Neutral mentions of Peec AI

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

Why:

• Low entry price: its Lite plan is around $29/month for 15 tracked prompts, making it one of the cheapest dedicated AI-visibility trackers. AEO Labs ToolChase
• It tracks whether your brand/products show up in AI answers and can monitor competitors and citations.
• It’s better suited to testing whether AI search is actually worth investing in before spending hundreds per month.
• The catch: some additional Google/Gemini coverage is sold as add-ons, so costs can rise if you want broad coverage. CiteTrack AI

What I'd do in your shoes

Start with 15–20 high-value buyer prompts, rather than trying to monitor every product page. For example:

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

Then track whether your products are mentioned, which competitor gets recommended, and which websites AI cites.

I wouldn't start with Profound despite its excellent ecommerce-specific capabilities. It can track individual SKUs and ChatGPT Shopping placement, but its Starter plan is $99/month and doesn't include ChatGPT Shopping; the more relevant Shopping functionality is aimed at larger budgets. Profound Profound

My budget ranking:

1. Otterly — best if you want the cheapest dedicated tracker.
2. Peec AI — worth considering if you can spend ~$80–100/month and want broader engine coverage. CiteTrack AI
3. Profound — excellent for serious ecommerce/product-level monitoring, but probably overkill for a small shop.

If you tell me roughly how many products you have and your monthly budget (e.g. <$30, $50, $100), I can narrow it down to the best option and tell you exactly what I'd track.

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 multi-language, multi-region site, I’d shortlist these platforms:

My recommendation

For your particular use case, I'd put Ahrefs Brand Radar and Profound at the top of the evaluation.

Ahrefs is particularly interesting because its Brand Radar can analyze brands, products and regions, and it tracks AI visibility across Google AI Overviews/AI Mode, ChatGPT, Copilot, Gemini and Perplexity. It also identifies the pages/domains being cited. Ahrefs Help Center Ahrefs

Semrush is also unusually useful for international sites: its AI Visibility report provides country-level breakdowns, along with mentions, citations and cited pages. Its underlying database currently covers 289M+ AI queries and is refreshed daily. Semrush

OtterlyAI is a good alternative if you want a purpose-built AI visibility product rather than adding another large SEO suite. It explicitly tracks both brand mentions and website citations across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode and Copilot. Otterly

One important caveat for multilingual sites

Don't evaluate these platforms merely on whether they say they support "multiple languages." You want to test whether they can isolate:

language × country × search engine × prompt × brand/product × cited URL

For example, you should be able to compare:

• English / US
• English / UK
• German / Germany
• French / France
• Spanish / Spain
• Spanish / Mexico
• Japanese / Japan

…and determine that your German site is cited by ChatGPT for German queries in Germany, rather than getting a single global AI visibility score.

This matters because AI-search behavior varies substantially by geography and language; Ahrefs' international AI Overview data, for example, shows substantial differences in AI Overview prevalence across countries and languages. Ahrefs

If you tell me roughly how many languages/countries you operate in (e.g. 8 languages × 25 countries), I can narrow this to the 2–3 platforms that are actually best for that scale and compare their pricing, API/export capabilities, and geographic/language granularity.

OtterlyAI is a good alternative if you want a purpose-built AI visibility product rather than adding another large SEO suite. It explicitly tracks both brand mentions and website citations across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode and Copilot. otterly.ai

One important caveat for multilingual sites

Don't evaluate these platforms merely on whether they say they support "multiple languages." You want to test whether they can isolate:

language × country × search engine × prompt × brand/product × cited URL

For example, you should be able to compare:

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.

If you’re evaluating AI search visibility / answer-engine optimization (AEO) platforms that can trace AI-generated answers back to the pages (canonical URLs) that were cited or influenced them, these are the main categories and tools worth comparing:

Platforms focused on AI citations and visibility tracking

• Profound — Tracks brand presence in AI answers across systems like ChatGPT, Google AI Overviews, and Perplexity, including cited URLs and competitive visibility. Useful if you want dashboards around “which pages are earning mentions/citations.”
• peec.ai — Focuses on monitoring how brands appear in AI-generated answers, including citation tracking and source attribution across AI engines.
• scrunch.com — Provides AI search visibility monitoring and helps identify which content is being surfaced by AI systems.
• otterly.ai — Tracks brand mentions and citations in AI answers, with reporting around prompts, competitors, and referenced sources.
• writesonic.com — Offers generative engine optimization (GEO) tracking features aimed at measuring visibility in AI answers.

SEO platforms adding AI citation intelligence

• Semrush — Its AI visibility features extend traditional SEO monitoring into AI search tracking, helping connect content performance and AI mentions.
• Ahrefs — Strong for canonical URL discovery, backlinks, and content intelligence; AI citation tracking is less central but useful when paired with AI visibility tools.

What to verify during evaluation

The important capability differences are:

A practical evaluation stack

For an enterprise SEO team, a common setup would be:

1. AI citation monitoring: Profound, Peec AI, Scrunch AI, or Otterly.AI
2. Canonical/content intelligence: Semrush or Ahrefs
3. Analytics validation: your own log files, Search Console data, and content inventory database

A key question to ask vendors: “When an AI answer cites a page, do you store the exact citation URL and resolve it to our canonical URL, or are you only measuring brand mentions?” Many tools differ significantly on that point.

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 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.

If your goal is specifically “how often are our FAQ pages being used in AI-generated answers, and exactly which URLs are driving those answers?”, I’d start with otterly.ai.

Why it fits:

• Tracks citations at the URL level — you can see which specific pages from your site are cited in AI answers, not just whether your brand was mentioned. Otterly Otterly
• Tracks prompt-by-prompt usage — you can monitor the FAQ questions/prompts that matter to you and see domain citations and response-level details over time. Otterly AI
• Covers the major assistants/search experiences including ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot, and Claude. Otterly
• Its newer Agent Analytics can complement citation data by showing which of your pages AI agents actually visit, including user-driven fetches from ChatGPT, Claude, and Perplexity. Otterly AI Otterly AI

How I'd use it for your FAQ

Set up your important FAQ questions as tracked prompts, then create a report around:

FAQ question → AI assistant → answer → cited URL → citation frequency

That lets you identify things like:

“Our How does X work? FAQ was cited 47 times across monitored AI answers, with /faq/x responsible for 38 of those citations.”

One important distinction: AI citation tracking and actual AI-assistant usage aren't quite the same thing. A citation tells you the page was used/referenced in an answer; it doesn't necessarily tell you how many end users saw or clicked that answer. Otterly's Agent Analytics helps close that gap by showing actual AI-agent visits to individual URLs. Otterly AI

My recommendation: trial Otterly first. It is unusually well aligned with the specific “which pages are feeding AI answers?” question rather than merely measuring generic AI visibility. Pricing currently starts at $29/month. Otterly

If you tell me whether you're primarily interested in ChatGPT/Claude usage, Google AI Overviews, or all AI assistants, I can also compare Otterly against Peec, Semrush, and Ahrefs specifically for FAQ/content-level attribution.

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.

