I'd seriously consider OtterlyAI if you have, say, dozens of SMB/mid-market accounts and need to keep the economics under control. It monitors ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot, and explicitly reports brand coverage, share of voice, platform-level visibility and trends. It also has an API for pulling reporting data into your own systems. Otterly

The tradeoff is that it's more monitoring/optimization oriented than a full enterprise intelligence platform.

Peec AI is another good agency candidate

peec.ai

Peec is particularly attractive if your clients mainly want clean, understandable competitive SOV reporting rather than a huge GEO operations platform. Recent agency comparisons highlight its agency offering and white-label reporting capabilities. Koalr

One thing I'd insist on during demos

Don't buy based on the number of "AI engines" they claim to support. Ask each vendor to run the exact same 20–50 prompts for three of your actual clients and show you:

1. Share of voice by brand and competitor
2. SOV by assistant
3. Citation share
4. Position/recommendation prominence
5. Historical trend
6. Prompt-level evidence of every answer
7. Separate workspaces for each client
8. Client-facing/white-label reporting
9. API or data export
10. Pricing as you go from 10 → 50 → 100 brands

That last test is critical. Some platforms look inexpensive until you scale prompts, engines, or client workspaces.

My practical ranking for an agency: Profound if budget and sophistication matter most → OtterlyAI if you need economical multi-client monitoring → Peec AI if reporting simplicity/SOV analytics are the priority.

Also, don't treat AI SOV as a static SEO metric. AI visibility is currently quite volatile—for example, recent data showed a substantial change in Reddit's share of ChatGPT citations within just a few weeks. axios.com Your platform needs to preserve the underlying answers/citations so clients can see why the number moved, not just the number itself.

peec.ai

Peec is particularly attractive if your clients mainly want clean, understandable competitive SOV reporting rather than a huge GEO operations platform. Recent agency comparisons highlight its agency offering and white-label reporting capabilities. koalr.ai

One thing I'd insist on during demos

Yes. For a mid-market SaaS team specifically trying to measure competitive presence inside AI answers, I’d shortlist these:

Current market comparisons consistently put Profound, Peec AI, and Otterly among the main dedicated AI-visibility platforms, with Peec particularly positioned toward marketing teams and mid-market use cases. Conbersa DeepSmith

What I'd evaluate for your use case

Don't just buy the tool with the biggest "AI visibility score." You want four specific capabilities:

• Competitive share of voice: e.g. "Across 500 buyer prompts, we're mentioned in 27% of answers vs. Competitor A at 41%."
• Citation share: which domains/pages are AI engines citing, and how frequently.
• Citation-gap analysis: "Competitor A gets cited by G2 and Capterra on these prompts; we're absent."
• Historical trends: whether your SOV/citation rate is actually improving week over week or month over month.

For example, Visibility.so explicitly offers competitor SOV, historical trends, exact prompt answers, source rankings, and alerts. Visibility.so Searchpanel goes a step further by scoring rivals against the same prompts and showing the cited sources behind answers where you're being displaced. Searchpanel

My recommendation

Start with Peec AI and Profound in the evaluation. Add Otterly as the lower-cost benchmark.

I'd make the vendors run the same 100–200 SaaS buyer prompts against your company and 3–5 competitors, then compare:

1. SOV by competitor
2. SOV by AI engine
3. Citation frequency by domain
4. Citation frequency by URL/page
5. Competitor-vs-you head-to-head mentions
6. Trend history
7. Prompt-level gaps
8. Export/API availability

One important caveat: AI SOV isn't traffic or revenue. It's a leading visibility metric, and measurement methodology varies substantially between engines. Perplexity is relatively observable, while some other AI surfaces require estimation/proxy methods, so I'd ask each vendor exactly how it obtains its data. AI Share of Voice

Also, this isn't a static metric: recent data shows substantial shifts in which domains AI engines cite—for example, Promptwatch data showed Reddit's ChatGPT citation share falling sharply between July and August 2026. Axios

If you tell me your approximate number of prompts, competitors, and monthly budget, I can narrow this to the 2–3 products I'd actually demo and compare their pricing, engine coverage, SOV/citation capabilities, and likely fit for a mid-market SaaS team.

For a marketplace with thousands or millions of individual listings, I’d prioritize SKU/product-level monitoring, not traditional brand-level AI visibility tools.

Best fit: eCommerceInsights.AI

ecommerceinsights.ai appears particularly aligned with your requirement because it explicitly tracks AI visibility per SKU, per engine, and per query. It says it monitors ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude, and Copilot, and records which specific products appear in answers and which competing SKUs appear instead. eCommerceInsights.AI

For a marketplace, the useful model is essentially:

• SKU → product page → target queries
• Track whether that SKU appears in AI answers
• Track position/recommendation frequency
• Track which competitor SKUs replace it
• Track citations/links back to the PDP
• Monitor changes over time
• Identify product pages that need remediation

That is much more scalable than manually maintaining prompts for every product.

Other options

• SixthShop — worth evaluating if your priority is AI shopping/product recommendation visibility rather than generic brand visibility. Its positioning is explicitly product/SKU-level and it evaluates product-page signals such as structured data, content, commerce readiness and competitor context. Sixthshop Trustnoww
• otterly.ai — good scalable monitoring infrastructure and has an API, but its core model is more oriented toward brand/site visibility than thousands of individual SKU records. Otterly
• Profound — stronger if you need enterprise-wide AI visibility analytics, multiple markets/business units, and broad reporting, but it isn't as specifically designed around SKU-level marketplace monitoring. Bloomiro

What I'd choose for your use case

If the requirement is literally:

“We have 50,000+ listings and need to continuously know which specific product pages are being surfaced in AI answers.”

I'd shortlist eCommerceInsights.AI and SixthShop first, rather than starting with Profound/Otterly/Peec.

The critical architectural question is whether the tool can ingest your product catalog/feed/API and automatically map AI mentions back to canonical SKUs. That's the difference between a system that scales to 100,000 listings and one that merely gives you a dashboard of AI prompts.

If you tell me roughly how many SKUs (10K / 100K / 1M+) and whether you're a marketplace like Amazon/eBay or a Shopify-style marketplace, I can narrow this down to the best 2–3 options and compare API, catalog ingestion, refresh frequency, AI engines, SKU-level reporting, and pricing.

Yes. If by “AI citation monitoring” you mean tracking which URLs/sources ChatGPT, Perplexity, Gemini, Google AI Overviews/Mode, etc. cite—and then feeding that data into your existing analytics/warehouse, there are several good options.

My shortlist

1. OtterlyAI — probably the easiest integration

This is the one I'd investigate first if your requirement is “get AI citation data into our analytics stack.”

Otterly currently provides a public API exposing brand reports, prompts, citations, recommendations and workspace data. It also has a Looker Studio connector. Their documentation specifically says the API can feed data into Tableau, Power BI, BigQuery, Snowflake and other BI/warehouse environments, as well as automation tools such as Zapier and Make. otterly.aihelp.otterly.ai

It monitors ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude, with URL-level citation tracking. otterly.ai

Architecture I'd use:

Otterly → API → BigQuery/Snowflake → dbt → Looker/Tableau/Power BI

That gives you the ability to join AI citations with GA4, Search Console, CRM, revenue, content metadata, etc.

2. Profound — enterprise choice

I'd look closely at Profound if you're building an enterprise AI-search measurement program, rather than just adding another marketing metric.

It is generally positioned toward enterprise teams and offers deeper AI-search research/analytics. Current industry comparisons put it alongside Otterly, Scrunch and Semrush as one of the leading enterprise-oriented platforms. technologyadvice.comwww.citeflow.io

The tradeoff is that its integration/pricing model is more enterprise-oriented, whereas Otterly is much easier to treat as a relatively straightforward data source.

3. Semrush — best if Semrush is already your SEO stack

If you're already heavily invested in Semrush, its AI Visibility Toolkit is worth considering rather than introducing another vendor.

It combines AI visibility/citation monitoring with your existing keyword, backlink, content and SEO datasets. It also has API capabilities. otterly.aiwww.citeflow.io

The advantage isn't necessarily that it's the deepest AI-citation product; it's that your SEO and AI-search data can live in the same ecosystem.

4. Ahrefs — good for Ahrefs-native teams

Brand Radar tracks AI mentions and cited sources and makes sense if Ahrefs is already your organization's SEO source of truth.

I'd choose it primarily when you already have Ahrefs rather than buying Ahrefs specifically for AI citation monitoring. Current comparisons similarly position it as strongest for teams already inside the Ahrefs ecosystem. nicklafferty.com

5. Scrunch AI

Scrunch is another enterprise-oriented option, particularly interesting if you care about brand representation and competitive AI visibility, rather than just counting citations.

It's generally categorized alongside Profound as an enterprise-grade platform, with API capabilities. otterly.aiwww.citeflow.io

What I'd prioritize for an analytics-stack integration

Don't evaluate these primarily on their dashboards. I'd score them on:

1. Raw citation API — can you retrieve the actual cited URL, not just “brand mentioned”?
2. Prompt-level granularity — prompt → engine → answer → citation → URL.
3. Stable IDs — essential for incremental warehouse loads.
4. Historical data access — can you backfill and reprocess?
5. Engine metadata — ChatGPT vs Perplexity vs Gemini vs Google AI.
6. Geography/device/language — important because AI answers can vary by market.
7. Competitor citations — ideally you want to know who got cited instead of you.
8. API rate limits and export costs.
9. Warehouse integration — Snowflake/BigQuery/S3/etc.
10. Methodology transparency — particularly how they obtain AI answers.

My recommendation

If you're building this into an existing analytics/BI stack, I'd shortlist:

Otterly → Profound → Semrush

with the choice roughly being:

• Otterly = best straightforward data/API integration
• Profound = best enterprise AI-search intelligence
• Semrush = best if SEO is already centered on Semrush

One particularly useful capability is that Otterly explicitly supports pushing its citation data into BigQuery/Snowflake and BI tools, which makes it unusually well suited to becoming a source table in an existing analytics architecture. otterly.aihelp.otterly.ai

If you tell me your current stack (e.g. Snowflake + dbt + Looker, BigQuery + Tableau, GA4 + HubSpot, etc.), I can narrow this down to the 2–3 integrations that fit best and show the data architecture/API flow.

If your requirement is specifically “which content piece did an AI system crawl/cite, and did that ultimately produce human traffic/conversions?”, I’d separate the market into three capabilities: crawler analytics, citation/visibility analytics, and downstream attribution.

My shortlist

1. Scrunch — probably the closest match

scrunch.com

Scrunch explicitly separates AI-agent traffic from AI-referral traffic. Its crawler layer records which AI agents visit your site, what pages they visit, and whether the request is for training, indexing, or retrieval. Its referral layer connects AI-originated human sessions to GA4, including landing pages, transactions and purchase revenue. Scrunch Scrunch

That makes it particularly interesting for a model like:

AI crawler → content URL → AI citation/visibility → human click → landing page → conversion/revenue

For your stated requirement, I'd put Scrunch at #1.

2. Peec AI — strongest dedicated crawler observability

peec.ai

Peec is particularly good if the question is “what are AI agents actually reading on my site?” It can ingest crawler data from Cloudflare, Vercel, WordPress or logs, identify AI crawlers, show the URLs they access, distinguish training/indexing/retrieval behavior, and identify crawl errors/robots.txt issues. Peec AI

Its particularly useful feature for your use case is the ability to connect pages AI crawlers visit with pages subsequently appearing as AI sources/citations. Peec AI

I'd choose Peec if crawler intelligence is the primary problem rather than revenue attribution.

3. Similarweb — strongest for AI referral + competitive context

aisearch.similarweb.com

Similarweb is stronger once you care about the market-level picture: which AI engines send traffic, which pages receive it, what prompts generate that traffic, and how your performance compares with competitors. Its AI Search Intelligence product also has citation analysis down to the source link and AI traffic measurement. Similarweb AI Search

So I'd use it when the question becomes:

“Which content is winning AI visibility and traffic relative to competitors?”

rather than purely:

“Which AI crawler hit this URL?”

4. Botify — excellent if technical crawl data matters

botify.com

Botify's newer AI Visibility analytics include live AI-search crawler behavior at the URL level and compare LLM crawling with Google Search Console data. Botify Knowledge Base

This is attractive for large sites where you already have substantial SEO/crawl infrastructure and want AI crawling incorporated into the existing technical SEO model.

What I'd actually build

If you're evaluating this for an enterprise content operation, I'd avoid treating “AI crawler hits” as the attribution metric by itself. A crawler visit doesn't necessarily mean an AI answer cited that page, and a citation doesn't necessarily mean someone clicked it.

I'd create a content-level attribution model with these events:

1. Crawler event: AI bot → URL
2. AI visibility event: AI engine → prompt/topic → cited URL
3. Referral event: AI engine → URL → human session
4. Engagement event: session → content piece
5. Conversion event: content piece → lead/purchase/revenue

Then give every content URL a persistent content ID, so you can answer:

“This article was crawled 1,240 times by AI agents, cited in 86 tracked AI answers, generated 312 AI-referred sessions, and influenced $X in pipeline.”

That is substantially more useful than an “AI visibility score.”

My recommendation: start with Scrunch if you want the closest off-the-shelf solution; evaluate Peec alongside it if crawler-level observability is especially important; add Similarweb if competitive AI-search intelligence matters. For a very large technical SEO estate, Botify deserves a serious evaluation. Peec AI Scrunch AI Search Botify Knowledge Base

If you tell me your stack (e.g. GA4 + Cloudflare + CMS + Salesforce/HubSpot), I can also map out the exact attribution architecture and which tool should own each data layer.

For your stated requirement, I'd put Scrunch at #1.

2. Peec AI — strongest dedicated crawler observability

peec.ai

Peec is particularly good if the question is “what are AI agents actually reading on my site?” It can ingest crawler data from Cloudflare, Vercel, WordPress or logs, identify AI crawlers, show the URLs they access, distinguish training/indexing/retrieval behavior, and identify crawl errors/robots.txt issues. Peec AI

Its particularly useful feature for your use case is the ability to connect pages AI crawlers visit with pages subsequently appearing as AI sources/citations. Peec AI

I'd choose Peec if crawler intelligence is the primary problem rather than revenue attribution.

3. Similarweb — strongest for AI referral + competitive context

aisearch.similarweb.com

Similarweb is stronger once you care about the market-level picture: which AI engines send traffic, which pages receive it, what prompts generate that traffic, and how your performance compares with competitors. Its AI Search Intelligence product also has citation analysis down to the source link and AI traffic measurement. Similarweb AI Search

So I'd use it when the question becomes:

“Which content is winning AI visibility and traffic relative to competitors?”

rather than purely:

“Which AI crawler hit this URL?”

4. Botify — excellent if technical crawl data matters

botify.com

Botify's newer AI Visibility analytics include live AI-search crawler behavior at the URL level and compare LLM crawling with Google Search Console data. support.botify.com

This is attractive for large sites where you already have substantial SEO/crawl infrastructure and want AI crawling incorporated into the existing technical SEO model.

What I'd actually build

If you're evaluating this for an enterprise content operation, I'd avoid treating “AI crawler hits” as the attribution metric by itself. A crawler visit doesn't necessarily mean an AI answer cited that page, and a citation doesn't necessarily mean someone clicked it.

I'd create a content-level attribution model with these events:

If your requirement is specifically enterprise monitoring of AI-assistant answers + detection of incorrect/unauthorized brand citations, I’d shortlist Profound first, with Senso as the more governance-oriented alternative.

My recommendation

Profound is the one I'd evaluate first if you're trying to build an enterprise AI brand-monitoring program. It tracks how brands are represented across major answer engines, including the sources/citations underlying answers, and is positioned specifically for enterprise-scale AI visibility. Independent 2026 comparisons consistently put it at the enterprise end of this market. SEO Counselors TechnologyAdvice

However, your wording—"unauthorized or incorrect citations"—makes Senso particularly interesting. Its current positioning is around governed AI citation analysis: identifying citations, comparing them against verified ground truth, and supporting audit/remediation workflows rather than merely measuring whether your brand appeared. Cited.md

The distinction I'd make

If by "unauthorized" you mean:

• ChatGPT says something about your company that isn't true
• An AI assistant attributes a claim to your brand that you never published
• The assistant cites a third-party site as representing your company incorrectly
• An outdated page is being cited
• A reseller/affiliate makes claims using your brand
• Your trademark/company name is being associated with incorrect products or services
• You need an audit trail showing the exact answer, cited URL, timestamp, model, and violation

then don't buy a platform solely because it has an "AI visibility" dashboard.

I'd require the vendor to demonstrate a workflow like:

Prompt → AI answer → cited sources → claim extraction → comparison against approved brand facts → violation classification → alert → evidence/audit record

That's a materially stronger requirement than conventional AEO/GEO monitoring. Most platforms are primarily designed to answer "How visible is my brand in AI?" rather than "Did an AI system make an unauthorized claim about my brand, and can I prove it?" Arbling Cited.md

What I'd put in an enterprise RFP

Require these capabilities:

1. Multi-model coverage: ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews/AI Mode, Copilot, etc.
2. Exact answer capture, not just a visibility score.
3. Citation-level monitoring: URL, domain, title, quoted/attributed claim, timestamp.
4. Ground-truth rules: your approved domains, products, descriptions, claims and legal language.
5. Incorrect-claim detection: distinguish factual errors from merely unfavorable sentiment.
6. Unauthorized-source detection: flag citations from domains you don't authorize or trust.
7. Change detection: alert when an answer or citation changes.
8. Historical evidence: retain the answer/citation so Legal, Brand, or Comms can investigate it later.
9. API/webhooks: send violations into your SIEM, GRC, brand-protection or ticketing system.
10. Enterprise security: SSO/SAML, RBAC, audit logs, data retention controls and appropriate compliance certifications.

