Answers that mention Peec AI

If you’re a small ecommerce shop and budget is the priority, I’d start with Otterly.AI.

• Otterly.AI — best budget starting point. Current comparisons put its entry plan around $29/month, with tracking for a small set of prompts across ChatGPT, Google AI Overviews, Perplexity, and Copilot. It can show whether your brand is mentioned and which URLs get cited. Loudmink GTM Help
• Peec AI — better if you need substantially more prompts, competitors, reporting, or multiple people working on it, but it starts around $95/month, so I'd consider it later. Loudmink
• Profound — excellent for deep enterprise-level analysis, but overkill for a small shop and much more expensive. Omid Saffari

What I'd actually do

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

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

Then track whether your products are recommended, which competitors appear, and which websites/pages the AI cites. That's much more actionable than simply checking whether your domain gets mentioned.

One caveat: the cheap plans have relatively low prompt limits, and some newer AI engines can cost extra. Loudmink

Bottom line: Otterly.AI for a tight budget. If you tell me roughly how many products you have (e.g. 20, 200, 2,000) and whether you mainly care about ChatGPT, Google AI, or both, I can tell you the cheapest setup I'd use.

Yes. For a mid-market SaaS team specifically focused on competitive presence in AI answers, I’d shortlist these:

My pick: Peec AI

For your exact use case, Peec is probably the first demo I'd take. It explicitly measures:

• Share of Voice against named competitors
• Visibility and average position
• Sentiment
• Competitor-by-competitor comparisons
• Historical trends by AI engine
• Which domains/URLs are being cited
• Citation gaps where competitors are cited but you aren't
• Prompt-level performance

Peec defines SoV as your share of brand mentions relative to the total mentions of tracked brands, and lets you break the comparison down by engine. Peec AI Peec.ai Docs

Its citation analysis is particularly relevant for SaaS: you can see which URLs/domains are feeding AI answers and identify sources where competitors are cited but you aren't. Peec AI

When I'd choose the others

Otterly — I'd choose this if you want to get monitoring running cheaply and don't need a particularly deep analytics workflow. Current market comparisons put its entry point around $29/month, with higher tiers as your prompt volume grows. Stork.AI

Profound — choose this if AI visibility is becoming a serious cross-functional program involving SEO, content, PR, brand, and executives. It is positioned much more toward enterprise-scale reporting and broad engine coverage. Bloomiro Stork.AI

Scrunch — interesting if you want the product to go beyond "here's your visibility" into diagnosing and optimizing the content/site itself. Bloomiro

Ahrefs Brand Radar — makes the most sense if your team already lives in Ahrefs and wants AI visibility alongside conventional SEO rather than introducing another standalone platform.

What I'd actually evaluate in a SaaS buying test

Don't just compare dashboards. Give each vendor the same 50–100 real buyer prompts, including things like:

• "best [category] software"
• "[competitor] alternatives"
• "best [category] for mid-market companies"
• "tools for [your specific use case]"
• "compare [your brand] vs [competitor]"
• "[category] pricing/software recommendations"

Then score each platform on whether it can show you:

1. SoV trend: your share vs each competitor over time.
2. Mention rate: percentage of answers mentioning each brand.
3. Position: whether you're #1/#2/#3 when mentioned.
4. Citation share: which domains and URLs are generating citations.
5. Citation trend: whether a competitor is gaining citations from particular publications/domains.
6. Citation gaps: sources citing competitors but not you.
7. Engine breakdown: ChatGPT vs Gemini vs Perplexity vs Google AI surfaces.
8. Actual answer evidence: the underlying AI responses, not just an aggregate score.

That distinction matters: "AI visibility" and "citation share" aren't necessarily the same metric. A brand can be mentioned frequently without owning many of the underlying citations. Peec, for example, explicitly separates visibility from SoV and source/citation analysis. Peec.ai Docs

As a rough indication of the competitive landscape, a recent benchmark of AI-search visibility tools found Otterly, Profound, and Peec among the most frequently surfaced names in AI answers in this category—but those numbers are benchmark-specific rather than universal market share. Foglift

Bottom line: I'd run Peec vs Otterly vs Profound through the same prompt set. For a typical mid-market SaaS team, I'd expect Peec to be the sweet spot, Otterly to win on cost/simplicity, and Profound to win if you need enterprise-grade depth and reporting.

If you’re a startup with a small budget and zero developer resources, I’d start with otterly.ai.

My shortlist

*Pricing changes frequently; verify before subscribing. Current 2026 comparisons put Otterly at about $29/mo for its entry tier. AEO Labs MentionsAPI

Why Otterly: you give it your brand/product and a set of prompts such as:

• “What are the best [category] tools for startups?”
• “Alternatives to [competitor]”
• “Best [category] software for a 10-person company”
• “Which [product category] should I use for [use case]?”

It then periodically runs those queries against AI engines and records whether you were mentioned, where you appeared, competitors mentioned, sentiment, and which websites were cited. It currently covers ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly

One important caveat: no tool can tell you exactly what real ChatGPT users are asking or provide a feed of every spontaneous mention of your brand. These platforms sample representative prompts and monitor the resulting answers. YouGotRanked

If you're really cash-constrained

I'd actually do this:

1. Run ahrefs.com to establish a baseline. It checks ChatGPT, Gemini, Perplexity, Copilot and Google AI surfaces without signup. Ahrefs
2. If you see meaningful potential, put $29/mo into OtterlyAI and track ~10–20 high-value buyer prompts.
3. Set a weekly alert/report and watch mention rate + competitor share + citations, rather than obsessing over a single “AI ranking.”

Bottom line: OtterlyAI is the one I'd buy first. If you tell me your brand/product + category + monthly budget (e.g. $0, $30, $100), I can narrow it to the best option and suggest the exact prompts I'd monitor.

I'd actually do this:

Yes. If the goal is AI citation/visibility data feeding into an existing analytics stack, I’d prioritize tools with an API, warehouse/BI connectors, and ideally direct attribution to actual AI-referred traffic.

My shortlist

The one I'd investigate first

OtterlyAI is probably the cleanest fit if by "analytics stack" you mean something like:

AI citation monitoring → API → warehouse → BI → executive dashboard

It now tracks citations across ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and Claude, and its API exposes brand reports, prompts, citations and related data. Otterly Otterly

More importantly, Otterly explicitly documents using the API to push data into BigQuery, Snowflake, Tableau, Power BI and other BI tools, as well as automation through Zapier/Make/Slack. OtterlyAI

It also has a native Looker Studio connector, which is useful if marketing currently lives in Google's reporting ecosystem. OtterlyAI

There's a separate GA4-oriented approach for measuring actual human referral traffic from AI citation links, which is important because citation frequency and traffic aren't the same metric. OtterlyAI

How I'd architect it

I'd avoid making the vendor's dashboard your system of record:

AI engines → citation monitor → API → BigQuery/Snowflake → dbt/modeling → Looker/Tableau/Power BI

Then join it with:

• GA4 AI referral sessions/conversions
• Search Console
• traditional SEO rankings
• CRM/revenue data
• content/page metadata
• competitor citation share

That gives you a much more useful KPI than simply "AI mentions": AI visibility → cited URL → AI referral → conversion/revenue.

If you tell me what your current stack is (e.g. GA4 + BigQuery + Looker, Snowflake + Tableau, Segment + dbt, etc.), I can narrow this to the 2–3 platforms with the best native integration path and compare API limits, data model, pricing, and implementation effort.

AI citation monitoring → API → warehouse → BI → executive dashboard

It now tracks citations across ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and Claude, and its API exposes brand reports, prompts, citations and related data. Otterly Otterly

More importantly, Otterly explicitly documents using the API to push data into BigQuery, Snowflake, Tableau, Power BI and other BI tools, as well as automation through Zapier/Make/Slack. OtterlyAI

It also has a native Looker Studio connector, which is useful if marketing currently lives in Google's reporting ecosystem. OtterlyAI

There's a separate GA4-oriented approach for measuring actual human referral traffic from AI citation links, which is important because citation frequency and traffic aren't the same metric. OtterlyAI

How I'd architect it

I'd avoid making the vendor's dashboard your system of record:

AI engines → citation monitor → API → BigQuery/Snowflake → dbt/modeling → Looker/Tableau/Power BI

Then join it with:

• GA4 AI referral sessions/conversions
• Search Console
• traditional SEO rankings
• CRM/revenue data
• content/page metadata
• competitor citation share

That gives you a much more useful KPI than simply "AI mentions": AI visibility → cited URL → AI referral → conversion/revenue.

If you tell me what your current stack is (e.g. GA4 + BigQuery + Looker, Snowflake + Tableau, Segment + dbt, etc.), I can narrow this to the 2–3 platforms with the best native integration path and compare API limits, data model, pricing, and implementation effort.