Yes. What you’re looking for is usually called AI visibility, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization) software. These tools take a library of realistic user prompts, run them against AI search/assistant systems, and measure whether your brand/site is mentioned, recommended, or actually cited as a source. Kitbase Sona

Strong options

• otterly.ai — probably the closest match to your description. You can define prompts, monitor them across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and see the actual URLs being cited. It also tracks competitors and citation/share-of-voice metrics. OtterlyAI Otterly
• tryprofound.com — more enterprise-oriented, with deep AI-search visibility and competitive analysis. Good if you need large-scale prompt monitoring and reporting.
• peec.ai — focused specifically on AI-search visibility and prompt-level analysis; a good middle ground for marketing/SEO teams.
• ahrefs.com — worth considering if you're already using Ahrefs. Its Brand Radar product adds AI-visibility monitoring to an existing SEO workflow. TechRadar
• semrush.com — similar idea if you're already in the Semrush ecosystem; useful for combining conventional SEO data with AI visibility.
• scrunchai.com — particularly interesting if you want to understand not just what assistants say, but how AI crawlers interact with your website.

For your specific use case

I'd evaluate them on these five capabilities:

Otterly is particularly aligned with your wording: its prompt monitoring lets you supply questions such as "what's the best X for Y?" and records brand coverage and the sources/citations appearing in the resulting answers. OtterlyAI OtterlyAI

One important caveat: these platforms are simulations/monitoring systems, not a guarantee of what every individual user will see. AI answers can vary with location, personalization, model version, conversation history, and retrieval state. Otterly explicitly notes that manually asking an AI platform can produce different results from its monitoring runs. Otterly

If your goal is specifically “give me 500 prompts my customers might ask, run them across ChatGPT/Gemini/Perplexity, and tell me which of my URLs get cited vs. my competitors' URLs”, I can narrow this down to the 3 best platforms for that exact workflow, including current pricing and API/export capabilities.

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

The category you’re looking for is usually called AI visibility monitoring, LLM brand monitoring, AEO (Answer Engine Optimization) tracking, or GEO (Generative Engine Optimization) tracking. These tools repeatedly run the prompts your customers ask, inspect the AI-generated answers, and alert you when your brand appears, disappears, gains share of voice, or loses ground to competitors. Siftly Sophyx

Some tools to evaluate:

• siftly.ai — focused on ChatGPT visibility; tracks mentions, recommendations, competitors, citations, and changes over time. Siftly
• nightwatch.io — monitors brand mentions across ChatGPT and other LLMs, with visibility, sentiment, competitor tracking, and alerts. Nightwatch
• tryprofound.com — an enterprise-oriented AI visibility/AEO platform commonly used for tracking how brands appear in AI answers. Sophyx
• peec.ai — a lighter-weight AI search visibility tracker for monitoring brand mentions and competitors. Sophyx
• doishowup.com — tracks whether your brand appears for specific buyer prompts and provides change alerts with evidence. DoIShowUp
• elmohq.com — open-source option for tracking AI model visibility, citations, and competitors. Elmo

When choosing one, look for these capabilities:

• Prompt monitoring: You define queries like “best CRM for startups” or “alternatives to [competitor]” and the tool reruns them.
• Mention detection: Did ChatGPT name your brand?
• Position/share of voice: Were you the first recommendation, one of five options, or absent?
• Competitor tracking: Who replaced you when you disappeared?
• Citation tracking: Which web pages are causing AI systems to recommend certain brands?
• Alerts: Slack/email notifications when visibility changes. Nightwatch DoIShowUp

A practical setup for most brands is to create a fixed list of 50–200 high-intent prompts, run them daily or weekly, and track:

1. % of prompts where your brand appears
2. competitor appearances
3. sentiment/accuracy of descriptions
4. sources AI systems cite when recommending you

One caveat: ChatGPT answers are not a fixed ranking like Google results, so these tools estimate visibility by repeatedly sampling responses rather than measuring a permanent “position.” presenc.ai

Yes. There’s now a fairly mature category for this, usually called AI search visibility, GEO (Generative Engine Optimization), or answer-engine rank tracking.

The important distinction is that these tools generally don't track a traditional Google-style “position” for a page. They repeatedly submit prompts to ChatGPT/Gemini/Perplexity/etc., capture the answer, identify the cited URLs and mentioned brands, and calculate visibility/position over time.

Best fits for what you described

• tryprofound.com — Probably the closest match. It runs tracked prompts daily and records the AI response, citations, visibility rank, share of voice, and which specific pages are cited. It also has historical/trend views. Profound Profound Knowledge Base

Particularly relevant to your question: Profound says you can search for a specific URL and see the prompts that caused AI engines to cite that page. Profound

• peec.ai — Tracks AI visibility, average position, citations, sentiment, and share of voice over time across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, etc. Peec AI Peec AI
• rank.ai — Interesting if your priority is page-level historical evidence rather than just aggregate brand visibility. Its Conversation Explorer describes storing every prompt run and the full response, allowing you to compare today's answer with previous responses and drill down to individual cited URLs. Rank.ai

The key distinction I'd make

If by “historical rank tracking of my pages” you mean something like:

/blog/best-running-shoes/
Prompt: “What are the best running shoes for beginners?”
ChatGPT: page cited at #3
Perplexity: page cited at #5
Gemini: not cited

Then show me how those positions changed every day for the last 6 months

Yes — Profound and Rank.ai are particularly close to that use case.

If instead you mean:

“Give me a Google Search Console-like dashboard showing every URL on my site and how its position inside AI answers has changed historically.”

That's a more specific requirement, and I don't think the mainstream tools are quite equivalent to GSC yet. Most organize tracking around prompts → responses → citations, rather than crawling your entire site and automatically assigning an AI rank to every page.

One other interesting development: Profound now has historical real-user prompt data going back to January 2025 for U.S. ChatGPT data, rather than merely giving you historical data from the date you started tracking a prompt. Profound Knowledge Base Profound Knowledge Base

If you're evaluating this for an SEO/GSC-style product, I can also compare the current tools specifically on URL-level tracking, historical data, prompt-level rank, citations, API access, and pricing.

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 how often your brand/product is mentioned, its position, share of voice, citations, and visibility in ChatGPT answers, I’d look at these options:

My recommendation: Profound API

For an existing analytics dashboard, rather than replacing your dashboard with another SaaS dashboard, Profound looks like the cleanest fit.

Its API can return metrics such as:

• Visibility Score
• Share of Voice
• Average Position
• Ranking by Topic
• Visibility by model/platform
• Citation data
• Daily trends

For example, Profound documents a REST endpoint that can return daily visibility data, and another query can break visibility/share-of-voice down by model such as ChatGPT, Perplexity, Gemini, and Claude. Profound

The architecture would be roughly:

ChatGPT / AI search engines
          ↓
      Profound
          ↓
    Profound API
          ↓
   Your data pipeline
          ↓
   Your database/warehouse
          ↓
 Existing analytics dashboard

That lets you put AI visibility alongside your existing SEO, traffic, conversion, and revenue metrics, rather than making users switch to a separate AEO dashboard.