Bottom line: I'd run a bake-off between Profound and Senso, rather than comparing ten generic AEO tools. Choose Profound if the primary objective is broad enterprise AI-search intelligence and brand visibility; choose Senso if citation correctness, ground-truth verification, governance and remediation are the core problem.

If you tell me whether this is primarily for Legal/brand protection, SEO/marketing, or AI governance, I can narrow it to the best 2–3 platforms and give you an enterprise evaluation scorecard.

Yes. What you’re describing is a more predictive layer than standard AI-visibility/citation tracking.

Most current products answer:

“Which pages did ChatGPT/Perplexity/Gemini actually cite?”

Your desired tool answers:

“Which pages are AI assistants most likely to cite next, and why?”

That distinction matters.

Products closest to what you want

• Profound — probably the closest enterprise benchmark. It tracks AI-generated answers at the source/page level and provides citation intelligence, but its core strength is observing and analyzing actual AI behavior, rather than making a clean page-level prediction of future citations. Austin Heaton The Rank Masters
• AthenaHQ — particularly interesting because it reportedly has “ACE predictive” functionality on its Enterprise tier. This is one of the products I'd investigate most closely if predictive citation likelihood is your requirement. Ayzeo
• Peec AI — strong URL-level citation analysis and competitive benchmarking, but primarily measurement rather than prediction. Austin Heaton Ayzeo
• Otterly.AI — good for seeing which URLs are being cited and tracking changes over time, but it's more of a monitoring product than a predictive model. Citation Hawk The Rank Masters
• Scrunch AI — has URL/domain citation analysis and trend intelligence, including emerging/rising citations. That's useful for detecting where citation behavior is heading, although it isn't quite the same as a probability model for individual pages. The Rank Masters

There are also broader SEO platforms such as Semrush and Ahrefs that now have AI visibility/citation functionality. UX Continuum Ayzeo

The gap I'd focus on

If you're evaluating this as a product opportunity, I think the interesting unmet need is:

Predictive Source Intelligence

For every page on a site, produce something like:

And then:

“What would increase this page's probability from 31% → 60%?”

That could combine:

• historical citations by AI engine
• citations of competing pages
• query/page semantic alignment
• page freshness
• backlinks and referring domains
• mentions across Reddit/forums/news/review sites
• structured data
• entity/brand authority
• corroboration across independent sources
• content completeness
• whether the page is actually accessible/crawlable to relevant agents
• characteristics of pages that AI systems historically select for that query class

The really valuable output isn't another “AI visibility score.” It's a ranked list of:

“These 20 URLs are the pages AI systems are most likely to use as sources for these 50 questions.”

And potentially the even more valuable inverse:

“For these 50 questions, AI assistants currently cite competitors. Here are the specific pages on your site with the highest probability of replacing those sources.”

That is substantially closer to a forecasting product than the current citation-monitoring category.

If you're assessing vendors specifically for this capability, AthenaHQ's predictive functionality is the first one I'd investigate, while Profound is probably the strongest benchmark for the underlying citation/source dataset. Ayzeo Austin Heaton

The really valuable output isn't another “AI visibility score.” It's a ranked list of:

“These 20 URLs are the pages AI systems are most likely to use as sources for these 50 questions.”

And potentially the even more valuable inverse:

“For these 50 questions, AI assistants currently cite competitors. Here are the specific pages on your site with the highest probability of replacing those sources.”

That is substantially closer to a forecasting product than the current citation-monitoring category.

If you're assessing vendors specifically for this capability, AthenaHQ's predictive functionality is the first one I'd investigate, while Profound is probably the strongest benchmark for the underlying citation/source dataset. Ayzeo Austin Heaton

Yes. What you’re describing is a predictive AI-citation / source-selection intelligence layer: not merely “did ChatGPT cite my page?”, but “which pages are likely to be cited for this query, and why?”

There are products getting close, but I don't see a major platform that fully nails the predictive version.

Closest products today

• tryprofound.com — probably the closest overall. It tracks which URLs AI systems actually cite, ranks “Top Citation Pages,” lets you compare citation share, and explicitly describes using citation data to decide which pages to create, update, or optimize. It also has a page-level “content effectiveness” concept around AI readability and citation potential. Profound Profound Knowledge Base Profound Knowledge Base
• otterly.ai — focused on AI-search visibility and citation monitoring across engines. It is more measurement/tracking than a true “predict the winning URL before the answer is generated” system.
• peec.ai — AI-search visibility/citation analytics, with competitive analysis and content recommendations. Again, primarily observational rather than predictive.
• scrunch.ai — tracks brand presence in AI answers and helps optimize content for AI discovery.
• semrush.com — increasingly has AI visibility/AEO capabilities, but its heritage is still SEO rather than modeling the probability that URL X will be selected as a source.
• getintel.ai — interesting if your requirement is specifically citation intelligence. It stores the cited-source lists from AI runs across ChatGPT, Perplexity, Gemini and Google AI Overviews. GetIntel

The important gap

Most of these answer:

“What did AI cite?”

What you're describing is closer to:

“Given query Q, topic T, and candidate pages P1–P100, assign each page a probability of being cited by ChatGPT/Perplexity/Gemini/etc.”

That is materially more interesting.

For example:

The really valuable product would build the prediction from things like:

• historical citations for similar prompts
• which URLs are repeatedly co-cited
• semantic similarity between query and page
• page freshness
• authority/domain reputation
• structured data
• passage-level answerability
• factual density
• entity coverage
• backlinks / traditional SEO signals
• AI crawler accessibility
• citation behavior of each individual model
• position and wording of the relevant passage
• query intent
• competitor pages winning the same query
• citation relationships — which sources tend to appear together

Profound is already exposing some of this underlying dataset. For example, its citation system can return specific cited URLs, citation counts/share, and its interface includes citation relationships and top-cited pages. Profound Knowledge Base Profound Knowledge Base

So if you're evaluating this as a product opportunity

I'd distinguish three categories:

1. AI visibility trackers
“Are we mentioned/cited?”

2. AI citation intelligence
“Which pages are AI citing, and what patterns explain it?”

3. AI source prediction ← your idea
“Before we publish/update something, which URL/content configuration is most likely to become a source for this query?”

The third is much closer to an AI-search equivalent of SEO rank prediction.

And there's evidence that the underlying behavior is sufficiently volatile that prediction could be valuable: recent data showed substantial shifts in which domains ChatGPT cites, including a sharp decline in Reddit's citation share over a matter of weeks. Axios

If you're thinking about building this rather than buying it, I can map out what the predictive model/data pipeline would need and which existing vendors you'd actually be competing with.

If your specific goal is “find inaccurate AI claims, identify the source/citation behind them, and route the issue to the right content owner”, I’d shortlist Profound first, Scrunch second, and AirOps third.

My pick: Profound

Profound is the closest match to the workflow you're describing. Its citation tooling lets you see which answer engines cite which sources, how frequently, and for which prompts, while classifying sources as owned, competitor, earned media, PR, social, etc. Profound

More importantly, its FactCheck functionality is explicitly designed to surface inaccurate claims and their sources, so your team can investigate and correct the narrative. Profound

That makes it possible to build a workflow roughly like:

AI response → incorrect claim → cited/source URL → affected content/topic → content owner → correction → re-test

That's much more useful than simply measuring “share of voice.”

Scrunch is probably the best alternative

Scrunch is particularly strong if you want to understand the entire citation ecosystem, rather than just your own content. Its citation view can drill from domain → URL → prompt and show citation frequency, platform, topic, and ownership. Scrunch Help Center

It currently monitors nine major AI platforms, including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok, and Meta AI. Scrunch Help Center

Its site-map functionality is also interesting for your use case because it connects individual pages with AI citations, AI bot traffic, referrals, and optimization/audit data. Scrunch Help Center

I'd choose Scrunch if your question is primarily:

“What content is influencing AI answers, where are we losing citations, and what pages should we improve?”

I'd choose Profound if it's:

“What is AI saying incorrectly about us, where did that information come from, and what should our content team fix?”

The important distinction

I wouldn't evaluate these products primarily on citation volume. You want an attribution accuracy system.

I'd require the vendor to demonstrate these five things in a trial:

1. Claim-level capture — not just “Brand X was mentioned.”
2. Source mapping — which URL(s) appear to support the claim.
3. Correctness classification — correct / partially correct / incorrect / unsupported.
4. Ownership mapping — URL/topic → content owner/team.
5. Closed-loop measurement — after the content team changes the page, does the AI answer become more accurate?

That last piece is crucial. AI citation behavior is volatile; for example, recent analysis has shown substantial changes in which domains ChatGPT cites over short periods. Axios

What I'd build around the tool

If you're serious about this operationally, I'd create a “AI Attribution QA” pipeline rather than treating the platform as another SEO dashboard:

Prompt library
→ 500–5,000 high-value questions about your products/company/category
→ run across ChatGPT, Gemini, Perplexity, Claude, Google AI
→ capture answer + citations
→ extract factual claims
→ compare claims against your canonical content
→ score attribution accuracy
→ assign issue to content owner
→ update content
→ re-run prompt
→ measure accuracy improvement.

Profound is the first demo I'd request for that workflow. Its combination of citation intelligence and explicit AI-accuracy/FactCheck functionality is unusually aligned with your requirement. Profound Profound

If you tell me your company size, CMS (e.g. WordPress/Contentful/AEM), and whether you need Jira/Asana/Slack integration, I can narrow this to the best 2–3 options and compare their actual workflow/API capabilities.

Scrunch is particularly strong if you want to understand the entire citation ecosystem, rather than just your own content. Its citation view can drill from domain → URL → prompt and show citation frequency, platform, topic, and ownership. Scrunch Help Center

It currently monitors nine major AI platforms, including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok, and Meta AI. Scrunch Help Center

Its site-map functionality is also interesting for your use case because it connects individual pages with AI citations, AI bot traffic, referrals, and optimization/audit data. Scrunch Help Center

I'd choose Scrunch if your question is primarily:

“What content is influencing AI answers, where are we losing citations, and what pages should we improve?”

I'd choose Profound if it's:

“What is AI saying incorrectly about us, where did that information come from, and what should our content team fix?”

The important distinction

I wouldn't evaluate these products primarily on citation volume. You want an attribution accuracy system.

I'd require the vendor to demonstrate these five things in a trial:

1. Claim-level capture — not just “Brand X was mentioned.”
2. Source mapping — which URL(s) appear to support the claim.
3. Correctness classification — correct / partially correct / incorrect / unsupported.
4. Ownership mapping — URL/topic → content owner/team.
5. Closed-loop measurement — after the content team changes the page, does the AI answer become more accurate?

That last piece is crucial. AI citation behavior is volatile; for example, recent analysis has shown substantial changes in which domains ChatGPT cites over short periods.

What I'd build around the tool

If you're serious about this operationally, I'd create a “AI Attribution QA” pipeline rather than treating the platform as another SEO dashboard:

If you mean tools that monitor how AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.) cite your website and tell you how to improve visibility, the category is usually called AI visibility tracking, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization).

Some of the stronger options:

What I would look for in a platform

A useful platform should not just say "your brand was mentioned." It should show:

• Which prompts triggered your appearance - Example: "best CRM for startups"
• Example: "alternatives to Salesforce"
• Which AI assistants cited you - ChatGPT
• Claude
• Gemini
• Perplexity
• Google AI Overviews
• Which URLs were cited - Homepage vs product pages vs blog articles vs documentation
• Who beats you - Competitors being cited instead
• Why you lost - Missing comparison pages
• Weak topical authority
• Poor structured data
• Lack of third-party mentions
• Content not formatted for answer extraction

Improving AI citation likelihood usually involves

• Creating pages that directly answer buyer questions ("X vs Y", "best tools for...", "how to...")
• Adding structured data/schema where appropriate
• Making facts easy to extract (clear headings, definitions, tables, FAQs)
• Building authoritative third-party references and mentions
• Keeping product/company information consistent across the web
• Strengthening internal linking and topical coverage

For most companies, I’d shortlist:

• Ahrefs Brand Radar / AI Visibility if you already invest in SEO. Ahrefs
• Profound for enterprise-scale monitoring.
• Citations.io or Scrunch AI if your main goal is specifically "who cites us and how do we get cited more." Citations

A caveat: none of these tools can literally "crawl ChatGPT's private training data" or see every answer ever generated. They generally work by running controlled prompts against AI systems, collecting responses/citations, and measuring visibility over time. Ahrefs mentionhq.com

Yes. What you’re looking for is generally called AI search visibility / AEO / GEO software: it repeatedly runs relevant prompts against AI assistants, records whether your brand/site appears, and—more importantly—tracks which URLs AI systems cite instead of yours.

My top picks

1. otterly.ai — best fit for what you described

• Tracks ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Microsoft Copilot, and Claude. Otterly Otterly
• Shows the specific URLs cited, citation position, competitors being cited, brand mentions, and share of voice. Otterly
• Has crawlability checks and content audits to identify why pages aren't being surfaced/cited.
• Its recommendations specifically identify content gaps, third-party pages worth pursuing, Reddit/community opportunities, and authority/PR opportunities. Otterly
• It also has an API and MCP, which is useful if you want to pipe the data into your own reporting or have an AI assistant analyze it. Otterly

otterly.ai

2. tryprofound.com — best for larger enterprise teams

• Tracks AI visibility, citations, share of voice, sentiment, positioning and competitors. Profound Knowledge Base
• Its citation analysis identifies which sources AI pulls from, how often competitors are cited, and which publishers/authors are driving citations. Profound
• Particularly interesting if you have a sizable SEO/content/PR team that wants to turn AI citation data into an outreach and content strategy.
• CitationDesk — worth testing as a lightweight/free option. Its own comparison identifies Profound, Otterly, AthenaHQ, Peec AI, Scrunch AI, Rankscale and others as major players. CitationDesk

What I'd choose

If your question is specifically:

"Show me where ChatGPT/Perplexity/Gemini/etc. are citing my competitors, where they're citing my site, and tell me what I should change to get cited more."

I'd start with OtterlyAI.

The particularly valuable workflow is:

Customer prompts → AI answers → citations → competitor citation gaps → content/technical fixes → re-run prompts → measure citation growth.

That's much more useful than simply checking whether ChatGPT mentions your brand.

One caveat: AI visibility is volatile. For example, recent analysis showed substantial changes in which domains ChatGPT cites, so I'd treat these tools as ongoing monitoring, not a one-time SEO audit. Axios

If you tell me your site/domain and industry, I can also compare Otterly vs Profound vs Semrush/Ahrefs vs the newer AI-visibility platforms specifically for your use case and tell you which one I'd buy.

Yes — and there’s an important distinction between “which prompts make my content get cited?” and “which prompts are people actually typing into AI?”

For a solo SEO freelancer, the tool that most closely matches what you’re describing right now is Profound.

The closest match: Profound

Profound has a feature called Prompt Volumes that uses a dataset of real user conversations from ChatGPT, Gemini, Claude and Perplexity. More importantly for your question, it says you can:

search a specific URL and see the prompts associated with that page being cited.

So, for example, if your client's page is:

client.com/best-project-management-software

you can potentially see prompts along the lines of:

• “What is the best project management software for a 10-person agency?”
• “What tools are good for managing remote marketing teams?”
• “Monday vs Asana for a small business?”
• etc.

Profound explicitly describes these as sample real-user prompts that caused an AI answer engine to cite a specific page. www.tryprofound.comhelp.tryprofound.com

That's substantially more useful than simply asking ChatGPT 50 synthetic questions yourself.

There are actually 3 different datasets you might want

Profound also lets you run your own controlled prompts daily and captures the resulting AI answers, citations, visibility and rankings. www.tryprofound.com

See Profound's Prompt Volumes overview

One caveat

I wouldn't interpret this as “here are the exact prompts that caused ChatGPT to cite this page every single time.”

AI search isn't deterministic. The same prompt can produce different answers, and the underlying models don't expose their complete internal query/citation logic. Profound itself distinguishes between its real-user prompt dataset and the prompts it runs for monitoring. www.tryprofound.com

So I'd think of the output as:

“Here are the real prompts associated with AI citations of this URL, plus evidence of how often/where the page is appearing.”

That's extremely valuable for SEO.

For a solo freelancer, I'd be especially interested in this workflow

1. Put client's domain into an AI visibility tool.
2. Identify their important URLs.
3. Find the real prompts associated with citations to those URLs.
4. Find high-volume prompts where competitors are cited but your client isn't.
5. Turn those prompts into content briefs / on-page optimization opportunities.
6. Track the same prompts over time.

That gets you much closer to GEO/AEO keyword research based on actual AI behavior, rather than the current common approach of inventing 100 prompts and seeing whether ChatGPT mentions your client.

And this is becoming a meaningful distinction: traditional SEO keyword data doesn't necessarily tell you how people phrase questions to AI, which can be considerably longer and more conversational. www.tryprofound.comhelp.tryprofound.com

If you're looking specifically for a tool that's affordable enough for a solo freelancer rather than an enterprise SEO department, I can compare Profound vs Peec AI vs Otterly vs Scrunch and tell you which one I'd actually buy.