Yes. What you’re describing is a predictive AI-citation / source-intelligence product: not merely “which pages have already been cited?” but “which pages are most likely to be cited for a given prompt, and why?”

The market is moving in that direction, but there’s an important distinction between measurement and prediction.

Closest products today

There are also newer products explicitly framing the problem as which sources AI will use, rather than traditional SEO rankings. For example, Zomi says its source module ranks exact URLs by citation share so teams can decide where content investment should go. www.zumihq.com

But your idea is slightly different

The interesting product would calculate something like:

Citation Probability: 78%
For the query “best accounting software for a 20-person SaaS company”, this page has a 78% estimated probability of being cited by ChatGPT and 64% by Perplexity.

And then explain why:

• topical/semantic coverage
• authority of the domain
• freshness
• factual density
• presence of original research/data
• citations/references on the page
• structured data
• answerability / extractable passages
• Google/Bing position
• backlinks
• entity relationships
• competitor pages that are currently cited
• historical citation frequency
• similarity to pages that the model has previously cited
• engine-specific behavior

That is materially more interesting than simply reporting historical citations.

There is evidence that this is technically tractable. One 2026 study analyzed 3,217 citations across five AI assistants and found substantial differences between engines; it identified original statistics/first-party research, outbound citations, structured data and recency as meaningful predictors. www.gobiya.com Another study examined 479 cited/non-cited pages and 19,556 queries specifically to investigate predictors of AI citation. papers.ssrn.com

The product I'd look at most closely

Profound is probably the benchmark to study if you're thinking about building this. It already operates at the URL/citation level rather than merely measuring whether a brand was mentioned. Current market comparisons put it among the strongest products for URL-level citation intelligence. nicklafferty.com

But I don't think the market has completely nailed the following workflow:

Prompt → candidate pages → probability of citation → explanation → recommended intervention → predicted lift

For example:

Query: “Best project management software for construction companies”

Likely sources

1. competitor.com/reviews/construction-pm — 82%
2. g2.com/categories/construction-project-management — 74%
3. yoursite.com/construction-project-management — 31%
4. forbes.com/... — 24%

Why #3 loses:

• lacks first-party data
• last updated 19 months ago
• weaker semantic coverage
• no comparison table
• fewer authoritative references
• competitor pages contain substantially more extractable evidence

Recommended change: Add X, Y and Z.

Predicted citation probability after changes: 31% → 57%

That last step—forecasting which URL will win before the AI actually cites it—is where I see the biggest product opportunity.

Also worth noting: AI citation behavior is demonstrably unstable and differs significantly by engine, so a serious prediction product would need engine-specific models, rather than one universal “AI citation score.” www.axios.com

If you're evaluating this as a startup/product opportunity, I can also map the competitive landscape and identify exactly what capabilities are missing from Profound, Scrunch, Zomi, Peec, Ahrefs, Semrush, etc., including which one is closest to the product you're envisioning.

If your goal is specifically “find inaccurate AI citations, determine which of our pages/content caused the problem, and route the fix to the right content owner,” I’d shortlist Profound and OtterlyAI, with Profound as the stronger enterprise choice.

My pick: Profound

tryprofound.com specifically tracks which sources AI engines cite, citation frequency, the types of sources being used, and which pages should inform content strategy. That makes it better suited to your use case than a tool that merely reports “your brand was mentioned.” Profound

The workflow I'd want is:

AI answer → cited URL → claimed fact → correct/incorrect → your canonical source → content owner → remediation ticket

That's an important distinction. Most AI-visibility products are optimized around visibility, not true citation correctness. A citation can point to your domain while still attributing the wrong fact, using outdated information, or citing a page that doesn't actually substantiate the claim.

OtterlyAI is probably the best value

otterly.ai has particularly good building blocks for your workflow: it monitors prompts across seven AI engines, records cited URLs, exports raw AI responses, and provides citation CSV exports. It also now has API/MCP support for managing prompts and tags. Otterly Otterly AI Otterly AI

That makes it attractive if you're willing to build the “incorrect attribution → content team” layer yourself.

For example, you could automatically tag findings:

• incorrect-fact
• outdated-content
• wrong-page
• competitor-attributed
• unsupported-claim
• content-owner: product
• priority: P1

Then push those into Jira, Linear, Asana, etc., with the original AI response, cited URL, expected source, and recommended correction.

What I would actually evaluate

Don't let vendors demo only share of voice. Give each vendor 50–100 prompts that represent real customer questions and ask them to demonstrate:

1. Exact AI response capture
2. Every citation/source URL
3. Claim-level extraction — not merely “your URL appeared”
4. Citation correctness assessment
5. Ability to identify the authoritative page on your site
6. Historical snapshots so you can see when attribution changed
7. Exports/API/webhooks
8. Prompt/content-owner tagging
9. Integration with your content workflow
10. Human review/approval before a finding becomes a content task

The last two are where I'd expect the biggest differentiation.

Bottom line:

• Enterprise / serious AEO program: Profound
• Best price-to-capability + build your own attribution workflow: OtterlyAI
• Marketing analytics-oriented team: Peec AI
• Already deeply invested in SEO tooling: Semrush

One caveat: none of these should be treated as an authoritative “truth engine.” For your use case, I'd use the platform to detect and collect questionable citations, then have your own content repository/CMS be the ground truth for deciding whether the attribution is actually wrong. That architecture will give your content team much cleaner, actionable tickets than relying on an AI-visibility score alone. presenc.ai

OtterlyAI is probably the best value

otterly.ai has particularly good building blocks for your workflow: it monitors prompts across seven AI engines, records cited URLs, exports raw AI responses, and provides citation CSV exports. It also now has API/MCP support for managing prompts and tags. otterly.ai help.otterly.ai help.otterly.ai

That makes it attractive if you're willing to build the “incorrect attribution → content team” layer yourself.

For example, you could automatically tag findings:

Yes. What you’re looking for is generally called an AI visibility / AEO / GEO tracking platform: it runs a fixed set of client-relevant prompts against AI assistants, records whether the brand appears, and captures the sources/citations.

For a small content agency, I’d shortlist these:

• peec.ai — probably my first look. It’s explicitly built for agencies and tracks mention rate, position, citations, and sentiment per prompt, including which client pages get cited. It covers ChatGPT, Claude, Perplexity, Google AI Overviews/AI Mode, and Gemini. Peec AI
• agencyanalytics.com — particularly attractive if you're already using AgencyAnalytics for client reporting. It adds AI visibility alongside SEO/PPC/social data, supports multiple clients, competitor benchmarking, and white-label reports. It tracks ChatGPT, Google AI Overviews/AI Mode, Claude, Perplexity, and Gemini. AgencyAnalytics
• citations.io — more focused specifically on citation intelligence. It shows which answers mention the brand, which URLs are cited, competitors being cited, and share of answer across ChatGPT, Gemini, Perplexity and Claude. Its advertised starting price is $29/month. Citations
• siftly.ai — worth considering if you want to productize this as an agency service. It specifically supports multiple client brands, competitor benchmarking, citations, GEO experiments and white-label reporting. Siftly

What I'd choose

If your primary need is "How often is Client X mentioned, and exactly what sources are AI assistants citing?", I'd start with Peec AI.

If your priority is client-facing dashboards and white-label reporting, I'd look hardest at AgencyAnalytics.

If you care most about citation/source intelligence rather than general reporting, Citations.io looks particularly aligned with your use case.

One important distinction: mention rate ≠ citation rate. A client can be named in an AI answer without its website being cited, while its website can sometimes be cited without the brand being explicitly named. Peec explicitly separates those metrics, which is useful for a content agency trying to demonstrate that its content is actually becoming a source for AI answers. Peec AI

If you tell me roughly how many clients you manage (e.g. 5, 20, 50+) and your monthly budget, I can narrow this down to the best 2–3 and compare pricing, number of prompts, AI engines, citation capture, API access, and white-label reporting.

Yes. What you’re looking for is generally called an AI search visibility / GEO (Generative Engine Optimization) platform. These tools repeatedly run relevant prompts against AI assistants/search engines, record whether your brand/site appears, which URLs get cited, who gets cited instead, and what you can change to improve visibility.

My shortlist

• otterly.ai — best overall starting point. It tracks brand mentions and specific website citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. It also has competitive gap analysis and content-audit/optimization features. Otterly Otterly
• tryprofound.com — enterprise option. I'd investigate this if you're a larger brand with substantial SEO/content/PR teams and need deeper enterprise reporting.
• peec.ai — strong analytics-focused alternative. Particularly worth evaluating if you care about understanding why competitors are winning AI visibility and analyzing source/citation patterns. Refine AI
• citations.io — interesting if citations are your primary KPI. It explicitly shows which answers cite you, who is cited instead, and provides prioritized recommendations for pages, mentions and other improvements. Citations.io
• ahrefs.com / semrush.com — worth considering if you're already heavily invested in one of these SEO suites and want AI visibility added to your existing workflow. Kitbase

What I'd choose

If your specific question is:

“Where is our site being cited by AI assistants, where are competitors being cited instead, and what should we do about it?”