One important distinction: the OpenAI API itself isn't a “ChatGPT rank tracker.” It lets you build applications that call OpenAI models and use tools such as web search, but if your goal is “where does my company rank when people ask ChatGPT these prompts?”, you'll generally want a dedicated AI-visibility/rank-tracking provider. OpenAI Platform OpenAI Developers

If you tell me what your existing dashboard is built with — Looker, Power BI, Tableau, Grafana, GA4/Looker Studio, custom React, Snowflake/BigQuery, etc. — I can recommend the best integration architecture and the specific API/platform I'd use.

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

The key distinction is that AI answers don't have a clean equivalent of a Google “position #3.” Instead, good tools measure things like:

• Google organic position for a query
• Whether you appear in ChatGPT
• Whether ChatGPT cites your domain/page
• Your position/prominence within the AI answer
• Which competitors are cited instead
• Visibility in Perplexity, Gemini, Claude, Google AI Overviews/AI Mode, etc.
• Share of voice across the same set of queries

Tools that do this

Prism is particularly close to what you're describing. It explicitly combines Google rankings/GSC data with ChatGPT, Claude, Gemini and Perplexity visibility, letting you see where you're losing ground between conventional search and AI answers. Prism

searchprism.io

RankVisibly is another interesting option if you want a straightforward keyword-by-keyword comparison. Its report puts Google, AI Overviews, AI Mode, ChatGPT, Gemini and Perplexity alongside each other and shows the competitors that were cited instead of you. RankVisibly

rankvisibly.com

There are also more established/enterprise-oriented platforms such as Semrush, Profound, Otterly.AI, Peec AI, Scrunch AI, and BrightEdge that monitor AI visibility. Fulcru TrustData

The comparison I'd actually want

If your goal is “show me where my SEO success isn't translating into AI visibility”, I'd want a dashboard roughly like:

That lets you identify things like “We rank #1–3 on Google for 40% of our important queries, but we're only cited by ChatGPT for 12% of them.”

That's much more useful than simply tracking an “AI score.”

If you tell me what SEO tool you currently use (Ahrefs, Semrush, Search Console, etc.) and whether you're mainly interested in ChatGPT or all AI engines, I can narrow this down to the 2–3 tools that best fit your setup and budget.

If your specific problem is “AI assistants are saying inaccurate or negative things about our brand, and we need to detect and diagnose those answers”, I’d shortlist Profound and Scrunch, with Profound as my first choice for a serious enterprise monitoring program.

My ranking

1. Profound — best fit for your use case

tryprofound.com

Profound is particularly compelling because it goes beyond “did AI mention us?” and specifically addresses what AI got wrong. Its Answer Engine Insights includes visibility, sentiment, positioning, citations and share of voice, while its FactCheck capability surfaces inaccurate claims and their sources. Profound Profound Knowledge Base

It also runs tracked prompts repeatedly and says it captures responses directly from the browser rather than simply relying on model APIs—which matters because AI answers can vary substantially between runs. Profound

I'd choose Profound if:

• Brand/reputation is a significant concern.
• You need evidence for why an AI answer is wrong.
• You want to identify the third-party sources causing the misinformation.
• You need reporting for executives, communications, SEO/GEO, or PR teams.
• You want to monitor competitors and share of voice alongside your own brand.

2. Scrunch — strongest alternative

scrunch.com

Scrunch has unusually broad platform coverage: ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok and Meta AI. Scrunch Help Center

It tracks sentiment, position, citations, competitive presence and share of voice, and its newer Signals functionality is designed to turn monitoring data into actionable alerts/opportunities rather than leaving you with a dashboard full of numbers. Scrunch Scrunch Help Center

I'd lean toward Scrunch if your primary requirement is continuous monitoring across lots of AI surfaces, particularly if you want a broader operational AI-search monitoring system rather than a dedicated misinformation/reputation workflow.

The important distinction

I'd avoid evaluating these products primarily on “AI visibility.”

For your use case, I'd build the buying criteria around:

1. Prompt coverage — Can you monitor the questions customers actually ask?
2. Answer-level capture — Can you see the complete AI response, not just a score?
3. Accuracy classification — Can you distinguish negative from factually incorrect?
4. Evidence — Does it show which URLs/sources appear to have caused the claim?
5. Model coverage — ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews/AI Mode, Copilot, etc.
6. Change detection — Can you alert when a previously accurate answer becomes negative/inaccurate?
7. Reproducibility — Does it run prompts repeatedly enough to account for stochastic answers?
8. Workflow — Can PR/communications/legal/SEO teams assign and resolve problematic claims?

That #3/#4 distinction is crucial. “AI says we're expensive” is a sentiment/positioning issue. “AI says our product was acquired by X in 2024” is a factual accuracy issue. You want a system that treats those differently.

What I'd actually do

For an enterprise brand, I'd run a 2–4 week bake-off between Profound and Scrunch using the same ~100–300 high-value prompts:

• “[Brand] reviews”
• “Is [Brand] trustworthy?”
• “[Brand] alternatives”
• “[Brand] vs [competitor]”
• “Problems with [Brand]”
• “[Brand] pricing”
• “[Brand] security”
• “[Brand] complaints”
• “[Brand] best for [use case]”
• category questions where your brand should appear

Then score each response for mention → recommendation → sentiment → factual accuracy → citation quality → competitive framing.

One reason I'd favor Profound for the final decision is that its product explicitly includes an “Ensure AI Accuracy” workflow and FactCheck functionality, which maps unusually closely to the problem you described. Profound

Bottom line: Profound for AI reputation/accuracy monitoring; Scrunch for broader AI-search observability. If you tell me your approximate company size and whether this is primarily PR/reputation, marketing/GEO, legal/compliance, or customer experience, I can narrow it down to the best 2–3 options and compare pricing, coverage, and implementation effort.

If you’re a small agency on a limited budget, I’d start with Otterly.ai.

• otterly.ai — best budget starting point. Current reporting puts its entry plan around $29/month, with a small prompt allowance and coverage including ChatGPT, Google AI Overviews, Perplexity, and Copilot. It tracks mentions, citations, position, and visibility trends. Is My Brand in AI NXTG.AI
• peec.ai — better if you need more serious agency reporting. It starts around €89–$95/month and is stronger for competitor comparisons, sentiment, multilingual monitoring, and citation analysis. Loudmink TrendlyAI Blog
• tryprofound.com — probably overkill for you initially. It's much more oriented toward deep analytics and larger organizations; its entry pricing is around $99/month but meaningful multi-engine capability gets considerably more expensive. Loudmink
• Semrush AI Visibility Toolkit is worth considering if you already pay for Semrush. An add-on can make more sense than adding another standalone subscription. MentionsAPI

What I'd do in your shoes

For an agency, the important distinction isn't simply "does it mention my client?" You want to monitor:

1. Mention rate — how often the client appears.
2. Share of voice — client vs. competitors.
3. Citation URLs — why the AI is mentioning them.
4. Prompt-level results — the actual questions you're tracking.
5. Change over time — whether your SEO/content work is increasing visibility.
6. Multiple clients — ideally without paying a separate full subscription for each.