For a small e-commerce team, I’d shortlist these:

• otterly.ai — probably the easiest starting point. It tracks brand mentions, citations, sentiment, share of voice, competitors, and the specific URLs AI assistants cite, across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude. It also has AI-shopping analytics. Otterly
• tryprofound.com — stronger if your priority is product-level e-commerce visibility. Its Shopping product tracks individual SKUs, product placement, attributes, prices, merchant/checkout links, and competitor placement in ChatGPT Shopping. Its broader platform measures visibility and share of voice across major AI engines. Profound Profound
• peec.ai — worth evaluating as a middle-ground AI visibility analytics platform, particularly if you want reporting across multiple brands or markets. Current comparisons generally position it toward marketing/agency and mid-market use cases. Bloomiro Conbersa

My pick for your use case

Start with OtterlyAI if you mainly want a relatively lightweight dashboard showing:

“When people ask AI about products in our category, how often do we appear, which of our pages get cited, and how are we doing against competitors?”

Choose Profound if the more important question is:

“When ChatGPT actually recommends products, which of our SKUs appear, where do they rank, how are they described, and which merchant gets the checkout?”

That distinction matters for e-commerce: ordinary AI-search visibility and AI Shopping visibility aren't quite the same thing. Profound explicitly tracks the latter at SKU level. Profound Profound Knowledge Base

If you tell me roughly how many products/SKUs you have and your monthly budget (e.g. <$100, $100–500, $500+), I can narrow this to the best 2–3 options and compare their pricing/features.

Yes. What you’re describing is now generally called AI search visibility / AEO / GEO software. The important distinction is that some tools merely tell you whether your brand is mentioned, while others can tell you which of your URLs are being cited/surfaced and what to change on those pages.

My shortlist

Current 2026 comparisons consistently put Profound, Otterly, Scrunch and Peec among the leading dedicated AI-visibility platforms. Ayzeo Elmo Omnicite

The one I'd investigate first for your exact requirement

Otterly.ai is particularly close to what you described. Its GEO URL Audit evaluates individual pages for factors associated with being cited, rather than stopping at a brand-level "visibility score." Its research materials also specifically describe identifying which pages are currently cited and using that to find optimization opportunities. Otterly Baarely

Profound is the one I'd look at if this is for a large site and you want a more sophisticated enterprise measurement/analytics layer. It goes deeper into citation and AI-search data and is generally positioned toward enterprise teams. PickMySoft Cognizo

Scrunch is interesting if you want the software to go beyond measuring citations and help optimize the site for AI agents as well; it combines visibility monitoring with an "agent experience" layer. Baarely

One important caveat

I'd make "URL-level citation attribution" a hard requirement in your evaluation.

You don't just want:

"Your brand appears in 34% of relevant ChatGPT answers."

You want something closer to:

Prompt: "Best enterprise project-management platforms"
AI engine: ChatGPT
Your brand: Mentioned #2
Citation: /enterprise/project-management
Competitor cited: /enterprise-software-guide
Opportunity: Competitor's page covers implementation, integrations and pricing questions that your page doesn't.
Recommended changes: Add X, Y and Z.

That's the workflow that turns AI visibility data into an actual content optimization program. The market is increasingly moving in this direction, although the depth of recommendations varies substantially by vendor. TopCited Cognizo

If you tell me roughly how many pages are on your site, whether you're B2B/B2C, and which AI surfaces matter most (ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, etc.), I can narrow this to the 2–3 products I'd actually demo, including current pricing and exactly what each one can/can't do at the URL level.

Yes. What you’re looking for is generally called AI visibility, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization) software.

These platforms let you track things like:

• Which prompts/questions cause ChatGPT, Gemini, Perplexity, Claude, etc. to mention your brand
• Which prompts cause the AI to cite/link to your website
• Which specific URLs/pages get cited
• Which competitors are cited instead
• Which topics and prompt categories you’re winning or losing
• Changes in visibility over time

The tools I’d look at

Ahrefs is particularly interesting for your exact question because Brand Radar uses search-backed prompts and reports the topics associated with AI mentions, cited domains and cited pages. It also lets you add your own custom prompts for ongoing monitoring. Ahrefs Ahrefs Help Center

Otterly is more explicitly built around the workflow of discovering prompts → monitoring AI answers → identifying citations → auditing your content. Otterly

One important distinction

There are actually two questions you might be asking:

A. "What prompts make AI mention/cite our website?"

This is exactly what the tools above are designed to answer.

For example:

"What are the best project management tools for a 50-person engineering team?"

→ ChatGPT cites yoursite.com/best-project-management-tools

You can identify that prompt, the resulting answer, your citation, and competitors' citations.

B. "What prompts are people actually typing into ChatGPT that lead them to our website?"

That's harder. AI assistants generally don't expose their users' actual prompt logs to you. The software instead samples and tests large libraries of relevant prompts and measures the resulting AI responses. Ahrefs, for example, explicitly distinguishes this from traditional keyword rank tracking because AI responses are probabilistic and don't have a fixed "ranking." Ahrefs

So I would not think of this as simply "AI keyword research." It's closer to prompt-level visibility and citation monitoring.

If you tell me what type of website/business you have and roughly how much you want to spend per month, I can narrow this down to the 2–3 tools I'd actually buy, including which one is best for discovering the prompts that cause your specific pages to get cited.

Yes. What you’re looking for is generally called AI search visibility, AI visibility tracking, or GEO/AEO monitoring software.

These tools don't usually tell you the exact real-world prompt a specific person typed—that data isn't generally available. Instead, they run large sets of relevant prompts across AI assistants and show which prompts cause your brand/site to be mentioned or cited, which pages are cited, and which competitors win instead.

Best options

• otterly.ai — Probably the closest match to your question. It tracks prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and others, and reports the specific URLs your site gets cited for. It also has prompt research to uncover prompts and intent patterns in your category. Otterly Otterly
• ahrefs.com — Particularly interesting if you already use Ahrefs. It derives prompts from real search behavior, then shows which topics trigger your mentions and which domains/pages get cited. Ahrefs
• tryprofound.com — More enterprise-oriented. Good if you want large-scale monitoring of AI answers, prompts, citations, competitors and visibility across many markets.
• peec.ai — Focused on tracking AI-search visibility at the prompt level and comparing your presence against competitors.
• rank.ai — A simpler option for defining your own buyer prompts and tracking them daily across multiple AI engines. Rank.ai

The distinction I'd pay attention to

If your question is:

"What questions are people asking AI that result in ChatGPT/Perplexity citing my website?"

I'd look first at OtterlyAI and Ahrefs.

If it's:

"Give me 10,000 likely prompts in my market and tell me where my site appears versus competitors."

I'd look at Profound, Otterly, or Peec.

And if it's:

"Which specific pages on our website are AI assistants pulling information from?"

OtterlyAI is especially relevant because it explicitly tracks cited URLs and can show which of your pages AI engines use as sources. Otterly

One important caveat: AI citation tracking is not the same thing as website analytics. Google Analytics/Search Console can tell you about traffic and search queries, but they generally cannot tell you "someone asked ChatGPT this exact prompt and ChatGPT subsequently cited /pricing." AI visibility platforms are essentially trying to measure that missing layer.

If you tell me your website/business type and whether you're primarily interested in ChatGPT, Google AI Overviews, Perplexity, or all of them, I can narrow this down to the 2–3 tools I'd actually evaluate, including pricing and what each can/can't measure.

Yes. What you're describing is usually called AI search visibility, AI visibility, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization) software.

These platforms let you define realistic buyer questions—e.g. “What are the best accounting platforms for a 50-person SaaS company?”—then run those prompts against AI search/answer systems and measure whether your company/content appears, which competitors appear, and which URLs get cited. Otterly Arbling

The ones I'd look at

• otterly.ai — Probably the easiest starting point. It supports prompt research and tracks brand mentions and website citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot. It can also show which pages are being cited. Otterly
• tryprofound.com — More enterprise-oriented. Strong if you want deep source/citation intelligence, large prompt sets, competitive analysis and reporting across multiple AI engines. SEO Counselors Bloomiro
• peec.ai — Good for marketing/SEO teams wanting to monitor prompts, competitors, mentions and citations across multiple AI engines. Kitbase Arbling
• ahrefs.com — Worth considering if you're already an Ahrefs customer; its AI visibility functionality can fit into an existing SEO workflow rather than introducing another standalone platform. UX Continuum
• semrush.com — Similar idea if you're already invested in Semrush's SEO ecosystem; its AI visibility tooling adds AI-answer monitoring to the traditional search stack. UX Continuum

What I'd choose

If your primary question is:

“When prospects ask AI assistants questions in our category, do they cite our website—and which of our pages do they cite?”

I'd start with Otterly.AI. It is specifically built around prompt tracking and citation monitoring and has a relatively low barrier to entry. Otterly

If you're doing this at enterprise scale—hundreds/thousands of prompts, many products/markets, competitive benchmarking and serious reporting—I'd evaluate Profound alongside it.

One important caveat: these tools are sampling a nondeterministic system, not measuring an absolute "AI ranking." Different sessions, personalization, location, model versions and whether an AI system is using live search can change the answer. Otterly itself notes that manual results can differ from its monitoring because of personalization/memory effects. Otterly

If you tell me what kind of content you have (e.g. SaaS website, publisher, ecommerce, B2B) and which AI assistants matter most, I can narrow this to the 2–3 tools I'd actually test and what metrics to compare.

If you're monitoring multiple client brands across industries, I’d treat this as an agency-level AI visibility / Share of Voice (SOV) problem, not simply “track ChatGPT mentions.”

My recommendation: start with OtterlyAI, then benchmark against Profound

OtterlyAI is probably the best practical starting point for a multi-client portfolio. It monitors brand mentions and citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot, supports competitive benchmarking, and exposes an API. It also explicitly calculates AI Share of Voice from tracked prompts. Otterly

otterly.ai

I'd shortlist the market like this:

Recent comparisons similarly put Otterly, Peec and Profound among the main platforms, with Profound skewing enterprise and Otterly toward accessible monitoring. Conbersa Arbling

tryprofound.com
peec.ai
zumihq.com

But don't measure SOV as simply "did ChatGPT mention us?"

For an agency, I'd build a standardized AI SOV scorecard for every client.

For each brand, create a prompt universe such as:

• Category discovery: “What are the best [category] companies?”
• Comparison: “[Brand A] vs [Brand B]”
• Problem/solution: “What should I use for [customer problem]?”
• Buying intent: “What are the best [product] for [use case]?”
• Alternatives: “What are alternatives to [competitor]?”
• Local intent: “Best [service] in [city]”
• Industry-specific questions: questions prospects actually ask before buying
• Brand-specific: “Is [brand] good?”, “[brand] reviews”, etc.

Then run the same prompt panel repeatedly and calculate:

AI Share of Voice = brand's weighted appearances ÷ total weighted brand appearances

I'd actually maintain three separate metrics:

1. Mention rate — % of prompts where the brand appears.
2. Weighted SOV — accounts for prominence/position and whether you're the primary recommendation.
3. Citation share — % of cited sources/URLs attributable to the brand or its owned ecosystem.

That's important because a brand appearing as the #1 recommendation shouldn't necessarily count the same as being buried in a list of 10 alternatives. Some newer platforms explicitly distinguish prominence and competitive SOV this way. Zumi AnswerMonk

The multi-client architecture I'd use

Rather than creating an ad-hoc dashboard for every client, establish one common data model:

Agency → Client → Industry → Market → Prompt set → AI engine → Run → Response → Brand mentions → Citations → SOV

For every client, store:

• 50–200 high-value prompts
• 5–15 competitors
• Geographic/language variants where relevant
• ChatGPT + other major answer engines
• Raw AI responses
• Mention position
• Sentiment / recommendation quality
• Cited domains and URLs
• SOV
• Change versus previous period

That gives you a portfolio-level view as well as client-level reporting.

For example:

Agency AI Visibility

Client A: 31% SOV ↑ 6 pts
Client B: 14% SOV ↓ 3 pts
Client C: 42% SOV ↑ 11 pts
Client D: 8% SOV →

Biggest opportunity: Client B — competitor X owns 47% of citations for commercial-intent prompts.

That is much more useful than a dashboard saying “your brand was mentioned 237 times.”

One important caveat

ChatGPT SOV is inherently volatile. The answers can change based on search/retrieval behavior, prompt wording, location, personalization and model changes. Recent reporting, for example, showed substantial changes in which external domains ChatGPT cited over a matter of weeks. Axios

So I'd avoid reporting:

“Your ChatGPT SOV is 27.4%.”

as though that's an objective market statistic.

Instead report:

“27.4% SOV across our standardized 150-prompt benchmark, measured weekly.”

That makes the methodology reproducible and gives the number meaning.

What I'd buy

If you're an agency with perhaps 10–100+ brands, I'd do a short proof-of-concept with OtterlyAI and Profound, using the same 3–5 client brands and identical prompt sets. Don't choose based on the prettiest dashboard.

Score them on:

• Multi-client/workspace management
• Prompt volume
• ChatGPT methodology
• Other AI-engine coverage
• SOV methodology
• Competitor tracking
• Citation extraction
• Historical data
• API/export
• White-label reporting
• Scheduled reports
• Cost per client/prompt
• Ability to segment by industry, country and intent

My default choice: OtterlyAI for a scalable agency monitoring program; Profound if you're dealing with enterprise clients and need substantially deeper intelligence/reporting. Current market comparisons support that general positioning. Conbersa AnswerManiac

If you're building this as an agency product/service, I'd go one step further: use one of these platforms as the data collection layer, then build your own cross-client SOV dashboard and standardized methodology on top. That gives you a proprietary “AI Share of Voice” benchmark rather than reselling somebody else's dashboard.

ChatGPT SOV is inherently volatile. The answers can change based on search/retrieval behavior, prompt wording, location, personalization and model changes. Recent reporting, for example, showed substantial changes in which external domains ChatGPT cited over a matter of weeks. axios.com

So I'd avoid reporting:

“Your ChatGPT SOV is 27.4%.”

as though that's an objective market statistic.

Instead report:

“27.4% SOV across our standardized 150-prompt benchmark, measured weekly.”

That makes the methodology reproducible and gives the number meaning.

What I'd buy

Yes. The category you want is an AI search / answer-engine visibility monitoring tool. It periodically runs the kinds of prompts your customers might ask and records whether your brand appears, disappears, moves up/down, or is replaced by competitors.

Best fits

• otterly.ai — probably the closest match to your description. It monitors prompts daily across ChatGPT and other AI engines, tracking brand mentions, brand coverage, share of voice, sentiment, rankings, and citations. Otterly Otterly
• tryprofound.com — another strong option. Its Answer Engine Insights tracks whether your brand appears in AI answers, visibility/share of voice, citations, sentiment, and positioning; it also runs tracked prompts daily. Profound Profound Knowledge Base

For your specific requirement

If your requirement is literally:

“Alert me when my brand starts appearing—or stops appearing—in ChatGPT answers.”

I'd start with OtterlyAI. Its Brand Coverage metric specifically measures the share of AI responses that mention your brand, while its prompt monitoring lets you track the exact questions that matter to you. Otterly

One important caveat: these tools don't continuously observe every ChatGPT conversation on the internet. They run a defined set of prompts against AI answer engines and monitor the resulting answers. That's actually the useful approach for measuring reproducible brand visibility.

otterly.ai

If you tell me your brand + industry, I can also identify the best tool between OtterlyAI, Profound, Peec AI, Scrunch, and similar platforms, including which ones have the most useful alerts/API/competitor tracking.

If your key requirement is “show me the exact text/passages from my site that ChatGPT used, and tell me where my site/page ranked in the answer,” I’d shortlist these:

1. rankability.com — best fit for rank tracking. It records the exact position of your brand among cited sources, tracks which pages earn citations, and stores a snippet of ChatGPT’s actual response over time. Rankability
2. citations.io — best fit for citation/passsage evidence. Its Citation Map shows the exact URLs and snippets AI engines cite, with rank/freshness signals, while its Answer Archive keeps verbatim, timestamped AI answers. Citations.io
3. otterly.ai — good broader AI-search platform. It tracks which of your URLs are cited, how often they're cited, and the order/position of brands in generated answers across multiple AI engines. Otterly
4. peec.ai — strong for ChatGPT visibility analytics. It identifies which sources influence ChatGPT answers and provides visibility/position metrics, although its notion of “rank” is not a conventional Google-style position because ChatGPT doesn't produce a numbered SERP. Peec AI

My pick

I'd start with Rankability if “rank position” is the most important thing, and Citations.io if “show me exactly what passage/source ChatGPT used” is the most important thing.

One important caveat: ChatGPT doesn't have a stable Google-like ranking position. The answer can change between runs, so the useful metric is usually something like “your page was citation #2 for this prompt on this scan” rather than “you rank #2 in ChatGPT.” Peec explicitly makes this distinction. Peec AI

If you tell me your site + whether you care about ChatGPT only or ChatGPT/Perplexity/Gemini/etc., I can narrow this down to the best 2–3 platforms and compare their pricing, exact passage-level evidence, API access, and historical tracking.

If by “ChatGPT rank data” you mean tracking where your brand/product appears in ChatGPT answers for a set of prompts, there are a few good options. I’d prioritize platforms that expose the underlying data through an API rather than trying to build the ranking collection yourself.

Best options

1. Peec AI — probably the easiest fit

peec.ai

Peec specifically tracks ChatGPT rankings/position, mention frequency, citations, sentiment and share of voice. More importantly for your use case, its API can feed raw chats, sources and metrics into BigQuery, Tableau, Power BI, or a custom internal dashboard. Peec AI Peec AI

Their data model is particularly convenient if your existing dashboard already has SEO metrics:

Your Analytics Dashboard
        ↑
     API / ETL
        ↑
     Peec AI
        ↓
ChatGPT | Gemini | Perplexity | AI Overviews | ...