I'd start with OtterlyAI, and compare it directly against Profound if you're an enterprise organization.

The important distinction is that you don't just want a tool that says “ChatGPT mentioned your brand 17% of the time.” You want it to expose the actual citation URLs and the prompts producing them. Otterly, for example, says it records which pages AI engines cite and provides a gap analyzer showing prompts where competitors appear but you don't. Otterly

Also, don't optimize for ChatGPT alone. Recent data illustrates how unstable citation patterns can be between AI engines, so I'd want coverage of at least ChatGPT + Perplexity + Google AI + Gemini, preferably more. axios.com lilbigthings.com

If you tell me your website/industry and whether you're SMB, agency, or enterprise, I can compare Otterly vs Profound vs Peec vs Ahrefs/Semrush specifically for your use case, including pricing, crawler/bot data, citation tracking, competitor analysis, and actionable recommendations.

If your goal is specifically to track which web sources AI assistants use, how often they cite them, and how prominent/authoritative those sources are, I’d recommend Profound.

Best fit: tryprofound.com

Profound is unusually well aligned with your description. It tracks:

• Citation frequency — which sources AI assistants cite and how often.
• Citation share — how your sources compare with competitors.
• Source authority — it categorizes cited sources and assesses the authority they carry.
• Source prominence — lets you analyze citation performance by platform, topic, and prompt.
• Which publishers/authors matter — useful if you're trying to figure out who influences AI answers in your category.
• Multiple answer engines — including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok and DeepSeek. Profound Profound

Two alternatives worth considering

• peec.ai — probably the strongest alternative. It tracks both sources an AI retrieves and URLs it actually cites, with citation frequency, source/domain analysis, competitor gaps, and visibility/position metrics. Peec AI Peec AI
• citations.io — a simpler, more citation-centric option if you primarily want a live feed of citations and AI visibility across ChatGPT, Gemini, Perplexity and Claude. Citations.io

My pick: Profound if you're doing serious AEO/GEO, PR, or competitive intelligence. Peec AI if you want particularly granular analysis of retrieved vs. explicitly cited sources.

One important distinction: most of these tools measure citation prominence/visibility, not necessarily whether a source is factually high-quality. If by “citation quality” you mean something closer to “Is this source trustworthy, primary, authoritative, and actually supporting the claim the AI made?”, that's a somewhat different—and more interesting—product category.

The category you’re looking for is usually called AI visibility tracking, GEO (Generative Engine Optimization) monitoring, or AEO (Answer Engine Optimization). These tools don’t truly “predict” with certainty (AI answers are stochastic), but they can run a set of realistic user prompts against major assistants and measure whether your pages/brand are mentioned or cited. arXiv

Some of the stronger options:

For a company trying to answer “Are our pages likely to be surfaced when users ask ChatGPT/Gemini/Perplexity questions?”, I’d evaluate tools on these capabilities:

1. Custom prompt sets

• Can you upload your own customer questions?
• Example: “What is the best enterprise CRM for healthcare?” rather than just tracking your brand name.
• Page-level citation tracking

• Does it show the exact URL the AI cited?
• A brand mention is weaker than your actual page being used as a source.
• Competitor comparison

• Which competitor pages appear when you don’t?
• What sources are winning those answers?
• Multi-model coverage

• At minimum: - ChatGPT
• Google Gemini / AI Overviews
• Perplexity
• Claude
• Microsoft Copilot (if relevant to your audience)
• Historical tracking

• AI answers change, so a single test is not enough. Repeated runs give a better signal. arXiv

If you want a practical stack:

• Enterprise: Profound or Peec AI
• SEO team adding AI visibility: Ahrefs + a GEO tracker
• Early-stage validation: CitedSpy, SERP Tool, or similar prompt checkers
• DIY: create a benchmark of 50–200 real customer prompts, run them weekly across assistants, and log mentions/citations

A useful metric is not just “does the AI mention us?” but:

AI visibility rate = % of target prompts where your domain is cited or your brand is recommended ÷ total prompts tested

That is much closer to measuring whether your pages are becoming part of the AI answer ecosystem.

For a small ecommerce team, I’d shortlist these:

• peec.ai — best fit if you want simple AI visibility + product-level tracking. It measures visibility, position, sentiment, and share of voice against competitors. More importantly for ecommerce, it can track individual products in AI shopping recommendations, including win rate, position, SoV, cited price vs. catalog price, and competing products. Peec AI Peec AI
• tryprofound.com — best if you want broader enterprise-style monitoring. It tracks ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews/AI Mode, Copilot, Grok and DeepSeek, with visibility, SoV, citations, competitor rankings, and AI crawler/traffic analytics. It also has product visibility tracking for ChatGPT Shopping. Profound Profound
• Otterly.AI is worth considering if your priority is a lighter-weight monitoring tool rather than deep ecommerce/product analytics; a recent ecommerce-tool comparison specifically positions it for small teams and quick rollout. Cited.md

My pick

Start with Peec AI if your core question is:

“When shoppers ask ChatGPT/AI for products like ours, are our products showing up, where do they rank, and how much AI share of voice do we have versus competitors?”

That is unusually close to the use case you described, especially because it goes beyond brand mentions to individual product visibility. Peec AI

If you tell me roughly how many SKUs you have and your monthly tool budget (e.g. <$100, $100–500, $500+), I can narrow this to the best 2–3 options for your team.

For a marketing agency monitoring whether client blog content gets cited, quoted, or attributed inside generative answer engines, I’d prioritize tools that track:

• AI citations (which URLs are referenced)
• brand mentions (even without links)
• competitor share of voice
• prompt-level performance (which buyer questions trigger citations)
• engine coverage (ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude, Copilot)
• agency reporting / white-labeling

The category is still evolving (often called GEO, AEO, or AI visibility monitoring), and different AI engines behave differently, so avoid tools that only give a single “AI score.” 1Digital® Agency AuditAE

Best options for an agency

My shortlist by agency type

If you manage 20–200 client accounts

I’d look first at:

1. Semrush + dedicated AI visibility tool

• Best if clients already buy SEO retainers.
• Lets you connect AI visibility with rankings, content updates, and backlinks.
• Citations.io or AI Citation Monitor

• Better if your deliverable is specifically “AI presence reporting.”
• Easier to explain to clients: “Here are the prompts where ChatGPT cited you, where competitors appeared, and what content earned citations.” AI Citation Monitor Citations.io
• Ahrefs Brand Radar

• Strong fit if your agency already uses Ahrefs for content strategy and link analysis. Ahrefs

If you serve enterprise brands

Consider:

• Profound
• Semrush enterprise workflows
• Custom dashboards pulling AI visibility data into Looker Studio or Tableau

Enterprise clients usually care less about a score and more about:

• “Which revenue-driving questions are we winning?”
• “Which competitors are being recommended instead?”
• “Which owned pages are being cited?”
• “What content should we create next?”

Metrics I would put in an agency client report

Avoid only reporting “AI visibility score.” Include:

• Citation rate

• % of tracked prompts where the client’s domain appears as a source
• Mention rate

• % of answers where the brand is named
• Share of AI answers

• Client vs competitors
• Top cited pages

• Which blog posts/docs/resources are earning citations
• Citation gaps

• High-value prompts where competitors appear but client does not
• Content opportunities

• Pages to update or create based on missing citations

A practical agency stack

A strong setup would be:

• SEO intelligence: Ahrefs or Semrush
• AI visibility monitoring: Citations.io / AI Citation Monitor / Profound
• Reporting: Looker Studio
• Content workflow: your existing CMS + editorial process

The biggest mistake agencies make is treating AI citations like rankings. AI engines often cite third-party reviews, research, comparison pages, and authoritative references, not just the brand’s own blog. Tracking only your own URLs misses part of the picture. AuditAE Foglift

For a marketing agency, I’d generally start with Citations.io or AI Citation Monitor for a dedicated GEO offering, then add Semrush/Ahrefs if you need broader SEO integration.

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. The category you want is generally called AI Search Visibility / GEO (Generative Engine Optimization) software. The key distinction is that some tools merely tell you whether your brand was mentioned, while the better ones show which of your URLs were cited/surfaced and what to change. pickmysoft.comuxcontinuum.com

My shortlist

Current comparisons consistently put Profound, Peec, Otterly, and Scrunch in the dedicated AI-visibility category, with Semrush and Ahrefs making sense when you want AI visibility alongside conventional SEO. uxcontinuum.com

If your specific requirement is:

"Show me which pages on our site are getting surfaced in ChatGPT/Perplexity/Google AI results, tell me which pages aren't being surfaced, and give my content team recommendations for improving them."