I'd therefore start with Otterly on 5–10 high-value prompts per client, rather than trying to monitor hundreds of queries. Once you're selling AI visibility as a recurring client deliverable, move up to Peec or an agency-oriented platform.

One caveat: this market is changing very quickly, and published pricing/features are moving around, so I'd verify the exact current tier before committing. Is My Brand in AI

If you tell me roughly how many clients you want to monitor (e.g. 5, 10, 25) and your monthly budget, I can narrow this to the cheapest setup that still gives you useful client reporting.

If your goal is specifically reputation risk from what AI assistants say about your company, rather than generic “AI SEO,” I’d shortlist these:

1. otterly.ai — best startup default.

It monitors your own prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and tracks mentions, sentiment, citations, competitors, and changes over time. It also runs monitoring daily. Otterly Otterly AI
Why I’d start here: relatively accessible, broad coverage, and you can actually see the underlying answers rather than just getting a mysterious “visibility score.” Its site currently lists pricing starting at $29/month. Otterly

2. tryprofound.com — best if reputation is strategically important.

Profound goes further on AI accuracy and reputation, including identifying incorrect claims and their sources. It also provides visibility/share-of-voice analysis and supports a larger set of AI platforms. Profound Profound
I'd look at this if you're a funded company with a marketing/PR team and a meaningful brand-risk budget.

3. Peec AI — worth evaluating for analytics.

It's another major player in AI-search visibility monitoring, particularly if you care about clean competitive analytics and reporting. Current industry comparisons generally put Peec, Otterly and Profound in the leading group. Conbersa Refine AI

What I'd actually monitor

Don't just track:

“Is my company mentioned?”

Build a reputation-risk prompt set around questions a prospect, journalist, investor, or employee might ask an AI:

• “What is [Company]?”
• “Is [Company] legitimate?”
• “What are the biggest complaints about [Company]?”
• “What are the alternatives to [Company]?”
• “Is [Company] better than [Competitor]?”
• “Should I buy/use [Company]?”
• “What are the risks of using [Company]?”
• “What do customers say about [Company]?”
• “Who founded [Company], and what is their background?”
• “Has [Company] had any controversies?”
• “Is [Company] financially stable?”
• “What are the disadvantages of [Company]?”

Then score each answer for accuracy, sentiment, prominence, competitor substitution, and source quality.

The particularly valuable signal isn't simply “ChatGPT said something negative.” It's:

“AI assistants are repeatedly making the same incorrect/negative claim, and we can identify the web sources apparently feeding that claim.”

That's where you can actually intervene.

My pick for a startup: start with OtterlyAI, spend a couple of weeks establishing a baseline, and only move to Profound if you discover that you need deeper enterprise-level monitoring or remediation. Otterly's current product explicitly supports response-by-response analysis, sentiment, competitor tracking and citation analysis, which maps unusually well to the reputation-risk use case. Otterly Otterly AI

If you tell me your startup's category + whether you're B2B or B2C + roughly how much you'd spend/month, I can narrow this to the best 2–3 options and tell you exactly what I'd monitor.

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. I’d treat this as an AI-answer Share of Voice (SoV) monitoring problem rather than traditional SEO rank tracking.

My recommendation: start with Profound

tryprofound.com is probably the strongest fit if your goal is specifically “How often does ChatGPT mention us vs. competitors, and how is that changing?”

It tracks prompts across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode and other answer engines, and provides visibility, Share of Voice, competitor rankings, citations, sentiment, position, and prompt-level analysis. Profound Profound

The key metrics I'd put on an executive dashboard are:

Profound explicitly defines SoV around the frequency of your brand mentions relative to competitors and provides rankings/charts for it. Profound Knowledge Base Profound Knowledge Base

A simple way I'd calculate the headline number

Suppose you run 1,000 relevant prompts and get:

• Your company: 240 mentions
• Competitor A: 300
• Competitor B: 180
• Competitor C: 120
• Others: 160

Your AI Share of Voice = 240 / 1,000 = 24% under a mention-based methodology.

I'd actually maintain two separate metrics, though:

Visibility:
answers mentioning you / total answers

Competitive SoV:
your mentions / all tracked brand mentions

That's important because a brand can have high visibility while still losing competitive share. Peec's documentation makes the same distinction between visibility and SoV. Peec.ai Docs

Profound vs. Peec AI

peec.ai is the other product I'd seriously evaluate. It has particularly clear dashboards for competitor visibility, SoV, position and sentiment, with filtering by model, country, topic and prompt. Peec AI Peec.ai Docs

I'd choose:

• Profound → best if this becomes a serious enterprise competitive-intelligence/AEO program, especially if you care about citations and discovering unexpected competitors.
• Peec AI → attractive if you primarily want a straightforward brand vs. competitor visibility/SoV dashboard.
• Build your own → worthwhile if you have unusual prompt taxonomies, need proprietary scoring, or want to integrate the data into an existing BI/marketing stack.

The dashboard I'd build

Then drill down:

1. Overall SoV — current % and week/month change.
2. SoV by AI engine — ChatGPT vs Gemini vs Perplexity, etc.
3. SoV by topic — product comparisons, “best X,” alternatives, pricing, use cases, etc.
4. Prompt-level battles — “Competitor A appears 78%, we appear 21%.”
5. Citation gap — sites/pages cited for competitors but not you.
6. Trend — SoV over the last 30/90 days.
7. Answer quality — position + sentiment, not just presence.

The last two are important: a 25% SoV isn't necessarily better than 20% if the competitor is consistently recommended #1 and you're mentioned as an afterthought.

One important implementation detail

Don't just track a handful of manually invented prompts. Build a representative prompt universe covering your category, buying funnel, use cases, competitors, alternatives and high-intent questions, then run the same corpus repeatedly. Profound runs tracked prompts daily, while Peec also supports prompt-level and model-level analysis. Peec.ai Docs Profound

If this is for a marketing/brand team, my short answer is: pilot Profound and Peec side-by-side for 2–4 weeks, using the same 100–500 prompts, and compare the resulting SoV numbers before committing. The methodology matters as much as the dashboard.

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

Yes — this is now a defined category usually called AI visibility / AI search monitoring / GEO (Generative Engine Optimization). The tools actually run a fixed prompt set against AI assistants, capture the returned answers, identify brand/competitor mentions and citations, and calculate share of voice. Spawned Viali AI

My shortlist

• tryprofound.com — Strong enterprise-oriented choice for tracking brand presence across AI engines and analyzing what models say about you and competitors. A recent benchmark found Profound among the most frequently surfaced AI-visibility tools. Foglift
• otterly.ai — Purpose-built AI-search monitoring; particularly worth considering if your main KPI is brand mentions/share of voice across prompts and competitors.
• ahrefs.com — A good option if you're already an Ahrefs customer. It tracks ChatGPT, Gemini, Perplexity, Copilot and Google AI surfaces, including mentions, competitors and cited sources. Ahrefs
• peec.ai — Focused specifically on AI-search visibility and competitive monitoring.
• getlatentline.com — Interesting if you want answer-level evidence behind the SOV number. It tracks the prompts, answers, mentions, competitors and sources rather than just giving you a black-box visibility score. Latentline
• agentgeo.org — More API/developer-oriented. Particularly compelling if you want to build your own SOV calculation from the raw answers rather than rely on a vendor's metric. AgentGEO

One important distinction

If by "voice and chat channels" you mean spoken assistants such as Siri/Alexa/Google Assistant in addition to ChatGPT/Gemini/Perplexity, that's a different requirement.