I'd choose Peec if your goal is essentially: “Add an AI-search/ChatGPT ranking section to our existing dashboard without building the collection infrastructure ourselves.”

2. Profound — stronger enterprise option

tryprofound.com

Profound's API exposes metrics including share of voice, mentions, visibility score, executions and average position, with dimensions such as date, region, topic, model, prompt, asset and persona. Profound

It also explicitly describes its Answer Engine Insights dataset as being generated from repeated prompt runs against answer engines, with metrics including visibility, citations, sentiment, SOV and positioning. Profound Knowledge Base Profound

This is the one I'd investigate if you're building a large multi-client marketing/SEO analytics platform and need more sophisticated segmentation.

3. OpenAI API — only if you want to build it yourself

developers.openai.com

You can query OpenAI programmatically and build your own pipeline, but the API isn't a turnkey “ChatGPT SEO rank tracker.” You'd need to define the prompts, execute them on a schedule, parse responses, determine brand positions, normalize results, and store historical data. OpenAI's Responses API supports programmatic model responses and tools such as web search. OpenAI Platform OpenAI Developers

What I'd recommend

If you already have something like Looker, Tableau, Power BI, Snowflake, BigQuery, or a proprietary analytics dashboard, I'd shortlist:

Peec → simplest path
Profound → more enterprise/AEO-oriented
OpenAI API → maximum control, maximum engineering

One important distinction: ChatGPT “rank” isn't equivalent to Google keyword rank. A useful dashboard should probably store the prompt + brand position + whether mentioned + competitors + citations + sentiment + model + date, rather than just a single rank number. Peec and Profound both support much of this richer measurement model. Peec AI Profound

If you tell me what your existing analytics dashboard is built on (e.g. Power BI, Tableau, Looker, Grafana, custom React, Snowflake, BigQuery), I can recommend the specific integration architecture and API between it and Peec/Profound.

Yes. What you’re looking for is generally called AI search visibility / GEO monitoring: a platform repeatedly runs the kinds of questions your customers ask in ChatGPT, tracks your brand and competitors, and alerts you when the competitive picture changes.

Best fits

• otterly.ai — probably the closest fit if your specific requirement is “alert me when a competitor overtakes us.” It tracks brand mentions, rank/order, share of voice, citations, and competitors across ChatGPT and other AI engines. Its analytics specifically identify prompts where competitors appear and you don't. OtterlyAI Otterly
• Profound — stronger choice for a larger enterprise program. It is one of the leading enterprise AI-visibility platforms and focuses heavily on competitive visibility and monitoring. SurfacedBy AI Sightline
• Peec AI — good middle ground for marketing teams wanting competitive benchmarking and AI-answer analytics without going as enterprise-heavy as Profound. Promptwatch Conbersa
• Promptwatch — worth considering if you want monitoring plus more workflow/action capabilities rather than simply a dashboard. Promptwatch

The alert you actually want

I'd configure the platform around a metric like:

Alert me when Competitor X moves ahead of our brand in ChatGPT for any tracked commercial prompt.

For example:

I'd also track share of voice, mention rate, average position, citation share, and sentiment, rather than just whether you're mentioned. Otterly, for example, explicitly tracks these dimensions and compares them against named competitors. Otterly

My pick: If your primary requirement is competitive ChatGPT alerts, I'd start with OtterlyAI. If you're building a serious enterprise GEO/AI-search intelligence program, I'd evaluate Profound alongside it.

If you tell me your industry, number of competitors, and approximate number of ChatGPT prompts you want monitored, I can narrow this down to the 2–3 platforms that fit best and compare their alerting, ChatGPT coverage, API/Slack integration, and pricing.

If your goal is specifically “what percentage of AI-generated answers mention my brand for a defined set of keywords/prompts, versus competitors?”, I’d shortlist these:

• otterly.ai — best straightforward choice. It lets you define the prompts your buyers might use and tracks brand mentions, share of voice, average rank, sentiment, and citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. You can break SOV down by prompt and engine. Otterly Otterly
• ahrefs.com — best if you already use Ahrefs. It has AI Share of Voice, competitor benchmarking, custom prompts, and a large database of search-derived prompts. It also covers ChatGPT, Gemini, Perplexity, Copilot and Google's AI experiences. Ahrefs
• Profound — best for enterprise/deep analysis. It is positioned more toward large-scale AI visibility measurement and prompt analytics; current comparisons put it at the high end for engine coverage and analytical depth. DataDab Aelo
• Peec AI — worth considering for marketing teams/agencies. It focuses heavily on AI-search analytics, prompt research and competitive brand monitoring. DataDab

My pick

Start with OtterlyAI if you have a finite list of keywords/brand terms such as:

“best CRM for startups”
“HubSpot alternatives”
“CRM for SaaS companies”
“Acme CRM”

You can turn those into a recurring prompt set and measure something like:

AI Share of Voice = your brand mentions / total competitor + brand mentions

That is more useful than simply asking whether ChatGPT mentions you, because you can see which queries you win, which competitors displace you, and how that changes over time. Otterly explicitly distinguishes coverage (do you appear?) from share of voice (how much of the competitive conversation do you own?). Otterly

If you tell me your approximate number of keywords/prompts and whether you're SMB, agency, or enterprise, I can narrow this to the best 1–2 tools and compare price, engines, keyword/prompt limits, SOV methodology, and API access.

Yes — what you’re looking for is generally called AI brand monitoring, AI visibility tracking, or GEO/AEO monitoring.

My top picks

• otterly.ai — probably the easiest starting point. It tracks brand mentions, sentiment, share of voice, and citations across ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews/AI Mode, and Copilot. You define the prompts your customers might ask, and it runs them repeatedly to see whether your brand appears and how it compares with competitors. Otterly Otterly
• tryprofound.com — a stronger choice if you're an enterprise/large marketing team. Its Answer Engine Insights tracks visibility, citations, sentiment, positioning, and share of voice across AI answer engines. Profound Knowledge Base Profound
• Peec AI — another dedicated AI-search visibility platform worth evaluating, particularly if you're focused on measuring how your brand ranks against competitors inside AI answers. Haystack

What I'd measure

Don't just track "Does ChatGPT mention my brand?"

Set up a library of real customer questions, such as:

• "What are the best [product category] brands?"
• "What's the best [product] for [use case]?"
• "Which companies offer [service]?"
• "What are alternatives to [competitor]?"
• "Is [your brand] worth it?"
• "Compare [your brand] vs [competitor]."
• "What should I buy if I need [problem your product solves]?"

Then monitor:

Brand mention → position/ranking → sentiment → recommendation → citation → competitor mentions → share of voice → changes over time.

That's considerably more useful than traditional web/social listening because you're measuring what an AI assistant actually tells a potential customer about you.

If you tell me your brand + industry, I can also suggest the best tool for your specific situation and the 10–20 prompts I'd monitor first.

Yes. If by “AI share of voice” you mean a dashboard that runs a defined set of brand/category/comparison prompts across ChatGPT, Perplexity, Gemini, Google AI Overviews, etc., then measures how often your brand appears versus competitors, several platforms now do this.

Strongest options

• peec.ai — probably the closest match to your description. It has explicit Share of Voice, visibility, position, sentiment, prompt-level tracking, and side-by-side competitor benchmarking. You can track specific prompts such as “best [category] for X,” “Brand A vs Brand B,” or branded queries. Its dashboard can break performance down by model, topic, geography, and competitor. Peec AI Peec.ai Docs
• tryprofound.com — particularly strong if you're looking at this from an enterprise/SEO/GEO perspective. Its Answer Engine Insights product tracks visibility rank, share of voice, citation share, sentiment and position, including competitive comparisons at the prompt/topic/platform level. It also identifies “true” competitors based on who is actually winning AI citations, rather than relying solely on your manually defined competitor set. Profound Profound Knowledge Base
• zumihq.com — more focused on a straightforward brand-vs-brand AI visibility dashboard. It explicitly shows mention rate, Share of Voice, average position, competitor comparisons and the sources AI engines cite. Zumi
• surva.ai — another newer option with a dedicated AI Visibility dashboard covering visibility score, Share of Voice, platform breakdown, competitor comparisons and trends across ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews. Surva.ai
• rivalsee.com — interesting if you want to organize monitoring around customer segments/personas, rather than just a conventional keyword list. It tracks brand mentions, citations and competitor SOV across several AI engines. RivalSee

If your specific use case is “brand queries”

I'd distinguish between two things:

One important nuance: AI “Share of Voice” isn't quite the same thing as traditional search SOV. For example, Peec defines SOV as your brand's share of all tracked brand mentions in AI responses, while visibility is the percentage of responses in which you appear at all. Peec.ai Docs Peec AI

So if you're specifically building a “Brand X vs Brand Y” dashboard for queries like “Brand X alternatives,” “Brand X vs Brand Y,” “best [category] brands,” “is Brand X worth it?”, Peec and Profound are the two I'd investigate first.

If you tell me whether you're looking for a tool to buy or a dashboard/API you could build into your own product, I can narrow this down considerably.

Yes. What you’re describing is usually called AI visibility / GEO (Generative Engine Optimization) tracking: monitoring how often assistants mention your brand, what they say about it, and how that varies by LLM, geography, language, prompt, and competitor.

Best fit: Profound

tryprofound.com is probably the strongest match if geographic and language differences are central to your question.

• Tracks brand visibility, share of voice, sentiment, citations, and positioning across major AI assistants. Profound Profound Knowledge Base
• Lets you break results down by countries, cities, and languages, specifically to identify regional differences. Profound
• Supports 30+ languages and 150+ regions. Profound
• Can track the same prompt separately by market, so you can answer questions like: “Does ChatGPT recommend us more in Germany than the U.S.?” or “What does Gemini say about us in Spanish vs. English?” Profound
• Covers ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews/AI Mode, Copilot, Grok, and DeepSeek. Profound

Two good alternatives

Peec AI — a good option if you primarily want straightforward mention/visibility, position, sentiment, and share-of-voice tracking. It records the geographic location associated with each prompt and can show where your brand is mentioned. Peec AI Peec.ai Docs

peec.ai

Ahrefs Brand Radar — worth considering if your team already uses Ahrefs for SEO. Its AI Visibility Checker tracks mentions across ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews and reports topics, mentions, and cited domains/pages. Ahrefs

ahrefs.com

My recommendation

If the requirement is specifically:

“Show me how AI assistants talk about our brand differently across countries and languages.”

I'd shortlist Profound first, Peec second, and Ahrefs if you want AI visibility integrated with an existing SEO stack.

One important distinction: these tools generally run controlled prompts in different regions/languages; they aren't necessarily observing the private conversations individual users are having with ChatGPT. So you're measuring AI-answer visibility under comparable conditions, rather than a census of every brand mention happening in the wild. Profound Peec.ai Docs

If you tell me your brand/category and the countries + languages you care about, I can also compare the tools specifically on regional/language tracking, prompt volume, LLM coverage, API/export capabilities, and pricing.

Yes. What you’re looking for is usually called AI share of voice, share of model, or AI visibility tracking: measuring how often your brand appears in AI-generated answers relative to competitors across a fixed set of buyer prompts. Geo Software Rankings Verity Score

Tools I’d shortlist

• tryprofound.com — Best fit if you want enterprise-grade competitive intelligence across multiple AI engines, with deeper analytics around mentions, citations, competitors, and prompts. It’s commonly positioned as an enterprise leader. AnswerManiac Refine AI
• peec.ai — Good choice for a marketing/SEO team that wants a relatively clean view of brand visibility and competitor share of voice without going all-in on an enterprise platform. Sapian Metrics Omid Saffari
• otterly.ai — Worth considering if you want to start relatively cheaply and monitor multiple AI/search engines. AnswerManiac Refine AI
• citedspy.com — Particularly interesting for a quick/free competitive snapshot. Its checker reports visibility, competitor share of voice, prompt-level rankings, sentiment, and cited sources across ChatGPT, Perplexity, Gemini, Claude, and Grok. CitedSpy
• modelmention.io — Another straightforward option focused specifically on visibility, position, share of voice, sentiment, and citations, with tracking across ChatGPT, Gemini, and Perplexity. ModelMention

If your primary question is literally “What % of AI answers mention us vs. Competitor A/B/C?”, I'd start with Peec or Profound. If you just want to validate the concept before buying anything, try CitedSpy's free checker. AnswerManiac CitedSpy

One important caveat: don't rely on a single ChatGPT query. AI answers are nondeterministic, and different engines can surface substantially different brands and sources. A meaningful measurement should use many buyer prompts, repeated runs, multiple engines, and a consistent competitor set/time window. Verity Score foglift.io

If you tell me your brand + 3–5 competitors + industry, I can also recommend which of these tools is the best fit and what metrics I'd track.

If you mean tracking how often your brand appears in AI assistant answers (ChatGPT, Gemini, Claude, Perplexity, voice assistants) versus competitors, you’re looking for an AI visibility / Generative Engine Optimization (GEO) / Answer Engine Optimization (AEO) monitoring tool. These tools usually work by running a fixed set of prompts, capturing AI outputs, and calculating metrics such as mention rate, citation rate, position, sentiment, and share of voice. Corbelix Visibility.so

Some of the main options:

For voice channels specifically (Alexa, Siri, Google Assistant-style experiences), measurement is harder because many assistants do not expose their answers in a crawlable way. Most commercial platforms today focus on AI search/chat outputs rather than true voice assistant conversations. Locafy A practical approach is usually:

1. Define a prompt set (e.g., 500 customer questions).
2. Run those prompts across target assistants.
3. Record: - brand mentioned?
4. competitor mentioned?
5. rank/order of recommendations
6. citations/sources used
7. sentiment
8. Calculate:

AI Share of Voice = your brand mentions (or citations) ÷ total brand mentions across tracked answers

SearchDock Geo Software RankingsIf you are building this internally, the stack is usually:

• API access where available (for example, model APIs)
• browser automation for assistants without APIs
• prompt orchestration
• output storage
• entity extraction/classification
• SOV dashboarding

For a large brand, I’d shortlist Profound, Otterly, Semrush, and SearchDock; for a leaner marketing team, ModelMention or Visibility.so are closer to a ready-made dashboard. Foglift Visibility.so ModelMention

If you’re a small ecommerce store and genuinely budget-constrained, I’d start with otterly.ai.

My ranking

1. Otterly.ai — best budget pick

• Starts at $29/month for 15 tracked prompts. CiteDaily AEO Labs
• Tracks mentions/citations and visibility across ChatGPT, Google AI Overviews, Perplexity and Copilot. CiteDaily
• Good for answering the basic question: “Are AI engines recommending/citing my store, and who are they recommending instead?”
• The downside: Gemini and Google AI Mode are paid add-ons, and the jump from 15 to 100 prompts is substantial. CiteDaily AEO Labs
• peec.ai — better if you can spend ~$95/mo

• Starter is $95/month for 50 prompts, 3 models and daily tracking. Peec AI
• Stronger reporting around share of voice, position, sentiment and the sources AI cites. Peec AI
• I'd choose this over Otterly if AI search is already generating meaningful sales for you and you want to optimize systematically.
• tryprofound.com — overkill for your situation

• Much more geared toward larger organizations and sophisticated AI-search programs. Current comparisons put its useful tiers well above what I'd recommend for a small store. Loudmink SEO Counselors

What I'd actually do

For a tight-budget ecommerce store, don't try to track hundreds of prompts. Start with ~15 highly commercial questions, such as:

• “best [product category] for [use case]”
• “[product category] alternatives”
• “best [product category] under $100”
• “where to buy [product]”
• “[competitor] alternatives”
• “best [product type] for [customer type]”

Track your store plus 3–5 competitors.

Then watch three numbers:

AI citation share → brand mention rate → position/recommendation frequency

The important distinction is that being mentioned isn't the same as being cited as a source. For ecommerce, I would particularly care about which third-party sites AI is using to form its recommendation—because those are often the sites you need to get your products/brand mentioned on.

Bottom line:

• <$50/mo: Otterly
• ~$100/mo and want better citation intelligence: Peec
• >$300/mo: only consider the heavier platforms if AI search is already a significant acquisition channel.

If you tell me your monthly budget (e.g. $30, $50, $100) and what you sell, I can narrow this down to the best option and tell you exactly what prompts I'd track.

Yes. If your goal is specifically “we changed a piece of content → did our AI share of voice/citation share improve?”, I’d look at dedicated AI-visibility/GEO platforms rather than traditional SEO rank trackers.

My shortlist

What I'd choose

For your exact use case, I'd start with Peec or Profound.

The important capability isn't simply tracking whether your brand is mentioned. You want the tool to preserve a stable prompt set and let you compare:

Pre-update: Brand SOV = 12%
Content update: revised comparison page
Post-update: Brand SOV = 21%
Change: +9 percentage points

Ideally, you also want citation share, competitor share, answer position, sentiment, and which URLs the AI cited.

That's important because AI visibility can move substantially even without changes to your site. Recent data, for example, showed Reddit's share of ChatGPT citations falling sharply over a few weeks—illustrating how volatile these measurements can be. Axios

One thing I'd insist on

Don't evaluate these tools based on a single “AI visibility score.” Set up an experiment framework:

1. Freeze 50–200 representative buyer prompts.
2. Record baseline SOV/citation share for 2–4 weeks.
3. Update specific pages.
4. Keep the prompt set unchanged.
5. Continue measuring for several weeks.
6. Compare treated pages/topics vs. untouched pages/topics where possible.
7. Look at citations, not just mentions.