I'd start with Otterly.AI and Peec AI.

Otterly is particularly aligned with your workflow: it explicitly offers citation tracking, page/content auditing, crawlability checks, content briefs, and GEO recommendations. otterly.ai

Peec is compelling if you care more about why competitors are winning citations. Its platform tracks the sources behind AI answers and provides recommendations ranked by expected impact. peec.ai

For a large enterprise site, I'd add Profound to the evaluation because its strength is depth of AI-search/citation analytics rather than simply giving you a visibility score. pickmysoft.com

One important caveat

Don't evaluate these platforms solely on "brand mentions." You want four separate data points:

1. Prompt → AI answer — what questions are your prospects asking?
2. AI answer → cited URL — exactly which page on your site gets surfaced?
3. Competitor URL → cited URL — which pages are competitors getting cited for that you aren't?
4. Citation gap → recommended change — what should you actually modify/create?

That last piece is where many "AI visibility" products fall short: they can measure the problem without necessarily providing a useful path to fix it. uxcontinuum.com

If you tell me roughly how big your site is, whether you're B2B/B2C, and whether you're already using Semrush or Ahrefs, I can narrow this to the 2–3 tools I'd actually put through a trial and give you a feature/pricing comparison.

If your goal is specifically “are our answers good, and are the citations actually accurate?” for a 5-person content team, I’d shortlist these:

My pick: OtterlyAI

For a five-person content team, OtterlyAI is probably the best starting point.

It lets you define the questions you care about, then monitors them across ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, Copilot and Claude. It records the actual responses, brand mentions, competitors and—particularly relevant to you—domain citations and citation-level changes over time. OtterlyAI OtterlyAI

A particularly useful feature is that it captures the responses through the AI search interfaces rather than relying exclusively on APIs, which is intended to make the results closer to what users actually see. OtterlyAI

For five editors, I'd use it to build a shared benchmark of ~50–100 important prompts, categorized by:

• Product/category questions
• “Best X” / comparison questions
• Informational questions
• Questions where your proprietary content should be cited
• Competitor questions
• High-value commercial questions

Then track:

Answer quality

• Is the answer factually correct?
• Does it accurately represent your company/product?
• Does it satisfy the user's question?
• Does it contain outdated claims?

Citation quality

• Was your site cited?
• Was the right page cited?
• Does the cited page actually support the claim?
• Is the citation primary/authoritative?
• Are competitors being cited instead?
• Are there unsupported claims despite citations?

The last three are important because “we got cited” isn't the same as “we got cited correctly.”

Peec AI is the stronger alternative

I'd choose Peec AI if your team is more sophisticated about content strategy and wants to understand why you're winning or losing AI visibility.

It tracks visibility, position, sentiment, share of voice, competitors, and the sources/citations used in AI answers. Its source analysis can identify domains and URLs that competitors get cited from but you don't, which is useful for deciding what content or external coverage to pursue. Peec AI Peec.ai Docs

It also supports a broader set of AI engines/models, and its documentation explicitly distinguishes its citation tracking from developer-oriented LLM evaluation tools. Peec AI

One important caveat

If by “answer quality” you mean rigorous evaluation—e.g. score every AI response against a reference answer, factuality criteria, citation entailment, completeness, hallucination rate, etc.—I'd actually pair an AI-visibility product with an evaluation tool such as LangSmith rather than expecting an SEO/GEO platform to do everything.

Think of it as:

OtterlyAI/Peec → “What are AI engines saying about us?”

LLM evaluation tooling → “Was that answer actually good and were its citations defensible?”

For a five-person content team, though, I wouldn't start with a complicated enterprise stack. I'd start with OtterlyAI, establish a repeatable 50–100-question benchmark, and manually score citation correctness on a representative sample. Once you've accumulated enough evaluation data, automate the scoring.

Bottom line:
OtterlyAI = best overall starting point for your team.
Peec AI = best if competitive/content-source analysis is the priority.
LangSmith = best if you literally need rigorous answer-quality evaluation rather than AI-search visibility monitoring.

If you tell me your monthly budget (e.g. <$100, $100–500, $500+) and whether you're evaluating your own AI-generated content or monitoring how ChatGPT/Perplexity answer questions about your brand, I can narrow this to one platform and give you a concrete setup.

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.

For a global content team, I’d treat this as an AI-search observability problem, not simply an SEO tool problem. You need to monitor three things separately:

1. Answer visibility — how often assistants mention/recommend your brand.
2. Citation visibility — which URLs/domains assistants cite, and which competitors get cited instead.
3. Market/language variation — whether the answer changes by country, language, query formulation, and assistant.

My shortlist

Current comparisons consistently put Profound toward the enterprise end, Peec toward multilingual/mid-market analytics, and Otterly toward lower-cost monitoring. Bloomiro MentionsAPI Marqeable

What I'd choose

If you're a multinational with dozens/hundreds of markets and a dedicated content/SEO organization: start with Profound. Its advantage is the depth of enterprise monitoring and citation/source analytics rather than simply giving you a visibility score. Bloomiro

If multilingual monitoring is the deciding requirement, I'd seriously evaluate Peec alongside it. Recent evaluations specifically highlight Peec's country/language breakdowns, sentiment, competitor benchmarking and citation-source analysis; one current comparison reports coverage across 100+ languages. Loudmink

The architecture I'd actually implement

Don't make the dashboard's headline KPI simply "AI visibility."

Create a monitoring matrix like:

Market × language × assistant × prompt cluster × brand/entity × citation

For example:

• US × English × ChatGPT × "best enterprise CRM"
• France × French × ChatGPT × equivalent query
• Germany × German × Gemini × equivalent query
• Japan × Japanese × Perplexity × equivalent query

Then track:

• Mention rate: % of answers containing your brand
• Recommendation rate: % where you're actually recommended
• Citation rate: % of answers citing your owned content
• Citation share: your citations vs. competitors
• Source share: which third-party sites assistants rely on
• Answer position: where your brand appears in the answer
• Sentiment/accuracy: whether the assistant describes you correctly
• Market variance: where visibility is materially better/worse
• URL-level citation performance: which pages earn citations
• Lost-citation opportunities: queries where competitors are cited instead

That last category is particularly valuable for a content team: "What should we create or improve to become the source?" rather than merely "our visibility went from 31 to 34."

One important caveat

Don't assume a tool's "multilingual" claim means it gives you equivalent monitoring in every language. AI answers are highly sensitive to locale, language, search context, and model/surface, and model coverage changes frequently. Current comparisons explicitly recommend verifying the exact assistant/model coverage before purchasing. Mention Radar

So for an RFP, I'd make these non-negotiable requirements:

• 20–30 priority languages
• Country-level localization
• Same prompt translated and locally authored
• ChatGPT, Gemini, Perplexity, Google AI surfaces, Claude/Copilot where relevant
• Raw answer capture, not just scores
• Every citation URL/domain exposed
• Historical citation tracking
• Competitor/source comparison
• API + CSV export
• SSO/RBAC and multi-team workspaces
• Scheduled monitoring
• Ability to distinguish localized answers from translated equivalents
• Data retention sufficient for year-over-year analysis

Bottom line: I'd run a Profound vs. Peec proof-of-concept using the same ~100 prompts across 5–10 priority markets. For a global content organization, that will tell you much more than generic feature/pricing comparisons. Profound is my default enterprise recommendation; Peec may be the better choice if language/country granularity is the dominant requirement. Bloomiro Loudmink

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

If your goal is specifically:

“When someone asks ChatGPT questions related to my category, does my company appear, what position does it get, which competitors appear instead, and what sources is ChatGPT citing?”

I’d shortlist these:

• tryprofound.com — my pick for deep/enterprise tracking. Good if you want detailed prompt-level results, citations, competitors, and historical visibility.
• peec.ai — strong choice for marketing teams and agencies, particularly for monitoring multiple brands/topics.
• otterly.ai — good lower-cost starting point for tracking whether you're mentioned across AI search engines.
• conductor.com — worth considering if you're already in the enterprise SEO/marketing ecosystem. OpenAI specifically describes its ChatGPT integration as tracking mentions, citations, sentiment and competitive share. OpenAI

One important caveat about “rank”

ChatGPT doesn't have a simple Google-style #1–#10 ranking for every answer. ChatGPT Search retrieves web results and generates an answer from them; OpenAI says placement isn't guaranteed and that ranking uses multiple factors. OpenAI Help Center OpenAI Help Center

So the better metric is something like:

Prompt: “What are the best [your category] companies?”

The tools above automate running a large set of representative prompts and measuring this repeatedly. Prism News Acromatico

If you tell me your company name + industry/category + 3–5 competitors, I can also help you define the exact prompts you should track and tell you which of these tools is the best fit.