Most of the current AI-SOV platforms primarily monitor text-based AI answers/search surfaces. For example, Ahrefs currently covers ChatGPT, Gemini, Perplexity, Copilot and Google's AI surfaces. Ahrefs

So if your goal is something like:

"Across every place a consumer can ask an AI about our category, what % of recommendations/mentions are us vs. competitors?"

I'd evaluate vendors specifically on actual answer crawling/API access, voice-assistant coverage, prompt sampling, repeat runs, competitor detection, and whether you can export the raw answers. Because AI answers are nondeterministic, multiple runs per prompt are important for a defensible SOV number. verityscore.io organikpi.com

If you tell me your industry and whether you mean ChatGPT/Gemini/Perplexity only or also Siri/Alexa/voice assistants, I can narrow this to the 2–3 tools I'd actually shortlist.

Yes. There’s now a fairly established AI visibility / AEO / GEO software category that does exactly this: tracks whether your brand appears in AI-generated answers and benchmarks you against competitors.

For an enterprise team, I’d look at these first:

• tryprofound.com — probably the clearest pure-play enterprise option. It tracks brand visibility across AI answer engines, prompt-level performance, citations, and competitor share of voice. It’s repeatedly positioned as the enterprise-oriented choice. Mention Radar AEO Labs
• similarweb.com — interesting if you want AI visibility connected to traffic, market intelligence, and competitive benchmarking, rather than just an AEO dashboard. Recent comparisons highlight its ability to connect AI visibility with broader digital/traffic context. Prism News Prism News
• peec.ai — more focused on AI-search monitoring and competitive visibility. Good fit if the core question is “how often are we recommended vs. competitors, and in which prompts/models?” Conbersa Mention Radar
• athenahq.ai — worth evaluating if you want the visibility data connected to GEO/content workflows and reporting rather than just measurement. Prism News
• sona.com — particularly interesting because it says it runs prompts against the consumer-facing AI experiences, then captures mentions, position, sentiment, citations, and competitor benchmarks. Sona

What these platforms actually measure

The useful ones go beyond a generic “AI visibility score.” They can give you things like:

That competitor + prompt + citation-source layer is the part I'd pay particular attention to. A single AI visibility score can be pretty vanity-oriented; knowing “Competitor X is winning 37 high-intent prompts because these 14 third-party pages are being cited” is much more actionable. AI Visibility Software Prism News

If you're evaluating this as a potential enterprise software category / product opportunity, there's an interesting distinction: most of these tools are essentially “rank trackers for AI answers.” The more differentiated products are moving toward competitive intelligence + attribution + recommendations/workflows. For example, newer platforms explicitly position themselves around connecting the visibility gap to the sources and actions needed to close it. geovium.com franixo.com

If you tell me whether you're shopping for a tool or thinking about building one, I can map the competitive landscape and tell you where the gaps are.

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.

Yes. There are now platforms that get quite close to exactly that combination, although “citation quality scoring” is still less standardized than AI share of voice.

The strongest matches I found:

• peec.ai — probably the closest established fit. It tracks AI visibility, Share of Voice, position, sentiment, and competitors, while also analyzing the sources/citations behind AI answers. Importantly, it distinguishes sources accessed from citations actually shown and has competitor citation-gap analysis. Peec AI Peec AI
• searchpanel.ai — particularly close to your wording. It scores competitors on the same scale, measures Share of Voice and head-to-head position, and captures the sources cited for each recommendation. Searchpanel
• bluejar.ai — combines AI visibility, competitor benchmarking and citation tracking, with a focus on identifying which citations need to be fixed. BlueJar
• insertengine.com — explicitly combines visibility scoring + competitor tracking + citation intelligence + an action engine. InsertEngine -
• searchdock.io — interesting if you want a more measurement-oriented approach. It reports AI Share of Voice against configured competitors alongside raw mention/citation counts and breaks results down by engine. SearchDock

The gap I see

If by “citation quality scoring” you mean something more sophisticated than “how often are we cited?”—for example:

Brand A: 42% AI Share of Voice
Brand B: 31%
But Brand B's citations are higher-quality because they're from authoritative, independent, category-relevant sources

—then I don't see a dominant platform that has fully solved that yet.

Most platforms currently measure things like:

• citation frequency
• domains/URLs cited
• citation rate
• competitor citation gaps
• source type
• whether the brand is mentioned/recommended
• AI Share of Voice

Peec, for example, classifies sources into editorial, corporate, UGC, reference, and owned-site categories and provides citation-gap analysis. Peec AI Peec.ai Docs

But a true Citation Quality Score could go further and score each citation on dimensions such as:

Authority × relevance × independence × topical expertise × freshness × prominence × competitor exclusivity

That would give you a much more useful metric than raw AI visibility.

If you're evaluating this as a product opportunity

I'd frame the category as:

AI Share of Voice + Citation Intelligence

rather than simply “AI visibility.”

The interesting dashboard would be something like:

That combination would answer not just “Are we winning AI search?”, but “Why are we winning/losing, and are the sources supporting our visibility actually strong?”

So, yes—the pieces exist, and Peec/Searchpanel/BlueJar are probably the closest current products. But there still appears to be room for a platform whose core differentiator is a rigorous, competitor-relative quality of citation, rather than merely citation volume. Peec AI Searchpanel BlueJar

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

For what you’re describing, OtterlyAI is probably the closest fit.

otterly.ai specifically tracks which URLs and domains AI search engines cite, rather than merely tracking whether your brand was mentioned. It can monitor prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude. Otterly Otterly

What you'd get for an ecommerce blog

You could give it prompts such as:

• “What are the best running shoes for beginners?”
• “Best gifts for a 30-year-old man”
• “Which air fryer should I buy?”
• “Best organic skincare brands”
• “How do I choose a standing desk?”

Then see:

• Which domains AI cites — e.g. nytimes.com, reddit.com, yourcompetitor.com
• Which specific URLs get cited
• Which AI engine produced the citation
• How frequently each domain/URL is cited
• Which prompts caused a particular URL to be cited
• Whether your site was cited versus competitors
• Citation trends over time
• Citation gaps where competitors are being sourced but your content isn't Otterly OtterlyAI

It also has Domain Ranking & Analytics, which tracks domains and their URL citations and changes in link position over time. Otterly

One particularly useful feature

If your goal is “figure out what websites influence ChatGPT's answers in my ecommerce niche”, don't limit the tracking to your own domain.

Track a set of important commercial prompts and look at the top cited domains across all answers. That can reveal that, for example, AI answers in your category disproportionately draw from:

reddit.com → wirecutter.com → major publications → manufacturer sites → competitors

That gives you a much more actionable GEO/content strategy than simply knowing whether your own site appeared.