That gives you a much better answer to “did our content change cause AI visibility to improve?” rather than merely “did our AI score go up?”

If you tell me your company size, approximate monthly budget, and whether you're optimizing for ChatGPT only or ChatGPT + Google AI Overviews + Perplexity, I can narrow this to the best 2–3 options and compare their measurement capabilities.

The important capability isn't simply tracking whether your brand is mentioned. You want the tool to preserve a stable prompt set and let you compare:

Pre-update: Brand SOV = 12%
Content update: revised comparison page
Post-update: Brand SOV = 21%
Change: +9 percentage points

Ideally, you also want citation share, competitor share, answer position, sentiment, and which URLs the AI cited.

That's important because AI visibility can move substantially even without changes to your site. Recent data, for example, showed Reddit's share of ChatGPT citations falling sharply over a few weeks—illustrating how volatile these measurements can be.

One thing I'd insist on

Yes — there’s now a fairly crowded category around AI Search Visibility / GEO reporting for agencies, and several platforms specifically support share of voice (SoV), multi-client management, and white-label dashboards/reports.

Strongest options I’d look at

A particularly interesting one is AgencyAnalytics because it isn't just an AI visibility product: its AI Tracker can put AI visibility alongside Google Analytics, Google Ads, Search Console, SEO, social, etc., inside the same client dashboard. AgencyAnalytics

If you want a dedicated GEO product, Geneo, Tower GEO, Qwairy, and Outercite are closer to what you're describing. For example, Geneo explicitly offers a client portal on the agency's domain with the agency's logo/branding and Share of Voice metrics. Geneo

One important distinction

There are actually two products hiding inside your question:

1. AI visibility measurement

• % of prompts where client appears
• Share of Voice vs. competitors
• position/rank in AI answers
• mentions
• citations
• sentiment
• ChatGPT vs. Gemini vs. Perplexity vs. Google AI, etc.
• Agency reporting infrastructure

• multiple client workspaces
• your logo/domain
• client login
• automated monthly reports
• custom metrics
• API / Looker Studio integration
• potentially your own pricing/margin

The second is where the market is still less mature. For example, Peec AI takes a more flexible approach: agencies can build branded Looker Studio dashboards from its data, while Gumshoe explicitly says it doesn't currently provide a fully branded client portal and expects agencies to build that layer through its API. Peec AI Gumshoe AI

If you're evaluating this as a product opportunity

There is definitely competition, but I wouldn't conclude that the market is solved.

The interesting gap is potentially "AgencyAnalytics for AI search" rather than another GEO tracker:

Agency logs in → adds 50 clients → every client gets a white-label AI Share of Voice dashboard → automatically incorporated into the agency's existing SEO reporting → client sees exactly what changed and why.

That is more compelling than simply showing an AI visibility score.

There are already products moving toward this: Qwairy, for example, emphasizes portfolio-level dashboards and isolated client workspaces, while Rankfender combines AI SoV with other marketing data and automated reports. Qwairy RankFender

If you're considering building this, I can also map out the current competitors feature-by-feature (pricing, APIs, white-label domains, client portals, engines tracked, SoV methodology, Looker Studio, etc.) and identify where there still seems to be a gap.

If your priority is comparing AI share of voice across countries and languages, I’d shortlist these:

1. Profound — my first choice

Profound is probably the closest match if you need a global AI SOV operating system, rather than just an AI rank tracker.

Its Answer Engine Insights supports Share of Voice, visibility, citations and positioning, with filters for regions, platforms, prompts, topics and personas. More importantly for your question, Profound says it supports 30+ languages and 150+ regions. Profound Profound Knowledge Base

You can therefore construct something like:

Brand × Country × Language × AI engine × Topic × Competitor → AI Share of Voice

It also has a dashboard specifically designed for SOV reporting and filtering by regions. Profound

Best if: you're a multinational brand and want to answer questions such as “Why are we 31% SOV in Germany but only 8% in France?”

2. Peec AI — particularly good for country comparisons

Peec is the one I'd demo alongside Profound.

It explicitly tracks visibility, position, sentiment and Share of Voice, and lets you benchmark competitors across AI engines. Peec AI

What's particularly relevant is its country-gap workflow: Peec can break brand visibility and SOV down by country code, then identify which competitor dominates each market. Peec AI

Best if: your main question is “Which countries are we losing AI visibility in, and to whom?”

3. Semrush — best if you want AI + conventional search

If your organization already uses Semrush, I'd seriously consider consolidating there. Semrush has been moving aggressively into AI Visibility/GEO while retaining its traditional international SEO capabilities. MarketsandMarkets

The advantage isn't necessarily that its AI SOV measurement is superior to Profound/Peec; it's that you can compare:

Google organic SOV → AI SOV → traffic → competitors

within a broader search intelligence stack.

One important caveat

Don't treat "AI Share of Voice" as a standardized industry metric. Different vendors calculate it differently. For example, Profound defines SOV as your brand's mentions divided by total brand mentions across the tracked answers, while other vendors use position-weighted or impression-like methodologies. Profound Knowledge Base Verity Score

For a serious multinational measurement program, I'd therefore insist that the vendor lets you inspect:

• Exact prompts being measured
• Country/locale used when querying the model
• Language of the prompt and language of the answer
• AI engine/model
• Competitor set
• Raw answer/mention data
• SOV calculation methodology
• Sampling frequency
• Historical data
• Ability to export data/API it
• Consistent prompt sets across markets

Otherwise, an apparent "France vs Germany SOV gap" can partly be a measurement-design artifact.

My ranking for your specific requirement

If you're evaluating software today:

1. 🥇 Profound — strongest fit for enterprise, multilingual, multi-country AI SOV
2. 🥈 Peec AI — excellent for country-by-country competitor gaps and easier operational analysis
3. 🥉 Semrush — strongest if AI visibility needs to sit alongside international SEO
4. Similarweb — especially interesting if market/traffic intelligence matters as much as SOV
5. OtterlyAI — good if you want a more lightweight monitoring solution

If you tell me roughly how many countries/languages you need (e.g. 10 vs 50), your company size, and whether you care about ChatGPT/Claude/Gemini/Perplexity/Google AI Overviews, I can narrow this to 2–3 platforms and compare their actual geographic, language, prompt, API, and enterprise capabilities.

You can therefore construct something like:

Brand × Country × Language × AI engine × Topic × Competitor → AI Share of Voice

It also has a dashboard specifically designed for SOV reporting and filtering by regions. Profound

Best if: you're a multinational brand and want to answer questions such as “Why are we 31% SOV in Germany but only 8% in France?”

2. Peec AI — particularly good for country comparisons

Peec is the one I'd demo alongside Profound.

It explicitly tracks visibility, position, sentiment and Share of Voice, and lets you benchmark competitors across AI engines. Peec AI

What's particularly relevant is its country-gap workflow: Peec can break brand visibility and SOV down by country code, then identify which competitor dominates each market. Peec AI

Best if: your main question is “Which countries are we losing AI visibility in, and to whom?”

3. Semrush — best if you want AI + conventional search

If your organization already uses Semrush, I'd seriously consider consolidating there. Semrush has been moving aggressively into AI Visibility/GEO while retaining its traditional international SEO capabilities. MarketsandMarkets

The advantage isn't necessarily that its AI SOV measurement is superior to Profound/Peec; it's that you can compare:

Google organic SOV → AI SOV → traffic → competitors

within a broader search intelligence stack.

One important caveat

Don't treat "AI Share of Voice" as a standardized industry metric. Different vendors calculate it differently. For example, Profound defines SOV as your brand's mentions divided by total brand mentions across the tracked answers, while other vendors use position-weighted or impression-like methodologies.

For a serious multinational measurement program, I'd therefore insist that the vendor lets you inspect:

I’d recommend peec.ai for this specific use case.

It is built around AI share of voice, not just generic brand monitoring: you can track your brand against named competitors across AI engines, see where you’re gaining/losing visibility, and monitor the same prompt set over time. Peec says its metrics update daily and include visibility, position, sentiment, and share of voice. Peec AI Peec AI

Why I’d pick it

• Direct competitor SOV: See your percentage of AI mentions versus competitors. Peec AI
• Drop detection: Track trends over time so a decline in visibility becomes apparent rather than relying on occasional manual checks.
• Prompt-level diagnosis: You can identify the specific customer questions where competitors are appearing and you're not.
• Multiple AI surfaces: It tracks major environments including ChatGPT, Gemini, Perplexity, Google AI Overviews and AI Mode. Peec AI
• Actionable competitive gaps: It also identifies sources/citations that competitors are getting but you aren't, which is useful for figuring out why your SOV dropped. Peec AI

One caveat: if the requirement is specifically “send me a Slack/email alert the moment our SOV falls below X% or drops X points versus competitor Y,” I’d verify the alerting/threshold functionality during a trial rather than assuming that every SOV tracker supports that exact trigger.

If you want enterprise-grade monitoring and more sophisticated alerting/reporting, I’d also put tryprofound.com on the shortlist. It explicitly supports competitor comparisons and SOV tracking. Profound

My pick: Peec for a marketing team that wants a practical competitive SOV dashboard; Profound if this needs to become a formal enterprise intelligence system.

If your specific requirement is “alert me when our AI share of voice drops relative to key competitors,” I’d shortlist these:

My pick: peec.ai

Peec is probably the cleanest fit for a marketing team that wants competitive AI visibility monitoring + alerts without building the workflow yourself.

• Tracks share of voice against named competitors across AI platforms. Peec AI Peec AI
• Lets you track the same prompt set over time, so you're comparing apples to apples.
• It has a documented workflow for daily competitor-surge alerts in Slack, including which models and prompts a competitor gained on. Peec AI
• It can also identify sources where competitors are cited but you aren't, which makes the alert actionable rather than just “SOV fell.” Peec AI

A useful alert I'd configure:

“Alert me in Slack if our 7-day AI share of voice falls ≥5 percentage points versus the previous 7 days, or if any key competitor gains ≥5 points relative to us. Include the affected AI models, prompts, and competitor citations.”

If you're enterprise: tryprofound.com

Profound is the stronger choice if you need deeper enterprise-grade competitive intelligence. It tracks share of voice, visibility rank and citation share across major AI platforms, and its monitoring can trigger alerts when visibility falls below a threshold. Profound Profound Knowledge Base

Quick decision

One important distinction: don't alert merely when your absolute mentions fall. AI answers fluctuate. Alert on relative SOV vs. competitors over a rolling window, ideally with a minimum percentage-point change, so you don't get flooded with noise.

Yes. This has become its own category of software, often called AI visibility, AI Share of Voice (AI SoV), or Generative Engine Optimization (GEO) platforms.

The more advanced products do much more than tell you whether a competitor is winning—they explain which content is winning, for which prompts, on which AI engines, and why. Slate arXiv

Here's what the best solutions typically provide:

Some of the leading platforms include:

• Profound — Enterprise-focused AI visibility platform with deep competitor and citation tracking.
• Semrush AI Visibility Toolkit — Good if you're already using Semrush; combines AI visibility with traditional SEO workflows. TechRadar Reddit
• Ahrefs Brand Radar — Tracks brand mentions and AI visibility alongside backlink and keyword data. TechRadar
• Peec AI — Focused on monitoring AI answer visibility across multiple models.
• Otterly AI — Tracks prompts, citations, and brand visibility.
• Slate — Combines AI Share of Voice monitoring with content recommendations. Slate

What a good workflow looks like

Instead of asking "What keywords rank?", these platforms answer questions like:

• "For 'best CRM for startups,' ChatGPT recommends HubSpot, Notion, and Attio."
• "HubSpot is cited 62% of the time."
• "The pages being cited are comparison pages and implementation guides."
• "Your site has no equivalent content."
• "Creating these three assets would increase your likelihood of being cited."

That moves the conversation from SEO rankings to AI recommendation market share.

The feature I'd prioritize

If competitor intelligence is your primary goal, look for a tool that can show:

• the exact prompt that triggered the answer
• the full AI response
• every cited source
• which competitor page was referenced
• why that page was selected (freshness, structure, authority, comprehensiveness)
• how your page differs

Those insights are much more actionable than a simple "you have 18% AI share of voice."

If you're evaluating vendors

I'd shortlist them based on these five capabilities:

1. Multi-model coverage (ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews).
2. Competitor content and citation tracking (not just brand mentions).
3. Prompt-level historical trends.
4. Automated content gap recommendations.
5. API or data export for integrating with your analytics stack.

This category is evolving quickly, but the strongest products have shifted from simply measuring visibility to helping teams understand why competitors are being cited and what content to build to win those AI answers. Slate arXiv

Yes. For a local business website, I’d focus on tools that track both brand mentions and the actual URLs AI assistants cite, not just generic “AI visibility.”

My picks

1. otterly.ai — best overall for a local business

• Tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude.
• Shows which pages on your site are actually cited, how often, competitors being cited instead, and share of voice.
• Runs tracked prompts daily.
• Particularly useful if you're trying to answer questions like “Who does ChatGPT recommend for [service] near [city]?” Otterly Otterly
• Current comparisons put its entry point around $29/month, making it considerably more approachable than enterprise platforms. Citation Hawk ToolChase
• peec.ai — best for deeper GEO analysis

• Strong choice if you want to understand why competitors are being cited instead of you and analyze citation/content gaps.
• It covers major AI surfaces including ChatGPT, Perplexity, Gemini, Copilot and Google's AI experiences. Citation Hawk Kitbase
• I'd choose this over Otterly if you're doing serious ongoing content/GEO work rather than simply monitoring your visibility.
• semrush.com — best if you already use Semrush

• Its AI Visibility Toolkit combines AI visibility with traditional SEO, competitor research and site auditing.
• Particularly attractive if you don't want another standalone SaaS subscription. Current comparisons put the AI toolkit around $99/month. Citation Hawk
• ahrefs.com — best for an existing Ahrefs user

• Worth considering if your SEO work already lives in Ahrefs.
• Its AI visibility capabilities are increasingly integrated with its broader SEO data, but I'd pick Otterly/Peec if AI citation monitoring itself is your primary objective. ToolChase

What I'd use for a local business

For example, suppose you own a roofing company in Leesburg.

I'd create prompts such as:

• “Best roofing companies in Leesburg VA”
• “Who should I call for a roof replacement in Leesburg?”
• “Best roof repair company near Leesburg”
• “Most reliable roofing contractors in Loudoun County”
• “How much does roof replacement cost in Leesburg VA?”
• “Roofing companies with the best reviews in Northern Virginia”

Then track weekly/daily:

AI platform → Was I mentioned? → Was my website cited? → Which URL? → Position/order → Which competitor appeared? → What source did the AI use instead?

That last part is crucial. A tool telling you “your AI visibility is 14%” is much less useful than telling you:

ChatGPT recommended Competitor A 7/10 times and cited their /roof-replacement/ page. Your site appeared 2/10 times, but when it did, it cited /services/roofing/.

That gives you something actionable.

My recommendation

Start with OtterlyAI. It's the best fit if your main question is “How often are AI assistants mentioning my local business and citing my website?” Its website-citation tracking specifically records the URLs AI engines use, rather than treating every brand mention as equivalent. Otterly

If you're an SEO agency managing multiple local businesses, I'd look more closely at Peec AI or an agency-oriented platform because reporting and multi-client management become more important.

If you tell me what type of local business you have and roughly how many locations/websites you're monitoring, I can narrow this down to the best 2–3 options and compare price, local-search tracking, citation-level data, competitor tracking, and agency reporting.

If you mean finding which exact passages from your website are being reused or quoted by AI answer engines (ChatGPT, Google AI Overviews, Perplexity, Claude, Gemini, etc.), the category of tools you’re looking for is usually called AI visibility / AI search optimization / LLM citation tracking.

Some tools that can help:

• ahrefs.com — Tracks search visibility and can help identify content performance signals, though it is not a dedicated LLM quotation tracker.
• semrush.com — Its AI visibility features are aimed at monitoring brand mentions and presence in AI-generated search experiences.
• getprofound.com — Built specifically for tracking how brands appear in AI answers and which sources are cited.
• otterly.ai — Monitors AI search results and citations across AI platforms.
• peec.ai — Tracks visibility and citations in AI search responses.
• scrunch.ai — Focuses on AI search visibility and how content is represented in AI answers.

For paragraph-level attribution (e.g., “AI systems are quoting this exact 47-word paragraph from /pricing”), the technology is still emerging. Most current tools primarily show:

• which queries triggered an AI answer containing your brand/site
• whether your domain was cited
• which URL was cited
• competitors cited alongside you
• sometimes the quoted text or citation context

A practical workflow is:

1. Use an AI visibility tracker to collect AI answers where your domain appears.
2. Export the cited URLs.
3. Compare the AI answer text against your pages using: - exact phrase matching
4. semantic similarity tools
5. embeddings/vector search
6. a crawler that stores your page chunks

If you want true snippet-level tracking, you’d typically build a pipeline:

• crawl your site → split pages into chunks → store embeddings → collect AI answers → run similarity matching against your chunks.

If you tell me whether you mean your own site’s content being quoted by ChatGPT/Perplexity/Gemini, or any AI crawler traffic (GPTBot, ClaudeBot, etc.) accessing your pages, the best tool choice changes.

For your use case, you want a multilingual GEO/AI-visibility platform that can run the same intent queries by language + country/region, then show differences in mentions, citations, competitors, and source domains.