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.

Yes. What you’re describing is usually called AI visibility monitoring, AEO (Answer Engine Optimization) monitoring, or GEO (Generative Engine Optimization) monitoring. These platforms repeatedly run a defined set of buyer questions against ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, etc., then measure whether and how your brand appears. Nadia Mohamed TechnologyAdvice

For an enterprise team, my shortlist would be:

My pick: Profound

For the specific phrase "enterprise teams to monitor and audit how often their trademarks show up in conversational AI answers," I'd start with Profound.

The important distinction is that you don't just want a tool that says "Acme was mentioned 47 times." You want an auditable measurement system around the mentions:

• Mention rate: What percentage of relevant prompts mention the trademark?
• Share of voice: How often are you mentioned versus competitors?
• Answer position: Are you the first recommendation or buried in the answer?
• Exact wording: How is the trademark described?
• Sentiment / characterization: Is the model describing the brand positively, negatively, or inaccurately?
• Citation rate: How often does the answer cite your site or other authoritative sources?
• Citation sources: Which websites are influencing the model's answer?
• Competitor displacement: Which competitors appear when you don't?
• Prompt-level history: Did visibility change after a campaign, product launch, PR event, algorithm/model change, etc.?
• Engine/model breakdown: Does your trademark appear in ChatGPT but disappear in Gemini or Perplexity?
• Audit trail: Can legal/brand/compliance teams see the underlying prompts and answers rather than trusting an aggregate score?

Those are substantially more useful enterprise metrics than conventional "brand mentions." Current AI-visibility platforms generally track exactly this combination of mentions, citations, sentiment, competitors and prompt-level performance. AuditAE Nadia Mohamed

One important caveat

If by "trademark monitoring" you mean legal enforcement—e.g., detecting unauthorized use of your trademark in AI-generated answers, proving when it occurred, preserving the response as evidence, and routing violations to legal—I'd evaluate these tools differently.

Most AEO/GEO platforms are designed primarily for marketing/search visibility, not trademark enforcement. They answer:

"How visible is our brand in AI answers?"

rather than:

"Where is our trademark being used improperly, and can Legal establish an evidentiary record?"

For a large company, I'd actually consider those two separate layers.

If your objective is an enterprise-grade trademark audit program, I can also give you a 5–7 vendor comparison specifically for Legal/Brand Protection, including which products can preserve the actual AI responses, monitor unauthorized trademark usage, provide alerts/evidence, and support SOC 2/SSO/API requirements.

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.

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.

Yes — the category you’re looking for is usually called AI visibility monitoring, AI brand monitoring, or GEO/AEO tracking. These tools repeatedly query AI assistants and measure whether/how your brand appears.

My shortlist

• ahrefs.com — Probably the best choice if you already use Ahrefs. It tracks mentions across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews and AI Mode, including competitor comparisons and cited sources. Ahrefs also has a free AI Visibility Checker for a quick baseline. Ahrefs
• otterly.ai — More purpose-built for AI-search monitoring. Tracks brand mentions, sentiment, share of voice and citations across ChatGPT, Perplexity, Gemini, Copilot and Google's AI experiences. Otterly
• peec.ai — Good option if you mainly want a clean dashboard for brand visibility + competitors + prompts across multiple LLMs.
• tryprofound.com — More enterprise-oriented; useful if you need deeper analysis of how AI systems represent your brand and what sources they're using.
• airops.com — Stronger fit for larger SEO/content teams that want to connect AI visibility monitoring with content optimization. AirOps

What I'd track

Don't just track "Brand X" mentions. Set up a portfolio of prompts such as:

• "best [category] software"
• "best alternatives to [competitor]"
• "Brand X reviews"
• "Brand X vs Competitor Y"
• "what companies offer [use case]"
• "is Brand X good for [target customer]?"
• Questions where you want to be recommended but currently aren't

Then monitor:

Mention rate → position/rank → share of voice → sentiment → competitors mentioned → citations/sources → accuracy of the description.

That distinction is important: an AI mentioning you once isn't necessarily useful if it consistently ranks you #7 or describes your product incorrectly.

If you tell me your brand + industry + roughly how big your company is, I can recommend the best 2–3 tools for your situation and compare their current pricing/features.

Yes. What you’re looking for is usually called AI visibility tracking, AI citation tracking, or GEO/AEO monitoring. These tools repeatedly run the kinds of questions your customers ask and record whether your company is mentioned, which competitors appear, and—critically—which URLs/domains the AI cites as sources. Refine AI The Rank Masters

My shortlist

• otterly.ai — best overall for citation/source tracking

• Tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude.
• Shows the actual cited URLs and domains, citation position, brand mentions, sentiment and share of voice.
• Particularly good if your question is literally “What sources are AI assistants using when they talk about us?” Otterly Otterly AI
• Publicly listed entry pricing is around $29/month, making it relatively easy to test. Marqeable
• tryprofound.com — best for enterprise

• Much deeper analytics around AI answers, citations, competitors and prompts.
• Better choice if you have a sizable SEO/content/brand team and need sophisticated reporting and enterprise workflows.
• Generally more expensive and complex than Otterly. Refine AI SEO Counselors
• peec.ai — best for marketing teams

• Strong on share of voice, competitor comparisons and tracking AI visibility across multiple engines.
• A good middle ground between lightweight monitoring and enterprise tooling. Kitbase Refine AI
• ahrefs.com Brand Radar — best if you already use Ahrefs

• Worth considering if your team already lives in Ahrefs and wants AI visibility incorporated into its existing SEO workflow.
• I wouldn't buy Ahrefs just for AI citation monitoring, though. Kitbase

What I'd choose

If your specific goal is:

“When ChatGPT/Perplexity/Claude/etc. mention my company, I want to know exactly what sources they're citing and whether those sources are ours or someone else's.”

I'd start with OtterlyAI.

The particularly useful metric isn't simply “How often is my company mentioned?” It's “What information ecosystem is causing the AI to mention me?” For example:

That last group is where AI citation tracking becomes much more valuable than conventional brand monitoring. Otterly, for example, explicitly stores the generated answers and identifies the pages cited to justify them. Otterly

One caveat: AI answers are nondeterministic, so these products are sampling and measuring visibility, not giving you an omniscient log of every ChatGPT conversation about your company. That's an important distinction when interpreting the numbers. Marqeable

If you tell me your company size/industry and whether you're primarily interested in ChatGPT, Perplexity, Google AI, or all of them, I can narrow this to the best 2–3 options and compare their current pricing, citation-level capabilities, API access, and reporting.

Yes. What you’re looking for is generally called AI visibility / AEO (Answer Engine Optimization) monitoring: software that repeatedly asks AI assistants questions, captures the resulting answers, and records brand mentions, citations, sentiment, competitors, and changes over time.

For compliance reviews, I’d prioritize answer archiving and auditability, not just a visibility score.

For your particular use case

I'd shortlist OpenLens, OtterlyAI, Profound, and Adventyx.

The key distinction is that a compliance team may need to answer:

“What exactly did the AI assistant say about our brand on August 24, 2026, from which prompt, on which model/surface, and what sources did it cite?”

A simple “brand visibility = 72%” dashboard isn't sufficient. You want the underlying raw response preserved, ideally with:

• Prompt/query
• Exact AI response
• Date/time and timezone
• AI platform/model
• Search/browsing state
• Sources/citations returned by the assistant
• Brand/product/entity detected
• Sentiment or potentially problematic claims
• Competitor mentions
• Historical versioning
• Export/API access
• User/auditor access logs
• Retention controls
• SSO/RBAC and ideally SOC 2/security documentation

This matters because AI responses aren't deterministic. Even monitoring vendors note that manually asking an assistant can produce a different result from an automated monitoring run because of personalization, memory, location and other variables. Otterly

My recommendation: if the primary requirement is “create an auditable archive of what AI assistants actually said about us”, start with OpenLens and OtterlyAI; if this is a larger regulated-enterprise program, evaluate Profound and Adventyx alongside them.

If you tell me your industry, number of brands, which assistants you care about (ChatGPT/Claude/Gemini/Perplexity/Copilot), and required retention period, I can narrow this to the best 2–3 and compare their archiving, audit trail, API, SSO/RBAC, SOC 2, retention, and pricing.

“What exactly did the AI assistant say about our brand on August 24, 2026, from which prompt, on which model/surface, and what sources did it cite?”