Otterly also provides API access to citation data, so you could potentially pipe the results into your own SEO/content dashboard. Otterly

My take: If your primary question is “What domains and URLs are ChatGPT/Perplexity/etc. citing for the queries my potential customers ask?”, I'd start with OtterlyAI rather than a conventional SEO tool.

If you tell me your ecommerce niche, I can also compare OtterlyAI vs Semrush vs Peec AI vs Ahrefs vs other AI-citation trackers specifically for finding which third-party sites you should get mentioned on.

For a small marketing agency managing multiple clients, I’d shortlist these:

• peec.ai — best overall agency fit. It’s specifically built around AI-search visibility, tracks multiple assistants, and is commonly positioned as the sweet spot between inexpensive trackers and enterprise platforms. One 2026 comparison puts it at about $95/mo starting and calls it a strong choice for agencies. AEO Labs Conbersa
• otterly.ai — best budget option. Good if you need to monitor lots of smaller clients without an enterprise bill. It tracks AI mentions/citations and share of voice across major AI search surfaces. AEO Labs Foglift
• citations.io — particularly interesting for agencies. It explicitly offers agency/multi-client tracking, white-label reports, competitor share of voice, citation monitoring, and implementation recommendations. It currently tracks ChatGPT, Perplexity, Gemini, and Claude. Citations
• foglift.io — worth testing if citation data is your priority. It tracks ChatGPT, Perplexity, Google AI, Claude, and Gemini, including cited URLs, competitors, share of voice, position, and sentiment. Foglift
• tryprofound.com — strongest enterprise-style option. Excellent depth, but probably more than a small agency needs unless AI visibility measurement is becoming a major revenue service. Independent 2026 testing puts it among the leaders for citation share. GeoHero Foglift

My pick

If your agency has, say, 5–30 clients, I'd start by demoing Peec AI and Citations.io, with Otterly as the lower-cost alternative.

The key distinction is that you want citation share of voice, not merely "does ChatGPT mention my brand?" A useful platform should let you see something like:

Client A: 24% citation SOV
Competitor B: 31%
Competitor C: 18%
Other: 27%

…and then break that down by prompt → AI assistant → cited URL → competitor → position. That's much more actionable for an agency reporting GEO/AEO results to clients. Foglift Citations

If you tell me roughly how many clients you manage and your monthly budget, I can narrow this to the 2–3 cheapest tools that support multi-client/white-label reporting and compare their current pricing.

For a university press, I’d look less at generic “AI SEO” tools and more at platforms that can answer:

1. Which books, chapters, articles, or domains are AI assistants citing?
2. For which research questions are our publications missing?
3. Which competing presses, journals, repositories, or institutions are getting surfaced instead?

A practical shortlist:

My recommendation for a university press

I would probably build a two-layer stack:

1. AI answer citation monitoring

Use one of:

• Profound (larger press, many disciplines, dedicated analytics team)
• Otterly.AI or Peec AI (smaller team, experimentation) CitationDesk Distribution.studio

Track prompts such as:

• “What are the best books on [field]?”
• “Who are leading scholars on [topic]?”
• “What should I read about [historical event/theory/method]?”
• “Recommend academic sources on [subject].”

Record:

• cited URLs
• cited domains
• publisher/platform
• author names
• whether the citation points to: - your landing page
• DOI page
• institutional repository
• Google Books
• JSTOR
• Internet Archive
• competitor press pages

2. Scholarly impact intelligence

Pair that with:

• Scopus
• Web of Science
• Dimensions
• Scite

These tell you traditional scholarly influence; AI trackers tell you AI-mediated discoverability. They are related but not the same. LLMrefs Grow with Tejas

Metrics I’d put on a press dashboard

A useful monthly dashboard might include:

• AI citation share

• % of tracked prompts where your press appears as a cited source
• Citation gap

• your press vs. university presses, journals, repositories, and commercial competitors
• Top AI-discovered titles

• books/chapters most frequently surfaced
• Lost-query report

• important scholarly questions where competitors appear but you do not
• Citation path

• “AI cited our book page” vs. “AI cited a third-party review mentioning our book”
• Metadata problems

• cases where AI cites an author’s profile, repository copy, or secondary source instead of the canonical press page

A low-cost pilot I’d run first

For 8–12 weeks:

1. Pick 100–200 high-value prompts across your strongest subject areas.
2. Run them weekly in ChatGPT, Claude, Gemini, and Perplexity.
3. Store every cited source URL.
4. Identify patterns: - Are AI systems finding your books?
5. Are they finding reviews instead?
6. Are they missing your catalog because metadata is weak?
7. Improve: - structured metadata
8. author pages
9. chapter abstracts
10. open-access excerpts where appropriate
11. persistent identifiers (DOIs, ORCID links, Crossref metadata)

The biggest strategic shift is that discoverability is moving from “rank for a keyword” toward “be a trustworthy source an AI system chooses to cite.” AI visibility tools are emerging quickly, but no single platform gives a complete scholarly picture yet. SiteTest.ai Nick Lafferty

For a university press, I’d prioritize citation-level source tracking over simple brand mentions—knowing which books and pages get cited is much more actionable than knowing your press name appeared. GetIntel

Yes. The category is usually called AI visibility monitoring, LLM citation tracking, or GEO (generative engine optimization) monitoring. These platforms periodically ask AI assistants questions, record whether your site/blog appears as a cited source, and alert you when your visibility changes. RankScope Sona

Some options:

• semrush.com — Good if you already use SEO tools; its AI visibility features track appearances in AI-generated answers alongside broader SEO data. Search Engine Land
• otterly.ai — Focused on AI search monitoring; tracks mentions/citations across assistants such as ChatGPT, Perplexity, and others. KITLabs
• peec.ai — Built around monitoring brand visibility in AI answers and comparing competitors. Citation Hawk
• tryprofound.com — More enterprise-oriented AI visibility analytics. Search Engine Land
• genwolf.ai — Tracks prompts, mentions, citations, and source domains across several AI assistants. Genwolf

A couple of important caveats:

• These tools usually do not detect every time an AI model has “read” your blog. Models like ChatGPT generally do not expose a live feed of training data usage or every retrieval event.
• They mostly detect observable citations: “When someone asks an AI assistant this question, does the assistant cite your URL?” Citation Hawk Search Engine Land
• For a personal blog, you may not need a full platform. A lightweight setup can work: 1. Pick 20–50 questions your ideal readers might ask AI assistants.
• Track whether your pages appear as citations in ChatGPT, Perplexity, Gemini, and Claude.
• Run the checks weekly or monthly.
• Alert yourself when a page starts appearing—or disappears.

If your goal is specifically “email me the moment ChatGPT/Perplexity starts citing my blog URL”, the market is still a bit immature; most tools are prompt-monitoring dashboards rather than true URL mention firehoses. SEOExpert

If you tell me your blog size (e.g., 20 posts vs. 5,000 pages) and whether you care about ChatGPT only or all AI assistants, I can narrow down the best fit.