Best fits

• menra.ai — probably the closest match. It explicitly supports region-, language-, and persona-aware tracking, and separates visibility by market while showing which sources AI cited. Menra
• citenso.com — especially interesting if Europe is important: it advertises 27 languages and 30+ countries, with citation/visibility analytics and geographic targeting. Citenso
• citeview.ai — useful for comparing the same brand across countries; its example dashboard explicitly contrasts US, Germany, and Brazil visibility and supports multiple languages/personas. Citeview
• askylabs.com — stronger if you want the tool to go beyond measurement into recommendations. It says it runs prompts in target languages with geographically scoped agents and compares citation quality, visibility, and sentiment across markets. Asky
• peec.ai — worth evaluating for very broad language coverage; a recent 2026 comparison reports 115+ languages. Citadex

What I'd choose

If the core question is “Why do we get cited in English/US but not German/DE, Japanese/JP, etc.?”, I'd start with Menra or Citenso.

The important thing is not merely a global “AI visibility score.” You want a matrix something like:

That lets you distinguish translation/content gaps from regional authority/source gaps. Research on multilingual AI search likewise finds that identical queries can produce different cited sources depending on language and locale. CEAVERS OnlyAEO

If you tell me your target languages/countries and which AI engines matter most, I can narrow this to the best 2–3 tools and tell you exactly what metrics to compare.

If your goal is “which exact user questions cause ChatGPT/Perplexity/Gemini/etc. to cite my how-to guides?”, you want a GEO (Generative Engine Optimization) / AI visibility tracker rather than a normal SEO rank tracker. The best tools capture the prompt, the AI answer, and the cited URLs so you can map query → answer → citation → your guide. Geol.ai

My shortlist:

For a how-to guide library, I’d prioritize these capabilities:

1. Prompt-level tracking

• “How do I configure X?”
• “What is the best way to fix Y?”
• “Step-by-step guide for Z”
• Not just “is my brand mentioned?”
• Citation extraction

• The exact guide URL cited
• The competing pages cited instead
• The surrounding answer text that triggered the citation
• Prompt discovery

• Tools that suggest likely customer questions are more valuable than manually entering hundreds of prompts.
• Historical snapshots

• You want to see: “After updating my guide on Aug 1, these 14 prompts started citing it.”

A practical setup for most content teams:

• Use Citations.io or Otterly for continuous monitoring.
• Export winning prompts.
• Add those prompts to a spreadsheet/database with: - query
• intent
• AI engine
• cited page
• competing citation
• guide improvements made

One caveat: AI citation tracking is still probabilistic. A tool is usually sampling prompts and answers rather than observing every real ChatGPT conversation, so look for platforms that store raw answer snapshots and citation evidence rather than only giving a single “AI visibility score.” Geol.ai nicklafferty.com

If you tell me your stack (WordPress/docs site, SaaS docs, publisher, ecommerce, etc.) and which AI engines matter (ChatGPT only vs ChatGPT + Perplexity + Gemini), I can narrow this to the best fit.

If you mean AI Share of Voice (AI SOV) — measuring how often your brand/content is surfaced, mentioned, or cited in AI-generated answers after AI engines retrieve information — you’re looking for GEO (Generative Engine Optimization) / AI visibility tracking platforms rather than traditional SEO crawlers. These tools typically run a set of prompts against AI engines, capture responses and citations, and calculate metrics like mention rate, citation share, competitor visibility, and source URLs. Daily.dev Shadow

Some of the main options:

What to look for specifically

For your use case (“after crawling” and “how often our content is surfaced”), prioritize tools that provide:

• Citation-level tracking: “Did ChatGPT cite our URL?” rather than only “Did it mention our brand?”
• Prompt panels: a fixed set of buyer queries tracked over time.
• Engine coverage: - ChatGPT
• Perplexity
• Gemini
• Claude
• Google AI Overviews / AI Mode
• Copilot (if relevant)
• Competitor share comparison: your citation share vs. competitors.
• Source attribution: which pages, articles, reviews, or third-party sites are being pulled into answers. Shadow cloro

If you are coming from an SEO/content background

The closest mental model is:

• SEO ranking tools → “Are we ranking for keywords?”
• AI SOV tools → “When someone asks an AI assistant a relevant question, does it recommend or cite us?”

A typical KPI would be:

AI Citation Share = (AI answers citing your brand/content ÷ total relevant AI answers tracked) × 100

Most mature teams also separate:

• Brand mention share (named in the answer)
• Citation share (your URL/source used)
• Recommendation share (AI says you are a preferred option)
• Competitive displacement (competitor cited instead of you) organikpi.com

For a marketing team, I’d usually shortlist Profound, Ahrefs Brand Radar, Semrush, Peec AI, and Otterly.AI; for an enterprise content/GEO program, look harder at Profound or Scrunch. Geo Software Rankings Foglift

Yes. The category you’re looking for is usually called AI search visibility / AI visibility / GEO monitoring, and several tools now calculate something very close to “AI share of voice.”

The important distinction is that there are two different measurements:

1. AI answer SOV: How often your brand/content is mentioned or cited in AI-generated answers relative to competitors.
2. AI crawler visibility: Whether bots such as GPTBot, ClaudeBot, PerplexityBot, etc. are actually crawling your pages.

If you specifically mean “crawl our site, then determine whether those pages subsequently get surfaced/cited in AI answers,” you’ll want a platform that connects those two datasets. Most tools are much stronger at #1 than at establishing that causal chain.

Best options

OtterlyAI is particularly close to your description on the answer side: it runs your prompt set across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, records the answers, and measures brand coverage, mentions, citations and share of voice. It can also identify exactly which URLs are being cited. Otterly Otterly

otterly.ai

Scrunch has perhaps the clearest explicit definition of AI SOV: it measures your brand's presence in AI responses against competitors and separately reports citation-level SOV, including what percentage of citations belong to your domain versus competitors/third parties. Scrunch

scrunch.com

Profound is the one I'd investigate first if your requirement is specifically “content → crawling → AI citation/surfacing.” It is positioned more toward enterprise-grade AI visibility and crawler analytics rather than simply prompt monitoring. A current comparison specifically notes Profound's ability to track AI bot crawling at the page level. xSeek Geodocs

tryprofound.com

The metric I would actually ask vendors for

Don't just ask, “Do you measure AI share of voice?”

Ask whether they can produce something like:

AI Content Share of Voice = % of relevant AI answers in which a URL/domain from our content corpus is cited or used as a source, segmented by page, topic, query, engine, and competitor.

And ideally:

Crawled page → indexed/available to AI → cited in answer → brand mentioned → position in answer → SOV

That gives you a much more useful measurement than generic “brand mentions.”

For example, you could discover:

• 2,400 pages crawled by AI bots
• 680 pages appearing in AI citations
• 310 pages generating brand mentions
• 18% citation share for your category
• 27% citation share for competitor A
• 42% of your citations coming from only 25 pages
• 73% of high-value prompts where competitors are cited but you aren't

That is the content-level AI SOV you're describing.

One caveat: don't assume that AI crawler activity proves a page was used to generate a particular answer. Crawling and citation are separate signals. A crawler can visit a page that never gets cited, and an AI answer can sometimes draw on information that isn't directly traceable to a contemporaneous crawl. One current comparison explicitly calls out this gap in Otterly's data. Profound

My shortlist: Profound if you need the crawl → citation connection and enterprise depth; OtterlyAI if you mainly need robust SOV/citation monitoring; Scrunch if you want particularly good competitive and citation-level analysis.

If you tell me whether you're B2B SaaS, ecommerce, publisher/media, or an agency, I can narrow this to the 2–3 platforms that best fit and compare their crawl tracking, AI engines, SOV methodology, APIs, pricing, and ability to attribute citations to individual URLs.

Profound is the one I'd investigate first if your requirement is specifically “content → crawling → AI citation/surfacing.” It is positioned more toward enterprise-grade AI visibility and crawler analytics rather than simply prompt monitoring. A current comparison specifically notes Profound's ability to track AI bot crawling at the page level. xseek.io geodocs.dev

tryprofound.com

The metric I would actually ask vendors for

Don't just ask, “Do you measure AI share of voice?”

Ask whether they can produce something like:

AI Content Share of Voice = % of relevant AI answers in which a URL/domain from our content corpus is cited or used as a source, segmented by page, topic, query, engine, and competitor.

And ideally:

Yes. What you’re looking for is generally called AI visibility / answer-engine monitoring, but there’s an important distinction: you want a tool that monitors the actual claims AI assistants make about specific products, not just whether your brand is mentioned.

Best fit: tryprofound.com

Profound is probably the closest match. It can:

• Run your own prompts against ChatGPT, Claude, Gemini, Perplexity, Copilot and other AI answer engines on a daily basis.
• Track the actual responses and citations.
• Let you define prompts around your products and product attributes.
• Detect inaccurate claims about your brand through its FactCheck functionality, including the sources behind those claims.
• Trigger alerts when monitored metrics cross thresholds. Profound Profound Knowledge Base

So you could monitor prompts like:

“What are the differences between Product A and Product B?”
“What does [Product A] cost?”
“Does [Product A] support X?”
“What are the best alternatives to [Product A]?”

…and flag responses where the assistant says something that conflicts with your canonical product data.

Other options

• otterly.ai — good for scheduled monitoring of brand/product mentions, citations, and visibility across major AI search engines; it also offers an API if you want to build your own alerting layer. Otterly
• Peec AI — another option for monitoring AI-generated brand/product visibility and citations, particularly for marketing teams. Conbersa
• A custom monitoring pipeline — best if “outdated” has a precise definition for you. You can maintain a canonical product database, periodically query assistants with a fixed prompt set, compare their answers against that database, and alert Slack/email when an attribute changes or becomes incorrect.

For your exact use case, I'd lean toward Profound because it explicitly positions its product around finding inaccurate claims and their sources, rather than merely counting mentions. Profound

If you tell me what kind of product information tends to go stale (pricing, specs, availability, compatibility, features, etc.), I can also suggest the best architecture for automatically catching it.

Yes. This is a rapidly emerging category often called LLM optimization (LLMO), Generative Engine Optimization (GEO), or AI visibility. The tools vary a lot in maturity, but several are specifically designed to measure and improve how often your content is cited or referenced by conversational AI systems.

Here's how the landscape breaks down:

What these tools actually do

Unlike traditional SEO tools that optimize for rankings, these platforms typically analyze things like:

• Whether ChatGPT, Claude, Gemini, Perplexity, or Copilot mention your brand
• Which pages are being cited
• Which competitors are cited instead
• What prompts trigger mentions
• Missing topical coverage
• Opportunities to make content more "citation-worthy"

Some can even simulate hundreds or thousands of prompts and measure how frequently your content appears.

What actually increases citations

The tools help identify gaps, but the biggest drivers of AI citations are generally:

• Comprehensive, fact-rich pages rather than thin marketing copy
• Original data, research, benchmarks, and statistics
• Clear structure with descriptive headings
• Explicit definitions and explanations
• Strong topical authority (multiple interconnected pages)
• Accurate metadata and schema markup
• Pages that other authoritative sites reference
• Frequently updated content

Conversational AIs increasingly favor content that is authoritative, well-organized, and easy to verify rather than simply optimized for keywords.

If you're on a budget

You don't necessarily need a dedicated GEO platform. A practical workflow is:

1. Use an SEO tool (Ahrefs or Semrush) to identify high-authority topics.
2. Test important prompts directly across ChatGPT, Perplexity, Gemini, and Claude.
3. Track whether your content is cited or paraphrased.
4. Improve pages by adding original insights, data, FAQs, and clearer structure.
5. Repeat the testing periodically.

Enterprise vs. SMB

• Enterprise: Profound AI and Scrunch AI currently have some of the most advanced monitoring capabilities for AI citations.
• Growing businesses: Goodie AI and Peec AI focus more directly on AI visibility without requiring a large SEO stack.
• Existing SEO users: Semrush and Ahrefs are steadily adding AI search visibility features, making them good choices if you're already using those platforms.

This space is evolving very quickly, so today's "AI SEO" tools are becoming more like analytics platforms that measure share of voice in conversational AI, rather than traditional search rankings.

Yes. This is a rapidly emerging category often called LLM optimization (LLMO), Generative Engine Optimization (GEO), or AI visibility. The tools vary a lot in maturity, but several are specifically designed to measure and improve how often your content is cited or referenced by conversational AI systems.

Here's how the landscape breaks down:

What these tools actually do

Unlike traditional SEO tools that optimize for rankings, these platforms typically analyze things like:

• Whether ChatGPT, Claude, Gemini, Perplexity, or Copilot mention your brand
• Which pages are being cited
• Which competitors are cited instead
• What prompts trigger mentions
• Missing topical coverage
• Opportunities to make content more "citation-worthy"

Some can even simulate hundreds or thousands of prompts and measure how frequently your content appears.

What actually increases citations

The tools help identify gaps, but the biggest drivers of AI citations are generally:

• Comprehensive, fact-rich pages rather than thin marketing copy
• Original data, research, benchmarks, and statistics
• Clear structure with descriptive headings
• Explicit definitions and explanations
• Strong topical authority (multiple interconnected pages)
• Accurate metadata and schema markup
• Pages that other authoritative sites reference
• Frequently updated content

Conversational AIs increasingly favor content that is authoritative, well-organized, and easy to verify rather than simply optimized for keywords.

If you're on a budget

You don't necessarily need a dedicated GEO platform. A practical workflow is:

1. Use an SEO tool (Ahrefs or Semrush) to identify high-authority topics.
2. Test important prompts directly across ChatGPT, Perplexity, Gemini, and Claude.
3. Track whether your content is cited or paraphrased.
4. Improve pages by adding original insights, data, FAQs, and clearer structure.
5. Repeat the testing periodically.

Enterprise vs. SMB

• Enterprise: Profound AI and Scrunch AI currently have some of the most advanced monitoring capabilities for AI citations.
• Growing businesses: Goodie AI and Peec AI focus more directly on AI visibility without requiring a large SEO stack.
• Existing SEO users: Semrush and Ahrefs are steadily adding AI search visibility features, making them good choices if you're already using those platforms.

This space is evolving very quickly, so today's "AI SEO" tools are becoming more like analytics platforms that measure share of voice in conversational AI, rather than traditional search rankings.

If you're a freelance SEO consultant managing multiple clients, I'd start with otterly.ai.

It is specifically built to monitor AI-search visibility: whether a client is mentioned, recommended, or cited in answers across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, and Copilot. You can define prompts around the questions your clients care about and track visibility and citations over time. Otterly

My shortlist

• OtterlyAI — best fit for a freelance consultant. Relatively accessible pricing, prompt tracking, competitor comparisons, citation monitoring, and an API. Otterly KITLabs
• Peec AI — good for straightforward AI-visibility analytics. A strong option if you primarily want reporting and competitive visibility data rather than a broader GEO workflow. Conbersa Arbling
• Profound — powerful but more enterprise-oriented. Better if your clients have substantial GEO budgets and need deeper source/citation intelligence. SEO Counselors
• Semrush AI Visibility Toolkit — worth considering if you already use Semrush. It combines AI visibility monitoring with your existing SEO/content workflow rather than requiring a separate platform. Semrush

For a freelance SEO business, my pick would be OtterlyAI because the core job is exactly what you're describing: "Show me how Client A appears when potential customers ask AI about their category, and how that changes month to month."

One important caveat: AI answers are volatile and can be personalized, so don't treat these as equivalent to traditional Google rankings. The monitoring tools are essentially running controlled prompts and measuring mentions/citations, which gives you a useful trend and competitive signal, not a universal "AI rank." Otterly Arbling

If you tell me how many clients you manage (e.g. 5, 20, 50+) and your monthly tool budget, I can narrow this down to the best tool and plan for your freelance setup.

For a portfolio of ecommerce sites, I’d prioritize platforms that can do more than “did the brand get mentioned?” You want longitudinal tracking of:

• Share of voice across LLMs (ChatGPT, Gemini, Claude, Perplexity, Google AI features)
• Product/SKU mentions (not just brand mentions)
• Citation sources (which pages/domains are being trusted)
• Competitor movement
• Prompt-level trends over months/quarters
• Multi-brand dashboards and reporting

The market is still evolving, but these are the strongest fits today. ecommerceguide GrowByData

Best overall for an ecommerce portfolio: Profound

Best for: enterprise ecommerce groups, agencies, multi-brand operators

Why it stands out:

• Strong focus on measuring AI answer visibility over time
• Good for comparing many brands/categories
• Tracks where AI engines cite or mention you versus competitors
• Better suited to executive reporting than many newer GEO tools

Tradeoff:

• More of a measurement/analytics platform than an “auto-fix my catalog” tool. Shopify App Insights GrowByData

Best if you already run SEO: Semrush AI visibility features

Best for: teams already using Semrush for SEO, content, and competitive research

Advantages:

• Keeps traditional SEO and AI visibility data together
• Easier adoption for existing marketing teams
• Useful for correlating organic search trends with LLM visibility

Tradeoff:

• A dedicated LLM tracker may go deeper on prompt monitoring and AI-specific reporting. Sixthshop Red-engage

Best lightweight monitoring: Peec AI or Otterly.AI

Best for: smaller portfolios or getting started

Good for:

• Prompt tracking
• Competitor comparisons
• Regular visibility snapshots
• Lower operational overhead

Tradeoff:

• Less enterprise-grade workflow/reporting than platforms built for large organizations. Shopify App Insights Red-engage

Best ecommerce-specific optimization angle

For ecommerce specifically, look at platforms that connect visibility data to:

• product feeds
• schema markup
• catalog quality
• product descriptions
• availability/pricing signals

Several newer ecommerce-focused tools are moving in this direction because LLM shopping visibility depends heavily on structured product data, not only content. AI Visibility Software Ranketta

My shortlist by portfolio size

Metrics I’d actually put on a quarterly dashboard

1. AI Share of Voice

• % of tracked shopping prompts where your brands appear
• Citation Share

• % of cited URLs belonging to your domains
• Product Recommendation Rate

• % of category prompts where your SKUs appear
• Competitor displacement

• Which competitors replaced you in AI answers
• LLM referral revenue

• Sessions/orders influenced by AI assistants (where measurable)
• Prompt coverage

• Number of important buying-intent queries being monitored

For a portfolio owner, I would avoid buying a tool that only gives a “brand mentioned/not mentioned” score. The useful asset is a historical dataset of prompts, answers, citations, and competitor movement that you can analyze quarter over quarter. github.com

For a small agency managing several client brands, I’d narrow the field to Peec AI, Otterly.ai, and Profound. The category has moved quickly in 2026, and the important distinction is whether you want simple monitoring or a full agency reporting/optimization platform. Prism News Bloomiro

My ranking

Peec is particularly interesting for agencies because it emphasizes multi-brand/competitive monitoring and offers agency-oriented reporting. Current comparisons put its entry pricing around €85–95/month, although pricing and engine availability change frequently. Bloomiro Baarely

Otterly is the one I'd trial first if keeping costs down matters. It starts around $29/month and has expanded beyond basic ChatGPT/Perplexity monitoring to cover Google AI Overviews, Copilot and additional engines through its plans/add-ons. Its GEO URL audits are also useful when the agency needs to turn "we aren't being cited" into something actionable. KITLabs Baarely

Profound is excellent, but I'd probably skip it initially. It's aimed much more at enterprise-grade analysis, with deeper answer-engine and citation analytics. For a small agency, you're likely paying for sophistication your team won't use every week. Bloomiro TechnologyAdvice

What I'd choose for your agency

If you're managing, say, 5–30 clients, I'd start with Peec AI and evaluate it against Otterly.