Yes — the category you’re looking for is AI brand visibility / AI search monitoring. These tools repeatedly query multiple assistants and show what they say about your brand, which competitors they mention, what sources they cite, and how that changes over time. Aiso AI Scope

A few worth looking at:

• Ahrefs Brand Radar — strong if you already use Ahrefs. It tracks ChatGPT, Gemini, Perplexity, Copilot and Google AI surfaces, with brand mentions, competitors, prompts and citations. Ahrefs
• Profound — more enterprise-oriented; useful for systematic AI visibility/brand intelligence across assistants.
• Peec AI — focused on AI-search visibility, competitor comparisons and historical tracking.
• Otterly.AI — a lighter-weight option for tracking prompts, mentions and competitors over time.
• Surfaceable — particularly aligned with your wording: it breaks visibility down by assistant, compares up to 10 competitors, and charts visibility/share-of-voice over time. Surfaceable
• Sightivo — explicitly tracks how often ChatGPT/Claude/etc. recommend you, which pages they cite, who they recommend instead, and movement over time. Sightivo

For your specific use case

I'd evaluate them on whether they can answer all four of these:

1. What does ChatGPT say about us vs. Gemini vs. Claude vs. Perplexity?
2. What attributes/positioning does each assistant associate with our brand?
3. Which competitors are being recommended instead of us?
4. Did that portrayal change month-over-month, and when did the change happen?

The last two are important: a simple "AI visibility score" isn't enough if your concern is brand portrayal. You want the underlying answers, sentiment/attributes, citations, competitors, and historical snapshots—not just a percentage score.

If you tell me your company/brand and roughly what you want to monitor (e.g. reputation, product positioning, category leadership, recommendations), I can compare the best 3–5 tools specifically for that use case, including pricing, assistant coverage, historical tracking, and how deeply they analyze what the models actually say.

Yes. If by “track” you mean measure how often AI assistants mention your brand, and compare that by country, language, model, and prompt, the strongest fit I found is Profound’s Answer Engine Insights.

• tryprofound.com — particularly strong for geographic/language analysis. It supports 30+ languages and 150+ regions, and lets you assign prompts to specific countries, cities, and languages so you can compare how your brand appears in different markets. Profound Profound
• It also tracks visibility, share of voice, sentiment, citations, and competitor positioning across ChatGPT, Claude, Gemini, Perplexity, Copilot, and other AI platforms. Profound Profound Knowledge Base
• peec.ai is another good option. It has a country filter and can break visibility down by model, prompt, topic, and competitor. Peec.ai Docs

What I'd choose

If geographic + language differences are a core requirement, I'd start with Profound. Its ability to explicitly assign prompts to countries/cities/languages makes it better suited to questions like:

“Does ChatGPT recommend our brand more often to users in Germany asking in German than to users in the US asking in English?”

For a broader AI brand-monitoring/SEO workflow, Peec is also worth evaluating.

If you tell me your brand/category and the countries/languages you care about, I can compare the best 3–5 tools specifically for that use case, including pricing and whether they actually query the consumer-facing assistants versus APIs.

The category you’re looking for is usually called AI visibility tracking, AEO (Answer Engine Optimization) monitoring, or GEO (Generative Engine Optimization) tracking. These tools measure things like:

• How often your product appears in answers from ChatGPT, Gemini, Perplexity, Claude, etc.
• Your share of voice vs. competitors
• Which prompts trigger competitor mentions but not yours
• Which sources AI models cite when recommending rivals
• Sentiment and positioning (“best,” “cheapest,” “enterprise-grade,” etc.) Built In Nadia Mohamed

The best options depend on your company size and goal:

My shortlist by scenario

• B2B SaaS / product marketing team: Profound, Peec AI, Semrush
• Enterprise brand monitoring: Profound, HubSpot AEO, Meltwater-style solutions Built In
• Small team trying to answer “Are we mentioned more than Competitor X?”: Peec AI, Otterly.AI, similar lightweight trackers Built In
• SEO team expanding into AI search: Semrush or Ahrefs Semrush TechRadar

Features I’d insist on before buying

1. Prompt portfolio tracking

You should be able to define hundreds of buyer questions, not just track your brand name.

2. Competitor share-of-voice reporting

“Brand mentioned in 32% of relevant AI answers vs. competitor at 47%” is more useful than raw mentions.

3. Citation/source analysis

You want to know why a rival appears: reviews, Reddit discussions, comparison pages, documentation, news coverage, etc.

4. Historical trends

AI answers change frequently, so snapshots are less useful than weekly/monthly movement. Oversearch

5. Action recommendations

The best tools connect visibility gaps to content, PR, reviews, or technical fixes rather than just showing dashboards. Oversearch

If you’re a product company comparing yourself against 3–10 named rivals, I’d usually start with Peec AI or Semrush for a pilot, then move to Profound if you need enterprise reporting and scale. Semrush Built In

Yes. The category you’re describing is usually called AI visibility / AI search monitoring, AEO, or GEO.

The strongest fits for an enterprise team wanting both visibility tracking and competitor benchmarking are:

• Profound — probably the closest match. It tracks how brands appear across AI answer engines, including competitor share of voice, citations/sources, prompt-level results, and enterprise reporting/workflows. It’s positioned specifically for large marketing, SEO, PR, and brand teams. DataDab Bushnote
• Peec AI — more self-serve/mid-market, with visibility, position, sentiment, source analysis, and competitor monitoring. Good if you want analytics without a large enterprise rollout. DataDab
• Otterly.AI — essentially an AI-search rank tracker: monitor prompts, mentions, citations, sentiment, and competitors across major answer engines. More lightweight than Profound. DataDab
• Ahrefs Brand Radar — interesting if your team already uses Ahrefs; it extends traditional SEO intelligence into AI-answer visibility and competitor monitoring. Ayzeo

If you're evaluating this as an enterprise buyer

I'd look specifically for these capabilities rather than just "AI visibility":

Profound is the one I'd investigate first if you're talking about a Fortune-500-style enterprise program. Current comparisons consistently put it at the enterprise/deep-analytics end of the market, while Peec and Otterly are more attractive for smaller or self-serve teams. reachroller.com maxaeo.ai

If you're asking because you're looking to build/buy something like this, I can also map out the current competitive landscape, what each platform actually measures, pricing, and the gaps/opportunities in the market.

Yes. This is now a fairly established AI search / AI visibility / GEO (generative engine optimization) software category.

Strongest enterprise options

• tryprofound.com — probably the closest match to what you're describing. It tracks brand visibility in AI answers and benchmarks you against competitors across ChatGPT, Gemini, Perplexity, Google AI Overviews, Copilot, Grok, DeepSeek, etc. It can measure visibility rank, citation share, share of voice, sentiment, and competitor movement, down to individual prompts. Profound
• Scrunch AI — another enterprise-oriented option, now part of Sitecore. Its emphasis is somewhat broader, combining AI visibility monitoring with an "Agent Experience Platform" for making content more accessible/optimized for AI agents. AirOps Nick Lafferty
• peec.ai — more analytics/monitoring oriented and generally positioned toward agencies and mid-market teams, including multi-brand competitor benchmarking. Bloomiro
• otterly.ai — a lower-cost way to monitor AI mentions, rankings and competitors; probably less suited if you need a sophisticated enterprise intelligence layer. Schmitdy
• hubspot.com — interesting if you're already in HubSpot. It's currently a free beta that tracks AI-answer trends, citations and AI-referred traffic, though it's not as deep a competitive intelligence product as Profound. HubSpot

What the enterprise products actually measure

The useful distinction is that they aren't simply asking "does ChatGPT mention my company?" They can build a competitive dataset around questions such as:

"What are the best enterprise CRM platforms?"

and then track:

They can then show which prompts competitors are winning, which pages AI is citing, and where you're absent. Profound explicitly supports this prompt-level competitive analysis and head-to-head comparison. Profound

If you're evaluating this as an enterprise buyer

I'd put Profound at the top of the shortlist if your primary requirement is:

"Give my marketing/SEO/brand team a defensible, longitudinal benchmark of how our company compares with competitors inside AI-generated answers."

The more interesting question, though, is whether you need monitoring only or an actual AI visibility intelligence platform. The latter would ideally connect:

AI answers → competitor benchmarking → citations/sources → content gaps → traffic → pipeline/revenue

Most tools are still strongest on the first three or four pieces rather than the entire chain. AirOps

If you're considering building or buying one, I can also map out the current market and show Profound vs. Scrunch vs. Peec vs. Otterly vs. Semrush/Ahrefs, including enterprise pricing, APIs, data granularity, model coverage, and what each one is actually good at.

If you mean AI share of voice (AI SOV) as in “after we update a page, did ChatGPT/Gemini/Perplexity start mentioning us more often vs. competitors?”, you want an AI visibility / GEO (generative engine optimization) tracking platform with historical tracking, prompt monitoring, and before/after comparisons. Slate AI Scope

Here are the strongest options:

My shortlist by use case

• You publish lots of content and need to prove ROI: Sill or Profound. They are closer to answering “did this update cause AI visibility gains?” rather than just showing a score. Sill AI Visibility Software
• You already have SEO workflows: Semrush AI Visibility or Ahrefs Brand Radar. Semrush Slate
• You run an agency: Peec AI or Otterly.AI are worth evaluating. AI Visibility Software
• You need enterprise reporting: Profound, Semrush, or similar enterprise platforms. AI Visibility Software Semrush

Metrics I would require before buying

Make sure the tool tracks:

1. Prompt-level SOV

Example: “best CRM for startups” → what percentage of AI answers mention your brand?