Yes. There’s now a fairly mature category for this: AI visibility / AI citation monitoring.

If your specific question is “Did ChatGPT, Perplexity, Gemini, etc. cite one of my actual URLs?”, rather than merely “did they mention my brand?”, I’d look at these:

• otterly.ai — probably the easiest place to start. It tracks the exact URLs cited in AI answers, including which of your pages are being cited, across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot. It also supports alerts/reporting. Otterly Otterly
• Peec AI — more marketing/SEO-oriented, with page-level citation tracking and competitive visibility analysis. It’s one of the more commonly compared options for this use case. The Rank Masters Conbersa
• Profound — geared more toward larger companies/enterprise GEO programs, with detailed source-level citation intelligence. SEO Counselors

One important distinction

These platforms generally don't have a magical feed of every time an AI assistant anywhere on the internet cites your page.

Instead, they periodically run a set of relevant prompts against AI search systems and record the sources those answers use. So, for example, you might configure:

“What are the best resources for learning X?”
“How does X work?”
“Best tools for X in 2026?”

Then the platform tells you something like:

ChatGPT — Aug 24
Citation: yoursite.com/blog/how-x-works

That makes them particularly useful for seeing which individual articles are becoming AI sources and whether citation frequency is increasing.

If your goal is specifically “alert me whenever any of my URLs gets cited, even if I didn't know which prompts to monitor”, that's a slightly different problem—and I can dig into whether there's a tool that does that rather than just prompt-based monitoring.

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 an enterprise content team, you’re looking for an AI visibility / GEO (Generative Engine Optimization) platform rather than a traditional SEO rank tracker. The strongest options today track things like:

• Citation frequency — how often AI models cite your pages/brand
• Citation sources — which URLs/domains are being referenced
• AI answer share of voice — how often you appear vs. competitors
• Position/rank within generated answers (where available)
• Prompt-level tracking — the questions your customers actually ask
• Multi-model comparisons — ChatGPT vs. Claude vs. Gemini vs. Perplexity, etc.

A shortlist for enterprise content teams:

My recommendation by use case

For a global content/SEO team managing many pages and stakeholders

• Start with Citations.io or Profound. You’ll want historical trends, competitor benchmarking, and reporting workflows. Citations.io

For a content operations team trying to improve what gets cited

• Prioritize platforms that show: - exact cited URLs
• missing citation opportunities
• competitor pages winning citations
• prompt-level failures

For an SEO team adding AI search to an existing stack

• Look for API/export capability and integrations so AI visibility data can flow into dashboards.

Evaluation checklist for an enterprise purchase

Before signing, ask vendors:

1. Which models are queried directly?

• ChatGPT (which version?)
• Claude?
• Gemini?
• Perplexity?
• AI Overviews?
• Do you measure citations or just mentions?

• A brand mention is weaker than being the cited source.
• Can we upload our own prompt set?

• Enterprise teams usually need hundreds/thousands of buyer-intent queries.
• Can we see citation rank?

• Example: “Our page was citation #1 of 8 sources.”
• Can we export raw answers and evidence?

• Important for executives, PR, and content attribution.
• Does it support multiple brands/regions/business units?

• Critical for enterprise governance.

If I were building a 2026 enterprise content measurement stack, I’d shortlist Citations.io, Profound, Zumi, and BotScope for evaluation, then choose based on model coverage, data retention, API access, and reporting needs. Citations.io BotScope Zumi

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 “show me the AI questions where competitors/research sources get cited but our content doesn’t, so we can create content that earns the citation,” then OtterlyAI is probably the closest fit.

• otterly.ai — Its Gap Analyzer identifies prompts where competitors are named/cited and you aren't, while its citation tracking shows which URLs AI engines use instead. It also has content-audit and content-brief functionality aimed at turning those gaps into content actions. Otterly Otterly
• tryprofound.com — Better if you're an enterprise team wanting deeper source-level citation intelligence and competitor overlap across AI engines. SEO Counselors Bushnote
• peec.ai — More focused on clean AI-search visibility/citation analytics; useful for identifying where you're absent, but less of a content-production workflow. GeoHero

For your specific use case

I'd frame the requirement as “citation-gap / source-gap analysis,” not simply AI visibility.

You want a workflow like:

Prompt → AI answer → citations → competitor/source cited → assertion with no citation → opportunity → your research/data that could substantiate it → content/page to publish or update → re-test citation.

That's more valuable than a generic “AI visibility score.” Research on citation behavior also suggests that topical relevance and evidence-rich content are important determinants of which retrieved sources get cited. arxiv.org arxiv.org

My pick: start with OtterlyAI if the content team needs actionable gaps; evaluate Profound if you have an enterprise GEO/SEO operation and need deeper competitive source intelligence.

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:

For a small marketing team, I’d avoid the enterprise AEO/GEO platforms unless you have a large SEO budget. The best fit is usually a lightweight AI visibility tracker that can answer:

• “How often does our brand appear in ChatGPT, Claude, Gemini, Perplexity, etc.?”
• “Which competitors are winning?”
• “Which prompts are we missing?”
• “Why are they being cited instead of us?” Spawned Built In

Here are the strongest options:

My shortlist for a small marketing team

Best overall: Otterly.ai

Good if your goal is: “Give me a weekly dashboard showing whether we’re gaining or losing AI visibility.”

Best dedicated AI share-of-voice tool: Peec AI

Good if AI search is becoming a major acquisition channel and you want prompt-level tracking. Semrush

Best if you already pay for SEO software: Semrush

Good if you want one system covering:

• traditional SEO
• competitor research
• AI visibility
• content opportunities Semrush

Best budget approach

For many small teams, I’d start with:

1. Pick 50–200 buyer-intent prompts.
2. Track them weekly across ChatGPT, Claude, Gemini, and Perplexity.
3. Measure: - brand mention rate
4. competitor mention rate
5. average position in answers
6. citations/source domains
7. sentiment/accuracy

A tool that only counts mentions is less valuable than one that shows which prompts you lose and what sources competitors are getting cited from. Spawned visibility.so

If you tell me your industry (B2B SaaS, ecommerce, local business, etc.), monthly budget, and whether you already use Semrush/Ahrefs/HubSpot, I can narrow this to 2–3 choices.

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.