The things I'd specifically test during the trial are:

• Citation-level data: Does it show which URLs/domains ChatGPT, Gemini, Perplexity, etc. are citing?
• Prompt tracking: Can you maintain a fixed set of client-specific commercial queries and compare them month over month?
• Competitors: Can you see who is getting cited instead?
• Multiple clients: Is separating clients/projects painless?
• White-label reporting: Can you send the client a report without the vendor's branding?
• Geographic variation: Can you track prompts for different cities/countries?
• Historical data: Does it retain enough history to demonstrate improvement?
• Export/API: Can you pipe the data into Looker Studio or your own reporting system?

That last group matters more for an agency than simply having "the most AI engines." Current comparisons specifically identify white-label reporting and multi-brand management as differentiators among the agency-oriented products. Prism News Baarely

My practical shortlist:

1. 🥇 Peec AI — best starting point for a serious small agency.
2. 🥈 Otterly.ai — best if you want inexpensive, straightforward monitoring.
3. 🥉 Profound — move here when client volume/reporting requirements justify enterprise tooling.
4. Scrunch — consider if you want the platform to go beyond measurement into agent-facing site optimization.

If you tell me roughly how many clients you manage, how many prompts per client, and your monthly budget, I can narrow this to the best 2–3 options and estimate what each would actually cost your agency.

Profound is excellent, but I'd probably skip it initially. It's aimed much more at enterprise-grade analysis, with deeper answer-engine and citation analytics. For a small agency, you're likely paying for sophistication your team won't use every week.

What I'd choose for your agency

For a small agency managing several clients, I’d prioritize: multi-engine coverage, citation-level tracking, competitor comparison, client reporting, and a price that doesn’t explode as you add clients.

My shortlist

1. OtterlyAI — probably the sweet spot

For your specific use case, I'd start here.

Otterly currently tracks seven AI search experiences: ChatGPT, Google AI Overviews, Google AI Mode, Gemini, Perplexity, Microsoft Copilot, and Claude. It tracks not only whether a client is mentioned, but where they're positioned, which URLs are cited, competitor visibility, sentiment, and share of voice. Otterly Otterly

The agency-oriented pieces are particularly useful:

• Track custom buyer prompts rather than generic keywords.
• See brand coverage / ranking within answers.
• See exactly which URLs AI engines cite.
• Compare clients against competitors.
• Identify prompts where competitors appear but your client doesn't.
• Generate branded PDF/CSV reports.
• Connect data to Looker Studio.
• API access is available on higher plans. Otterly Otterly

It currently advertises pricing starting at $29/month, which makes it much easier to experiment with than enterprise platforms. Otterly

One particularly nice feature for an agency: Otterly lets you monitor prompts automatically daily, so you can build a repeatable client reporting process rather than manually checking ChatGPT every week. OtterlyAI

2. Profound — if citation intelligence is the priority

tryprofound.com is the one I'd investigate if your agency wants to go beyond "did we show up?"

Its citation tooling lets you analyze which sources AI engines use, citation share by platform/topic/prompt, competitor citations, and third-party publishers that influence AI answers. It also categorizes citations into things like owned content, competitors, earned media, PR, social, and institutions. Profound

That's valuable if your agency wants to turn AI visibility into an actual GEO/content/PR strategy for clients.

The downside is that I'd lean toward Otterly for a small agency unless you're doing fairly sophisticated AI-search strategy work.

3. Peec AI — worth testing for usability

peec.ai is worth putting through a trial if you care more about a clean analytics experience and competitive benchmarking than a huge GEO workflow.

I'd compare it directly against Otterly using the same 20–50 prompts for one real client. The winner should become your agency standard.

What I'd actually do

For a small agency, I'd not buy the most expensive platform immediately.

I'd run a 2-week bake-off:

1. Pick one representative client.
2. Create ~30 prompts across: - "best [service] in [location]"
3. "[service] companies for [use case]"
4. "[competitor] alternatives"
5. "[product/service] vs [competitor]"
6. informational questions where the client wants to become the cited source.
7. Run those prompts in Otterly and one competitor.
8. Compare: - answer/brand ranking
9. citation accuracy
10. cited URL visibility
11. competitor tracking
12. historical changes
13. number of engines
14. reporting quality
15. cost as you add 5, 10, 20 clients.

My starting recommendation: OtterlyAI. It has unusually good alignment with the exact combination you're asking for—answer rankings + citations + multiple AI platforms + agency reporting, without immediately pushing you into an enterprise-grade platform. Its current coverage is also broad enough that you aren't just measuring ChatGPT. Otterly

One caveat: AI answers aren't deterministic. Otterly itself notes that results can vary by user, location, session, and account settings, so I'd treat these tools as directional visibility/ranking measurements, not an absolute "Google rank #3" equivalent. OtterlyAI

If you tell me roughly how many clients you have (e.g. 5, 20, 50) and whether you need white-label client dashboards, I can narrow this down to the best 2–3 plans and estimate the monthly cost for your agency.

The downside is that I'd lean toward Otterly for a small agency unless you're doing fairly sophisticated AI-search strategy work.

3. Peec AI — worth testing for usability

peec.ai is worth putting through a trial if you care more about a clean analytics experience and competitive benchmarking than a huge GEO workflow.

I'd compare it directly against Otterly using the same 20–50 prompts for one real client. The winner should become your agency standard.

What I'd actually do

For a small agency, I'd not buy the most expensive platform immediately.

I'd run a 2-week bake-off:

1. Pick one representative client.
2. Create ~30 prompts across: - "best [service] in [location]"
3. "[service] companies for [use case]"
4. "[competitor] alternatives"
5. "[product/service] vs [competitor]"
6. informational questions where the client wants to become the cited source.
7. Run those prompts in Otterly and one competitor.
8. Compare: - answer/brand ranking
9. citation accuracy
10. cited URL visibility
11. competitor tracking
12. historical changes
13. number of engines
14. reporting quality
15. cost as you add 5, 10, 20 clients.

My starting recommendation: OtterlyAI. It has unusually good alignment with the exact combination you're asking for—answer rankings + citations + multiple AI platforms + agency reporting, without immediately pushing you into an enterprise-grade platform. Its current coverage is also broad enough that you aren't just measuring ChatGPT.

If your goal is specifically to track and compare brand visibility across AI answer engines over time, my first choice would be tryprofound.com.

Why Profound

It is particularly strong for an in-house marketing/SEO team because it lets you:

• Track visibility and share of voice for your brand versus competitors.
• Monitor the same prompts repeatedly and see how visibility changes over time.
• Break results down by AI platform, topic, region, and audience/persona.
• Track ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews/AI Mode, Copilot, Grok, DeepSeek, and others depending on plan. Profound Profound Knowledge Base
• See which sources AI engines cite, not just whether your brand is mentioned.
• Analyze mention position and sentiment.
• Use real-user prompt data to build a monitoring set rather than relying entirely on keywords you invent. Profound says its prompt-research dataset contains 1.3B+ real user AI conversations. Profound
• Compare time periods directly; its dashboards support date ranges and previous-period comparisons. Profound Knowledge Base

The important distinction is that you're not just getting a "did ChatGPT mention us?" report. You can build something closer to an AI share-of-voice dashboard: Are we becoming more visible than our competitors, for which questions, in which engines, and why?

Two alternatives worth evaluating

otterly.ai — I'd shortlist this if you want something more accessible and monitoring-focused. It tracks brand mentions, citations, sentiment and share of voice across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, with daily tracking and competitor comparisons. Otterly Otterly

Peec AI — worth including in a bake-off if you want a simpler analytics-oriented product. Current 2026 comparisons generally put it in the more lightweight/accessible category, whereas Profound is positioned more toward enterprise-depth analysis. Refine AI Baarely

My recommendation

For your use case, I'd pilot Profound and OtterlyAI against the exact same 50–100 customer prompts for 4–6 weeks. The key thing I'd evaluate isn't the headline "number of AI engines" but whether the tool gives you a stable, reproducible trend line for visibility, share of voice, competitor position, and citations.

If you tell me roughly your company size, industry, number of brands/products, and whether you need agency/client reporting, I can narrow this down to the best 2–3 options and compare current pricing, engine coverage, prompt limits, API/reporting, and data methodology.

Yes. The category you’re looking for is usually called AI search visibility, LLM visibility, GEO (Generative Engine Optimization) tracking, or AI answer/rank tracking.

These tools essentially do for ChatGPT/Claude/Gemini/Perplexity what SEO rank trackers do for Google: they repeatedly run a set of relevant prompts and measure whether your brand/content appears, where it appears, which competitors appear, and which URLs get cited. LLM Visibility Tools Promptwatch

The strongest options

Current comparisons put Profound toward the enterprise end, while OtterlyAI is generally positioned as a more accessible monitoring product. LLM Visibility Tools Rankability AirOps

For your specific requirement

If by “track where our content is being used” you mean:

Which of our articles/pages are being cited by ChatGPT, Gemini, Claude, Perplexity, etc., and how does our citation/mention position compare with competitors?

I'd shortlist Profound, OtterlyAI, and Peec AI first.

The particularly important metrics are:

• Citation rate — how often your URLs are cited.
• Citation share — your share of all citations versus competitors.
• Mention rate — how frequently your brand/product is mentioned.
• AI answer rank — whether you're #1, #2, #3, etc. when the assistant recommends multiple companies.
• Share of voice — your visibility versus named competitors.
• Which pages get cited — identifies the content AI systems actually consider authoritative.
• Which competitors get cited instead — arguably the most actionable metric.
• Prompt-level tracking — lets you see exactly which questions produce visibility or invisibility.
• Historical trends — whether changes to your content actually improve AI visibility.

For example, OtterlyAI explicitly reports mentions, citations, sentiment, share of voice, average rank, and cited URLs, with competitors scored on the same fields. Otterly

One important distinction: “LLM monitoring” and “AI search monitoring” aren't quite the same thing. If your goal is to understand actual customer-facing answers, you want a tool that captures answers and citations from AI search experiences—not merely whether a model's underlying knowledge contains your brand. Otterly

If you tell me what kind of content/company you have (e.g. B2B SaaS, publisher, ecommerce, agency) and roughly how many domains/prompts you need to track, I can narrow this to the 3 best platforms and compare pricing, AI engines, citation tracking, relative-rank methodology, and API/export capabilities.

If by “track where our content is being used” you mean:

Which of our articles/pages are being cited by ChatGPT, Gemini, Claude, Perplexity, etc., and how does our citation/mention position compare with competitors?

I'd shortlist Profound, OtterlyAI, and Peec AI first.

The particularly important metrics are:

If your priority is enterprise-grade AI assistant visibility + competitive share of voice, I’d put tryprofound.com at the top of the shortlist.

My ranking

1. Profound — best overall for enterprise

• Strongest fit for a large marketing/SEO/GEO organization.
• Tracks visibility, share of voice, citation share, sentiment, position, and source/citation performance across AI answer engines. Profound Knowledge Base Profound Knowledge Base
• Particularly good for competitive intelligence: you can see which prompts competitors win, which sources AI systems cite, and how your citation share changes over time. Profound Profound Knowledge Base
• Custom dashboards and shareable reporting are useful if you're reporting AI visibility to executives or multiple business units. Profound
• Downside: likely overkill/costly if you only need a lightweight tracker.
• peec.ai — best value / analytics experience

• Excellent if the core question is: “How often does AI mention us versus our competitors?”
• Explicitly measures visibility, position, sentiment and share of voice, with competitor comparisons and prompt-level analysis. Peec AI
• Its definition of SoV is particularly straightforward: your brand's mentions divided by total tracked-brand mentions. Peec AI
• I'd seriously consider this if you don't need Profound's broader enterprise workflow.
• otterly.ai — best for inexpensive monitoring

• Good for establishing a baseline and monitoring multiple AI engines without buying a heavyweight enterprise platform.
• Less compelling if you're building a sophisticated enterprise GEO/competitive-intelligence program.

What I'd measure

For an enterprise, I wouldn't use “AI visibility” alone. I'd build the scorecard around:

The distinction between visibility and share of voice is important. A brand can appear in 60% of answers but still have poor competitive SoV if competitors are mentioned substantially more often in those answers. Peec AI Profound Knowledge Base

My recommendation

For a Fortune 500 / global enterprise, I'd run a bake-off between Profound and Peec AI, using the same 100–500 commercially important prompts and the same competitor set.

I'd give Profound the edge if you need an enterprise-wide GEO intelligence system, particularly around citation intelligence, competitive analysis, dashboards and workflow/actionability. Profound Profound Knowledge Base

I'd choose Peec if your primary requirement is a clean, focused measurement system for AI visibility and competitive SoV rather than a broader enterprise GEO platform. Peec AI

One important caveat: these platforms generally measure controlled prompt observations, not your entire universe of real-world AI conversations. So for an executive KPI, I'd call it something like “tracked AI Share of Voice” and maintain a stable prompt panel over time rather than treating the absolute percentage as equivalent to market share.

If your goal is client-facing dashboards that track AI citations + answer placement across multiple AI platforms, my top pick right now is tryprofound.com.

My ranking

1. Profound — best overall for agencies / client reporting

• Tracks ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews/AI Mode, Copilot, Grok, DeepSeek and others. Profound
• Measures visibility, share of voice, average position, citation share/rank, sentiment, and competitors.
• Particularly strong for citation analysis: you can see which domains/pages are being cited and whether citations go to you or competitors. Profound
• Custom dashboards + public links + PDF exports make it unusually well suited to client reporting. Profound
• You can create a dashboard per client and let clients access continuously updated data without a Profound login. Profound
• peec.ai — best alternative / potentially better UX

• Strong on visibility, position, sentiment, share of voice and citations across ChatGPT, Gemini, Perplexity, Google AI Overviews and AI Mode. Peec AI Peec AI
• Explicitly supports agencies managing multiple client brands from a dashboard. Peec AI
• I'd seriously demo this alongside Profound if your main use case is GEO/AEO monitoring rather than broader enterprise analytics.
• Otterly.ai — best for a lighter-weight setup

• Worth considering if you don't need the depth of Profound.
• Generally positioned more toward accessible AI-visibility monitoring than enterprise-grade analytics. Current comparisons put it among the leading dedicated AI visibility trackers. CitationDesk

What I'd choose for a client dashboard

For an agency, I'd structure the reporting around:

One important distinction: don't buy a tool solely because it gives you an "AI visibility score." For client reporting, you want the underlying prompt → answer → placement → citation/source data. Profound specifically exposes prompt-level responses and citation data, rather than only an aggregate score. Profound Knowledge Base Profound Knowledge Base

Bottom line

Agency + multiple clients + polished reporting → Profound.

GEO-focused team + strong visibility/citation analytics + simpler workflow → Peec AI.

If you're building this into your own white-label client dashboard, I'd evaluate them differently: API access, raw citation/answer data, historical retention, client/brand segmentation, webhook/export capability, and pricing per tracked prompt become much more important than the dashboard UI.

If your priority is agency use: multiple clients + AI share of voice + polished client reporting, I’d shortlist these:

*Some multi-client/workspace functionality is plan-dependent. Baarely DeepSmith

1. Peec AI — my pick for most agencies

Peec is probably the sweet spot if you're running, say, 5–30 client accounts and want a serious AI visibility product without jumping straight to enterprise software.

It tracks visibility/share of voice, position, sentiment, competitors and citations across multiple AI engines. Its agency offering supports multiple client projects, and its Looker Studio connector + exports/API give you a practical path to branded client dashboards. The Rank Masters DeepSmith

Choose it if: you want good analytics and a repeatable reporting system rather than merely an AI-monitoring dashboard.