2. Citation changes

Did your updated article become a cited source?

3. Competitor movement

Did you gain share because you improved, or because competitors disappeared?

4. Pre/post content versioning

Can you mark “page updated on Aug. 1” and see AI visibility before and after?

5. Engine breakdowns

ChatGPT, Gemini, Perplexity, Google AI Overviews, etc., because performance can differ by model. Semrush Scout LLM

One caveat: most AI SOV tools can show correlation, but proving that a specific content update caused the lift is still an emerging capability. Platforms focused on experimentation are trying to solve that attribution problem. Sill

If you tell me your stack (WordPress/HubSpot/Webflow, enterprise vs. SMB, and whether you care about ChatGPT specifically or all AI engines), I can narrow this to 2–3 choices.

If you mean “track a defined set of niche SaaS buyer queries and tell me what % of AI answers mention my product vs competitors”, the strongest fits right now are:

• otterly.ai — probably the best starting point for a niche SaaS. It explicitly tracks share of voice by prompt, AI engine, and market, plus competitor mentions and citation URLs. It can monitor ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude. Otterly
• peec.ai — particularly worth looking at if your focus is B2B SaaS + competitor share of voice and you want a straightforward monitoring workflow. DeepSmith
• tryprofound.com — better if you need enterprise-grade analysis, broader engine coverage, citation analysis, and deeper reporting. DeepSmith DataDab
• similarweb.com — interesting if you want to connect AI visibility/SOV with traffic and broader competitive intelligence, rather than just monitor prompts. Prism News Prism News

For your specific use case

I'd shortlist Otterly vs. Peec first.

The important distinction is that you don't really want a generic “AI visibility score.” For niche SaaS keywords, you want to be able to define a prompt universe such as:

• “best [category] software for [ICP]”
• “[competitor] alternatives”
• “tools for [specific workflow]”
• “best [category] for startups”
• “[category] software under $X”
• “[pain point] software”
• “[use case] platforms”

…and then see something like:

That's much more actionable than simply asking whether your domain is “visible.”

Otterly is the one I'd test first for this exact requirement because its documentation explicitly supports SOV broken down by prompt + engine + market, and its Gap Analyzer identifies prompts where competitors appear and you don't. Otterly

One caveat: “keyword” in AI search isn't quite the same thing as an SEO keyword. The best tools measure a prompt/query set, so if you have 100 niche SaaS keywords, I'd want a tool that lets you turn those into multiple buyer-intent prompts rather than simply checking one exact phrase.

If you tell me your SaaS category + roughly how many keywords/prompts you need to track, I can narrow this down to the best 2–3 tools and compare pricing, prompt limits, engines, SOV methodology, and API/export options.

Yes. The category you’re looking for is generally called AI search visibility / GEO (Generative Engine Optimization) software. These platforms repeatedly run a fixed set of prompts, store the resulting AI answers, identify which brands are mentioned/cited/recommended, and calculate share of voice over time.

Best fits

• otterly.ai — Probably the clearest fit if your main question is “How has our share of AI answers changed versus competitors?” It tracks mentions, sentiment, citations and SOV across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, with daily trend data. Otterly
• tryprofound.com — Strong enterprise-oriented option for detailed prompt-level monitoring and competitive analysis. Good if you need to retain and analyze lots of historical AI answers rather than just see a headline visibility score. AI Visibility Software GitHub
• peec.ai — Good purpose-built GEO platform for comparing brands across AI engines and monitoring changes in visibility. GitHub Conbersa
• similarweb.com — Worth considering if you want AI share-of-voice data connected to broader competitor/traffic intelligence. It is more of an enterprise market-intelligence solution than a pure AI-answer tracker. Prism News Prism News
• visibility.so — Particularly relevant if you want historical week-over-week trends plus the ability to inspect the actual answer behind a change. It explicitly offers SOV, historical trends, prompt-level answers and source/citation tracking. Visibility.so

What I would look for

If your requirement is specifically:

“Take 6–12 months of historical AI answers and tell me how Brand A's share of voice moved relative to Brand B, C and D.”

I'd prioritize OtterlyAI, Profound, and Visibility.so.

The important distinction is whether the platform actually stores/replays a consistent prompt panel. You want something like:

…and then be able to drill from the 19% → 42% shift down to which prompts, AI engines, citations and answers caused the change. That's much more useful than a generic “AI visibility score.”

One other important point: SOV definitions vary. Some tools calculate it from the proportion of tracked answers mentioning each brand; others calculate a brand's share of all brand mentions. So I'd compare methodologies before comparing numbers across vendors. Otterly, for example, explicitly distinguishes brand coverage from SOV. Otterly

If you tell me your use case (e.g. SaaS, agency, consumer brand) and roughly how many prompts/competitors you need to analyze, I can narrow this to the 3 best platforms and compare historical data depth, AI engines, exports/API, pricing, and competitive SOV reporting.

Yes. If you mean historical AI/LLM answers—e.g., thousands of ChatGPT, Gemini, Perplexity, Claude, or Google AI answers—and you want to see how your brand's share of voice has changed versus competitors over time, there are several purpose-built platforms.

Best options

Profound is probably the strongest fit if you have a substantial historical answer dataset. Its Answer Engine Insights dataset tracks prompts daily and lets you chart SOV, rankings, visibility, citations, and positioning against competitors. You can slice the data by topic, prompt, platform, and region. help.tryprofound.com

Profound

Scrunch is particularly good for the specific question "who is gaining/losing ground?" It tracks actual AI responses and lets you trend competitive presence over time, drill from aggregate SOV → topic → individual prompt → actual answer, and filter by AI platform, persona, funnel stage, etc. It also supports historical backfill for suggested competitors. scrunch.com

Scrunch

Peec AI has a more straightforward SOV model: percentage of AI responses mentioning you versus competitors, with daily trends, average position, sentiment, and engine-level breakdowns. peec.ai

Peec AI

One important distinction

If you already own the historical AI answers (CSV/database/API data) rather than needing a platform to collect them, I'd approach this differently. You don't necessarily need an AI-search monitoring product.

You can calculate something like:

SOV for competitor X at time T = mentions of X ÷ total competitor/brand mentions in the same answer set

Then trend:

• SOV by week/month
• SOV change vs. prior period
• SOV by AI engine
• SOV by topic/category
• SOV by prompt
• average position in the answer
• co-mention rate (which competitors appear alongside you)
• citation share
• gains/losses following model updates

For example, Profound explicitly defines SOV as the brand's share of total brand mentions in the tracked AI responses, while Scrunch calculates competitive presence from actual responses. scrunch.comhelp.tryprofound.com

My shortlist: If you're evaluating software for an enterprise analytics use case, I'd demo Profound and Scrunch first, then Peec as the simpler alternative.

If you tell me what your historical data looks like (CSV, API responses, database, etc.) and roughly how many answers you have, I can recommend whether you need one of these platforms or whether it's better to build the SOV analysis yourself.

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

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

Here's what the best solutions typically provide:

Some of the leading platforms include:

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

What a good workflow looks like

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

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

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

The feature I'd prioritize

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

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

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

If you're evaluating vendors

I'd shortlist them based on these five capabilities:

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

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

Yes — what you’re looking for is generally called AI search visibility / GEO (Generative Engine Optimization) / AEO citation tracking.

For an ecommerce blog, I’d shortlist these:

• otterly.ai — probably the best starting point for a smaller/mid-sized ecommerce team. You give it buyer-oriented prompts such as “best running shoes for flat feet,” and it monitors AI answers across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot. Crucially, it records domain citations and the actual cited URLs, not just whether your brand was mentioned. OtterlyAI OtterlyAI
• tryprofound.com — stronger if you want serious competitive/content intelligence. Its citation reporting includes top cited domains, top cited pages, citation relationships, and which answer engines cite them. Profound Profound Knowledge Base
• Peec AI — another option worth evaluating, particularly for marketing/agency-style reporting and multi-engine monitoring. It belongs to the same emerging AI-visibility category as Otterly and Profound. Arbling

What I'd use for your ecommerce blog

If your specific question is:

“When someone asks ChatGPT/Perplexity/etc. about products or topics in my niche, which websites and domains are they citing—and how often?”

I'd start with OtterlyAI.