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 is usually called AI visibility tracking, AI citation tracking, Generative Engine Optimization (GEO) tracking, or Answer Engine Optimization (AEO) monitoring. These tools don't literally crawl every AI assistant in the way Googlebot crawls the web; instead, they typically run tracked prompts against AI assistants, capture the answers, and record which domains/pages are cited or mentioned. Slate Foglift

Tools worth looking at:

• ahrefs.com — Tracks visibility across ChatGPT, Gemini, Perplexity, Copilot, and Google AI surfaces; reports mentions and cited domains/pages. Ahrefs
• otterly.ai — Focused on monitoring AI search results, citations, and crawlability signals across major AI answer engines. Citation Hawk
• conductor.com — Enterprise SEO platform with AI visibility/citation tracking capabilities. Citation Hawk
• tryprofound.com — Enterprise-focused AI search monitoring (often used by larger brands).
• peec.ai — Tracks brand visibility and citations in AI answers.
• citations.io — Specifically focused on which AI engines cite your brand and which sources they use. Citations.io
• indexly.ai — Tracks mentions, citations, sentiment, and AI referral traffic. Indexly

What you generally get from these platforms:

• Which AI assistants cite you

• ChatGPT
• Perplexity
• Gemini
• Claude
• Google AI Overviews / AI Mode
• Copilot (varies by vendor) Slate
• Which of your URLs appear

• /blog/how-to-x
• /docs/product-guide
• /research/report
• pricing/product pages
• The prompt that triggered it

• “best CRM for startups”
• “alternatives to X”
• “how do I solve Y problem”
• Who beats you

• competitor domains cited instead
• third-party pages ranking above your own content
• Trends

• citation share over time
• new pages being picked up
• lost citations

One important distinction: if you mean “which AI crawlers are actually visiting my site”, that is a different problem. You’d look at server logs, CDN analytics, or bot-management tools to identify crawlers such as GPTBot, ClaudeBot, Google-Extended, etc. If you mean “which of my pages are being used as sources in answers users see”, the AI citation trackers above are the right category. Foglift

For a marketing/SEO team, I’d usually evaluate them by asking:

1. Can it show the exact prompt + AI answer + cited URL?
2. Does it track your competitors’ citations?
3. Can it export the data?
4. Does it distinguish mention vs actual linked citation?

Those four capabilities are more useful than a single “AI visibility score.” Ahrefs Foglift

Yes. The category you’re looking for is usually called AI visibility tracking, LLM visibility, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization) software.

These platforms let you define the questions your customers might ask—e.g. “What are the best payroll platforms for a 100-person company?”—and then repeatedly run those prompts across multiple AI systems to see whether your brand appears, where it appears, which competitors appear, and which sources the AI cites. Baarely Lyra

The ones I'd shortlist

Current comparisons put Profound at the high end for breadth and enterprise analytics, Peec in the mid-market/agency sweet spot, and Otterly as one of the easiest low-cost ways to start. Baarely Ayzeo Bloomiro

What I'd choose

If by “tell me which queries our brand ranks for” you mean you want something analogous to Google Search Console's queries → impressions → position, I'd focus on Profound, Peec, or Otterly.

The important distinction is that AI doesn't really have a conventional “keyword ranking” system. A good platform should instead show you something like:

Prompt: “Best CRM for a 50-person SaaS company”
ChatGPT: Brand mentioned #2
Perplexity: Brand mentioned #4
Gemini: Not mentioned
Claude: Brand mentioned #1
Competitor: Mentioned in 4/4
Citations: Your site, G2, Reddit, competitor comparison pages
Visibility/share of voice: 38%

That's much more useful than a generic “AI visibility score.” The better platforms track the individual prompts, competitors, citations, sentiment, and changes over time. PickMySoft UX Continuum

One especially important consideration: make sure the tool actually supports the AI surfaces your customers use. Coverage varies substantially—some products that advertise “multi-engine” monitoring only include a subset on their cheaper plans. Ayzeo Stork.AI

If you tell me your approximate company size, number of brands/domains, and whether you're B2B or B2C, I can narrow this to the 2–3 tools I'd actually demo, including current pricing and exactly what each can report.

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.

Yes. There are now several platforms specifically aimed at agencies selling AI visibility / GEO as a recurring service, with multi-client monitoring and white-label reporting.

A few worth looking at:

• peec.ai — probably one of the more mature options. Tracks mentions and citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot, with multi-client management, automated reporting, APIs, and branded Looker Studio dashboards. Peec AI
• geneo.app — explicitly positioned as a white-label AI visibility platform. Offers your own domain, logo, client portal, and client-facing reports, with metrics such as citations and share of voice. Geneo
• qwairy.co — built around multi-client GEO management, portfolio dashboards, client access, white-label reporting, and Looker Studio integration. Qwairy
• towergeo.com — particularly agency-oriented: multi-client workspaces, competitor tracking, white-label PDFs, branded client dashboards, custom domains and scheduled reports. Tower GEO
• agencyscope.ai — more narrowly focused on the reporting workflow. It runs recurring checks across ChatGPT, Perplexity and Gemini and turns the evidence into white-label PDFs. AgencyScope
• jujugeo.com — interesting if you want more than reporting: it identifies where competitors are being cited instead, drafts fixes, then re-checks the same query after publishing to demonstrate citation movement. Its agency tier currently advertises up to 25 brands and white-label reporting. JujuGeo
• aisearchrank.ai — positioned as a full agency GEO platform, combining multi-client management, white-label reporting, audits, optimization and publishing workflows. AI Search Rank

If you're evaluating this as an agency

I'd separate them into three categories:

Peec is probably the first one I'd demo if you already have an SEO/content agency and want to add AI visibility reporting without rebuilding your reporting stack. Its API/MCP and Looker Studio integration are especially useful if you want to automate reports across a large client roster. Peec AI Peec AI

If you're thinking about building a platform like this, there's also a pretty interesting gap: most tools measure "did the AI mention/cite my client?", but fewer turn that into a genuinely useful agency deliverable—e.g. which competitor got cited instead, which source caused it, what should we change, and did the citation move after the change? jujuGEO is explicitly moving in that direction. JujuGeo

I can also compare 10–15 of these platforms on pricing, AI engines, citation-level data, API, white-label portals, Looker Studio, automated reports, and number of client accounts if you're deciding which one to use.

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.

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 goal is specifically monitoring how AI assistants talk about your brand—including whether the sentiment is positive/negative, how often you're mentioned, what competitors are recommended, and which sources are cited—you want an AI visibility / AEO monitoring platform, not traditional social-listening software.

My shortlist

My pick: Profound

For a serious brand-monitoring program, I'd start with Profound. Its Answer Engine Insights product explicitly measures sentiment, visibility, citations, share of voice and positioning, while querying the actual answer engines on a recurring basis. Profound Knowledge Base

That distinction matters: you don't merely want to know "Did ChatGPT mention us?" You want something closer to:

What does ChatGPT say about us? Is that portrayal favorable? How does it compare with competitors? Which prompts produce negative perceptions? Which sources are causing that perception? Is the answer changing over time?

Profound currently covers a particularly broad set of AI surfaces, including ChatGPT, Claude, Gemini, Perplexity, Copilot, Grok, DeepSeek and Google's AI experiences. Profound Profound

One important caveat

"Sentiment" in AI answers isn't quite the same as social-media sentiment. A brand can be mentioned positively but still lose the recommendation, for example:

"Brand X is reliable, but Brand Y offers better value."

So I'd prioritize platforms that let you analyze sentiment + recommendation/positioning + share of voice + citations, rather than buying a tool based solely on a positive/neutral/negative score.

If you tell me your company size and approximate monthly budget (e.g. <$100, $100–500, $500–2k, enterprise), I can narrow this to the top 2–3 options and compare pricing, assistant coverage, sentiment accuracy, alerts, API access, and reporting.

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.