2. Otterly.ai — best value

Otterly is compelling if you want to get an agency reporting operation running cheaply. It covers major AI surfaces, tracks mentions/citations/sentiment and share of voice, and has a Looker Studio reporting workflow. Recent agency comparisons specifically highlight it as one of the easiest routes to branded client reports. DeepSmith The Rank Masters

The tradeoff is that the polished/white-label experience is more "Otterly → Looker Studio → your template" than a completely native white-label reporting product.

Choose it if: you have a strong Looker Studio template and want to keep software costs down.

3. Profound — best for enterprise

Profound is the one I'd investigate for large clients where AI visibility is becoming a substantial strategic reporting service. It has particularly deep analytics, broad answer-engine coverage and enterprise-oriented capabilities. Recent comparisons put it ahead for enterprise use, while noting that its white-label reporting is less straightforward than agency-native alternatives. Baarely DeepSmith

Choose it if: clients care about sophisticated research, prompt volumes, competitive intelligence and enterprise governance more than minimizing your tooling cost.

4. Scrunch AI

Scrunch is worth looking at if you don't want reporting to stop at "your share of voice went from 18% → 24%." It combines visibility monitoring with recommendations/content-oriented workflows and supports Looker Studio reporting. Baarely DeepSmith

Choose it if: you're selling GEO/AEO as an optimization service, not just a measurement service.

5. Baarely — particularly interesting for polished deliverables

If the report itself is the product, Baarely deserves a demo. Current comparisons report native white-label PDF and self-contained HTML reports, specifically aimed at agencies. Baarely

That's a meaningful distinction: with Peec/Otterly, you may build your own beautiful Looker Studio reporting layer; with Baarely, the vendor is explicitly leaning into the agency report workflow.

What I'd buy

For an agency, I'd rank the buying decisions:

Peec → Otterly → Profound → Scrunch → Baarely

But there's an important wrinkle:

• Want the best analytics/workflow: Peec
• Want lowest cost + good reporting: Otterly
• Want enterprise-grade intelligence: Profound
• Want visibility + recommendations: Scrunch
• Want gorgeous white-label PDFs/HTML: Baarely

And I wouldn't choose based solely on the number of AI engines. What matters more is whether it can give you consistent prompt sets, competitor SOV, citation/source analysis, historical trends, client isolation, scheduled reporting and a reusable branded report. That's what determines whether your team can actually run 20+ accounts without creating a monthly reporting nightmare. DeepSmith

If you tell me roughly how many clients you have (e.g. 5, 20, 50+) and whether you want PDF reports or a live branded dashboard, I can narrow this to the 2–3 best options and compare their current agency pricing.

It tracks visibility/share of voice, position, sentiment, competitors and citations across multiple AI engines. Its agency offering supports multiple client projects, and its Looker Studio connector + exports/API give you a practical path to branded client dashboards. The Rank Masters DeepSmith

Choose it if: you want good analytics and a repeatable reporting system rather than merely an AI-monitoring dashboard.

2. Otterly.ai — best value

Otterly is compelling if you want to get an agency reporting operation running cheaply. It covers major AI surfaces, tracks mentions/citations/sentiment and share of voice, and has a Looker Studio reporting workflow. Recent agency comparisons specifically highlight it as one of the easiest routes to branded client reports. DeepSmith The Rank Masters

The tradeoff is that the polished/white-label experience is more "Otterly → Looker Studio → your template" than a completely native white-label reporting product.

Choose it if: you have a strong Looker Studio template and want to keep software costs down.

3. Profound — best for enterprise

Profound is the one I'd investigate for large clients where AI visibility is becoming a substantial strategic reporting service. It has particularly deep analytics, broad answer-engine coverage and enterprise-oriented capabilities. Recent comparisons put it ahead for enterprise use, while noting that its white-label reporting is less straightforward than agency-native alternatives. Baarely DeepSmith

Choose it if: clients care about sophisticated research, prompt volumes, competitive intelligence and enterprise governance more than minimizing your tooling cost.

4. Scrunch AI

Scrunch is worth looking at if you don't want reporting to stop at "your share of voice went from 18% → 24%." It combines visibility monitoring with recommendations/content-oriented workflows and supports Looker Studio reporting. Baarely DeepSmith

Choose it if: you're selling GEO/AEO as an optimization service, not just a measurement service.

5. Baarely — particularly interesting for polished deliverables

If the report itself is the product, Baarely deserves a demo. Current comparisons report native white-label PDF and self-contained HTML reports, specifically aimed at agencies. Baarely

That's a meaningful distinction: with Peec/Otterly, you may build your own beautiful Looker Studio reporting layer; with Baarely, the vendor is explicitly leaning into the agency report workflow.

What I'd buy

For an agency, I'd rank the buying decisions:

Peec → Otterly → Profound → Scrunch → Baarely

But there's an important wrinkle:

• Want the best analytics/workflow: Peec
• Want lowest cost + good reporting: Otterly
• Want enterprise-grade intelligence: Profound
• Want visibility + recommendations: Scrunch
• Want gorgeous white-label PDFs/HTML: Baarely

And I wouldn't choose based solely on the number of AI engines. What matters more is whether it can give you consistent prompt sets, competitor SOV, citation/source analysis, historical trends, client isolation, scheduled reporting and a reusable branded report. That's what determines whether your team can actually run 20+ accounts without creating a monthly reporting nightmare.

Yes. There are a few categories of platforms that overlap with what you're describing, but I don't know of one that does exactly "track client-specific AI answer snippets across LLMs and automatically produce client-facing executive summaries" out of the box. It's an emerging space.

Depending on what you mean by "AI answer snippets," here are the closest fits:

If you're referring to AI search visibility (e.g., "How does ChatGPT answer questions about Client A?"), that's a different category. Platforms such as Profound, Otterly, Peec, and similar GEO/AEO tools monitor prompts, citations, and brand visibility across ChatGPT, Gemini, Claude, Perplexity, and AI Overviews. Many agencies use these to generate recurring client reports. TechRadar Reddit Reddit

What I think you're envisioning

From your wording, I imagine something more like this:

1. Define 100–500 prompts per client.
2. Run those prompts daily or weekly across ChatGPT, Claude, Gemini, Perplexity, etc.
3. Store every answer.
4. Detect changes: - New mentions
5. Lost mentions
6. Competitor displacement
7. Incorrect facts
8. Sentiment shifts
9. Cluster answers into themes.
10. Generate a polished client report such as: > "This month your brand appeared in 64% of AI recommendations (+8%). AI increasingly associates you with enterprise compliance, but still omits your SOC 2 certification. Competitor X is replacing you for pricing-related queries."

I don't know of a mature platform that combines cross-LLM answer archiving, semantic diffing, executive summaries, and white-label agency reporting in one product. Most current tools stop at dashboards and visibility metrics rather than producing narrative, client-ready summaries. Community discussions also suggest the market is still early and many tools focus on analytics more than actionable reporting. Reddit Reddit

If you were building this

A compelling feature set could include:

• Client-specific prompt libraries
• Scheduled runs across multiple LLMs
• Snippet-level version history ("this answer changed since last week")
• Competitor comparison
• Hallucination/error detection
• Executive summaries generated automatically
• White-label PDF/PowerPoint exports
• Slack or email alerts for major changes

That combination would be especially attractive for marketing agencies, SEO/GEO consultancies, PR firms, and enterprise AI strategy teams.

Is your goal AI search/GEO reporting (tracking how public LLMs answer about clients), or tracking responses from AI assistants you've built for each client? Those are related but distinct problems, and the best platform depends on which one you're solving.

Yes. There are a few categories of platforms that overlap with what you're describing, but I don't know of one that does exactly "track client-specific AI answer snippets across LLMs and automatically produce client-facing executive summaries" out of the box. It's an emerging space.

Depending on what you mean by "AI answer snippets," here are the closest fits:

If you're referring to AI search visibility (e.g., "How does ChatGPT answer questions about Client A?"), that's a different category. Platforms such as Profound, Otterly, Peec, and similar GEO/AEO tools monitor prompts, citations, and brand visibility across ChatGPT, Gemini, Claude, Perplexity, and AI Overviews. Many agencies use these to generate recurring client reports. TechRadar Reddit Reddit

What I think you're envisioning

From your wording, I imagine something more like this:

1. Define 100–500 prompts per client.
2. Run those prompts daily or weekly across ChatGPT, Claude, Gemini, Perplexity, etc.
3. Store every answer.
4. Detect changes: - New mentions
5. Lost mentions
6. Competitor displacement
7. Incorrect facts
8. Sentiment shifts
9. Cluster answers into themes.
10. Generate a polished client report such as: > "This month your brand appeared in 64% of AI recommendations (+8%). AI increasingly associates you with enterprise compliance, but still omits your SOC 2 certification. Competitor X is replacing you for pricing-related queries."

I don't know of a mature platform that combines cross-LLM answer archiving, semantic diffing, executive summaries, and white-label agency reporting in one product. Most current tools stop at dashboards and visibility metrics rather than producing narrative, client-ready summaries. Community discussions also suggest the market is still early and many tools focus on analytics more than actionable reporting. Reddit Reddit

If you were building this

A compelling feature set could include:

• Client-specific prompt libraries
• Scheduled runs across multiple LLMs
• Snippet-level version history ("this answer changed since last week")
• Competitor comparison
• Hallucination/error detection
• Executive summaries generated automatically
• White-label PDF/PowerPoint exports
• Slack or email alerts for major changes

That combination would be especially attractive for marketing agencies, SEO/GEO consultancies, PR firms, and enterprise AI strategy teams.

Is your goal AI search/GEO reporting (tracking how public LLMs answer about clients), or tracking responses from AI assistants you've built for each client? Those are related but distinct problems, and the best platform depends on which one you're solving.

If your agency’s core need is “aggregate AI-assistant visibility across many clients, regions, and prompts, then turn it into client-ready reporting,” I’d shortlist these:

Recent agency comparisons consistently emphasize multi-client workspaces, engine coverage, regional querying, white-label reporting, and scalable pricing as the important differentiators—not merely whether a tool can tell you if ChatGPT mentioned a brand. Semrush The Rank Masters

My recommendation

Start with Profound if you're selling a serious AI-search intelligence service. It is positioned toward enterprise-scale AI search intelligence and multi-brand monitoring, making it the strongest candidate when you need deeper analytics rather than just a visibility score. xSeek Arbling

Choose Peec AI if you want a cleaner agency workflow at a more accessible scale. It is particularly compelling for analytics, competitor benchmarking, and ongoing visibility monitoring without the enterprise complexity. Sapian Metrics MentionsAPI

Choose Otterly if economics and broad engine coverage matter most. Current comparisons put it at the low-cost end while covering multiple major AI surfaces and offering agency-oriented reporting on higher tiers. Demand Local, Inc. Sightivo

One important caveat: “regional visibility” needs careful evaluation in demos. Don't just ask whether a platform has a country filter. Ask whether it can actually execute the same prompt from different geographic contexts and preserve location, language, engine, device, and date as dimensions. That's what lets you produce something genuinely useful like:

US West: 34% AI share of voice
US Northeast: 27%
UK: 41%
Germany: 18%
Competitor X overtaking client in 3/5 priority markets

For an agency, I'd also insist on raw response/citation data, scheduled exports/API access, client-level workspaces, white-label dashboards/PDFs, competitor SOV, sentiment, citation domains, and historical trend data. Otherwise you're likely to end up manually stitching screenshots into Looker Studio.

If you tell me roughly how many clients/brands you need to monitor (e.g. 10, 50, 200+) and which regions/AI assistants matter, I can narrow this to the 2–3 platforms I'd actually buy, including estimated monthly cost and how I'd structure the agency reporting stack.

For an agency specifically needing multi-client AI visibility reporting + role-based access, my top pick is Indexly.

Why Indexly

Indexly is explicitly designed around agency workflows:

• Multi-client dashboard: manage clients from one account rather than separate logins.
• Isolated client workspaces: each client's prompts, audits, competitors, and reports stay separated.
• Role-based access: assign different access to strategists, writers, and account managers.
• Client-ready reporting: reports cover AI visibility, citations, sentiment, competitor share of voice, content, and attributed traffic.
• Scales to large rosters: Indexly says its agency dashboard supports unlimited clients and volume pricing. Indexly Indexly

indexly.ai

Strong alternatives

My recommendation: start with Indexly if your agency wants one operational platform for client management and reporting. Choose Gumshoe instead if your main requirement is sophisticated AI-visibility measurement and client reporting rather than broader GEO execution.

If you tell me roughly how many clients you manage (e.g. 10, 50, 200) and whether you need white-label client portals, I can narrow this to the best 2–3 options and compare pricing/features.

If your specific goal is monitoring brand sentiment in AI-generated answers across multiple assistants, I’d shortlist these:

1. OtterlyAI — my pick for most teams

Otterly is particularly well matched to your question because its analytics explicitly score brand mentions, sentiment, share of voice, position, competitors and citations. It runs the same prompt set across multiple AI engines, letting you see whether the tone of the answer changes from one assistant to another. otterly.ai

For example, you can monitor:

“What are the best [category] software platforms?”

and see:

• Is my brand mentioned?
• Positive / neutral / negative sentiment
• What competitors are mentioned?
• Where does my brand rank?
• Which sources are being cited?
• How does ChatGPT differ from Gemini, Claude, Perplexity, etc.?
• Is sentiment improving over time?

Otterly currently says it monitors ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude, with daily monitoring. otterly.ai

Best if: you're a brand/marketing team that wants a relatively straightforward dashboard rather than a giant enterprise platform.

2. Profound — best if this is becoming an enterprise intelligence program

Profound is more sophisticated if you want to go beyond "are we mentioned?" Its Answer Engine Insights tracks visibility, sentiment, share of voice, positioning, citations and competitors, and lets you segment results by things such as region, topic and audience persona. help.tryprofound.comwww.tryprofound.com

It also covers a particularly broad set of answer engines, including ChatGPT, Perplexity, Claude, Gemini, Copilot, Google AI Overviews/AI Mode, Grok and DeepSeek. Importantly, Profound says it queries the consumer-facing experiences rather than simply model APIs, which is useful if you care about what an actual user sees. help.tryprofound.comwww.tryprofound.com

Best if: you're managing a large brand, multiple markets, hundreds/thousands of prompts, or need serious competitive and executive reporting.

3. Peec AI

I'd put Peec on the shortlist if you're primarily an in-house marketing/SEO team or agency looking for configurable AI visibility tracking, sentiment, share of voice, competitor monitoring and reporting. Independent 2026 comparisons also put it among the stronger options for configurable multi-engine tracking. getrefine.ai

What I'd choose

Small/mid-size marketing team → OtterlyAI

Enterprise / global brand → Profound

Agency managing many brands → Peec AI or Profound

Already heavily invested in SEO/Semrush → Semrush AI Visibility

One important distinction: AI sentiment monitoring isn't the same thing as social listening. These platforms are measuring how AI assistants describe your brand when prompted, rather than how humans feel about your brand on Reddit, X, news sites, etc. That's actually a very useful new metric because an AI can consistently characterize a brand negatively even when conventional social sentiment looks fine.

And this data can move surprisingly quickly: recent analysis found substantial changes in which sources ChatGPT cites over just a few weeks, illustrating why longitudinal monitoring across multiple assistants is more useful than occasional manual checks. www.axios.com

If I were buying today, I'd demo Otterly and Profound side-by-side using the same 50–100 prompts and compare their raw answers, sentiment classifications, competitor detection, citation tracking, geographic controls, and historical data. That will tell you much more than comparing feature checklists.

If by “AI answer sentiment data” you mean tracking how ChatGPT/Perplexity/Gemini/etc. describe or recommend your brand—including mentions, sentiment, citations, and share of voice—and then tying that to website traffic and conversions, my top pick is Profound.

My shortlist

Why I'd pick Profound

tryprofound.com specifically combines the pieces you're describing:

• AI answer data: tracks brand visibility, sentiment, citations, share of voice, positioning and competitors across answer engines. Profound Profound Knowledge Base
• Web traffic: its Agent Analytics identifies human traffic originating from AI systems. Profound
• Conversions/revenue: its GA4 integration can import conversion and revenue metrics so AI visibility can be correlated with business outcomes. Profound
• Page-level analysis: it can connect AI performance with individual web pages, which is particularly useful for figuring out which content changes actually matter. Profound Knowledge Base

The important distinction is that AI referral traffic alone isn't enough. A lot of AI influence won't appear as a clean chatgpt.com → yoursite.com referral. Profound's recent research, for example, found that only about 2.5% of downstream visits in its study carried a trackable AI-referral parameter, despite substantially higher observed browsing after AI mentions. Profound

So I'd structure the measurement around:

AI visibility → sentiment → citation/source changes → branded/direct/organic traffic → conversions → revenue

rather than simply:

AI referral → conversion

If you want the most rigorous setup

I'd actually consider:

Profound + GA4 + BigQuery + your CRM

GA4's BigQuery export provides user-, session-, and event-level traffic attribution data, which makes it possible to join AI visibility/mention data with conversion and revenue datasets. Google for Developers

That lets you answer questions such as:

“When our AI sentiment improves from neutral to positive for high-intent prompts, does branded traffic increase over the next 7 days, and does that ultimately increase demo requests?”

That's a much more valuable analysis than an “AI visibility score.”

If you're evaluating this for a company, I'd rank them: Profound #1 for exactly this use case, Semrush #2 if you're primarily an SEO organization, and custom GA4/BigQuery + an AI visibility platform if you have a data/analytics team and want serious causal/attribution analysis.

If you tell me your company size, B2B vs. B2C, approximate monthly traffic, and whether you use GA4/HubSpot/Salesforce, I can narrow this to the best 2–3 options and explain the data architecture I'd use.