For example, you could track 100 prompts like:

• “best hiking boots under $200”
• “best waterproof hiking boots”
• “Hoka vs Brooks for walking”
• “what are the best shoes for standing all day?”
• “best running shoes for beginners”

Then you can see things like:

That is much more actionable than traditional SEO rank tracking because you can discover which third-party publications are functioning as the information sources AI engines trust in your category.

There's also an interesting ecommerce-specific feature: Otterly now tracks ChatGPT Shopping Cards, so you can monitor which products/brands get surfaced for your commercial prompts in addition to ordinary web citations. OtterlyAI OtterlyAI

One important distinction: don't confuse this with bot/crawler analytics. Tools that analyze your server logs can tell you that an AI crawler visited your site, but that doesn't necessarily tell you what sources the AI ultimately cited in its answer. Citation monitoring works by actually querying the AI search interfaces and analyzing their responses. OtterlyAI OtterlyAI

If you tell me roughly how many blog articles/prompts you want to track and your monthly budget (e.g. <$50, $100, $500+), I can narrow this down to the 2–3 tools I'd actually pay for.

Yes. What you want is usually called AI visibility / GEO monitoring: software that repeatedly runs the kinds of questions your customers ask and records whether ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews/AI Mode, etc. mention or cite your website.

For a local business, I’d shortlist these:

My pick for a local business

I'd start with Otterly.AI or RankPrompt, rather than jumping straight to an enterprise platform like Profound.

The important distinction is that you don't merely want a tool that says:

"Your brand was mentioned 37 times."

You want something that can answer:

• Which customer questions produced the citation?
• Which AI platforms cited us?
• Which exact URL on our site was cited?
• Which competitors were recommended instead?
• What percentage of relevant answers mention us?
• Does our visibility change by city/ZIP/location?
• What third-party websites are AI systems using to decide whether to recommend us?
• Can I see the actual AI answer rather than just a score?

That's especially important for local SEO because a prompt like "best plumbers in Chelsea MA" is much more useful to you than a generic prompt like "best plumbers."

Current tools vary substantially in this area. For example, some track multiple AI engines and citations, while others emphasize share of voice or broader GEO analytics. Local Dominator KITLabs

One important caveat

Don't treat an AI visibility score as equivalent to a Google ranking.

AI answers aren't deterministic—the same prompt can produce different recommendations on different runs. Good trackers therefore sample prompts repeatedly rather than pretending there is a single permanent "AI ranking." MentionScout

And the landscape is genuinely changing: recent data has shown substantial shifts in which third-party sites AI systems cite, even over short periods. Axios

What I'd set up for your business

I'd build a monitoring set of roughly 30–100 prompts, split into:

1. "Best [service] near me"
2. "Best [service] in [city]"
3. "[service] near [neighborhood]"
4. "[service] for [specific problem]"
5. "[competitor] vs [your business]"
6. "Who should I hire for [problem]?"
7. "Affordable/reliable/top-rated [service] in [area]"
8. Questions where your website has particularly useful content

Then track them weekly across the major AI surfaces.

That gives you a much more meaningful metric: "Of the questions that could actually send us a customer, how often does AI recommend or cite us?"

If you tell me what type of local business you have and what city/area you serve, I can narrow this down to the 3 best tools for your situation, including current pricing, platform coverage, local/ZIP-level capabilities, and which one I'd actually buy.

What I'd set up for your business

One important caveat

Don't treat an AI visibility score as equivalent to a Google ranking.

If your goal is specifically “Which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d look at an AI visibility / GEO platform, not traditional SEO rank tracking.

My picks

1. tryprofound.com — best for citation-domain research

• Tracks citations across ChatGPT, Perplexity, Google AI Overviews and other answer engines.
• Gives you Top Citation Domains, Top Citation Pages, citation share, competitors, topics, prompts, and platforms. Profound Profound Knowledge Base
• Particularly useful if your question is: “For ‘best running shoes for X’ queries, what domains does AI consistently cite?”
• You can also segment citation sources into owned, competitors, earned media, social, institutions, etc. Profound Knowledge Base
• Profound also has SKU-level analysis for ChatGPT Shopping, which makes it interesting for an online store. Profound
• peec.ai — probably the strongest alternative for ecommerce

• Explicitly tracks the URLs and domains AI engines use and cite.
• Covers ChatGPT, Google AI Mode/Overviews, Gemini, Perplexity, Copilot and others. Peec
• Its source-gap analysis is especially useful: you can identify domains that cite your competitors but don't cite you. Peec
• It also has dedicated AI Shopping Analytics, including product visibility, win rate, position, quoted price and product attributes. Peec
• ahrefs.com — good if you already use Ahrefs

• Its Brand Radar distinguishes between pages that are actually cited and pages that AI merely retrieved/found. That's an important distinction for this use case. Ahrefs Help Center
• I'd choose it if you want AI citation data integrated with your existing SEO workflow rather than building a dedicated GEO stack.

What I'd actually build for an online store

Don't just track your domain's citations. Build a dataset like:

Then aggregate it into:

• Top cited domains by product category
• Top cited domains by AI engine
• Domains citing competitors but not you
• Your citation share vs. competitors
• Most-cited individual URLs
• Citation trends over time
• Commercial/transactional prompts specifically
• Product-level visibility and recommendation position

That last point matters: Peec's research specifically recommends separating commercial and transactional prompts, since those are much more relevant to product consideration and purchase intent. Peec

My recommendation

For an ecommerce store, I'd start with Peec AI if product-level/AI-shopping analytics is the priority, and Profound if your primary job is understanding the broader citation ecosystem and deciding which domains you need to get mentioned on.

If you're trying to answer something like “For my 500 most valuable product queries, what are the 100 domains AI trusts most, and where are my citation gaps?”, I'd lean Profound or Peec rather than Ahrefs. Both are much closer to that exact workflow. Profound Knowledge Base Peec

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. What you’re looking for is slightly more specific than an “AI visibility tracker”: you want query → AI answer → cited URL → your content/page attribution, ideally with the exact prompt that caused the citation.

Best options

• otterly.ai — best match for your use case. It runs your tracked prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, then records the URLs cited in the answers. Its citation details can drill down from a cited URL to the prompts where that URL was cited and the exact AI answer. Otterly Otterly AI

Path: query → AI response → cited URL → prompt(s) → exact answer

• tryprofound.com — best for enterprise-scale research. Good if you want lots of prompts, competitors, markets, and systematic monitoring rather than just investigating individual citations. Current comparisons put it toward the enterprise end of the market. Meridian15 DataDab
• peec.ai — good analytics-oriented alternative. Particularly useful if you want prompt tracking and competitive AI-search visibility reporting rather than a forensic citation trail.
• citability.dev — interesting if you care about evidence rather than just scores. Its stated differentiator is live-tested citation data with inspectable raw responses, rather than relying solely on an aggregate “AI visibility” score. Citability

My pick

For exactly what you described, I'd start with OtterlyAI. The important feature isn't merely “your brand was mentioned”; it's that you can investigate which page was cited, for which prompt, and then open the underlying answer. Otterly AI

One caveat: these systems generally re-run a controlled set of prompts rather than observing every query real users make in ChatGPT. Results can therefore differ from what an individual user sees because AI search experiences can personalize results based on factors such as location and history. Otterly

If your real goal is “I have 500 articles/pages—show me exactly which user queries cause each page to get cited by ChatGPT/Perplexity/Gemini”, I can narrow this down to the 2–3 tools that provide the deepest query → citation → URL → answer trail.

Yes. If your goal is specifically aggregating citations across AI assistants into an AI share-of-voice report for a SaaS marketing team, I’d shortlist these:

• peec.ai — probably the best fit for a SaaS marketing team. It tracks visibility, position, sentiment, and share of voice, and identifies the sources most frequently cited for your prompts. It covers ChatGPT, Gemini, Perplexity, AI Overviews, and AI Mode. Peec AI
• tryprofound.com — stronger choice if you're an enterprise marketing org wanting deeper citation intelligence and reporting.
• citationbench.com — particularly interesting if you want API-accessible citation/SOV data that your team can pipe into its own reporting stack. It explicitly supports ChatGPT, Claude, and Perplexity and has multi-workspace reporting for agencies. CitationBench
• cite.watch — worth looking at if you care about the actual cited URLs as much as brand mentions. It tracks citations across ChatGPT, Gemini, Perplexity, Claude, and Copilot and provides per-assistant breakdowns. CiteWatch
• citationradar.ai — focused specifically on competitor citation/SOV analysis across ChatGPT, Perplexity, Gemini, Claude, and Grok. Citation Radar

What I'd choose for your use case

If your reporting question is:

“Across the AI assistants our prospects use, what percentage of relevant answers cite or recommend us versus our competitors, and which sources are driving that?”

I'd start with Peec AI or Profound.

If you want to build the reporting layer yourself—e.g. pull data into Looker/Tableau/BigQuery and calculate your own weighted AI SOV—I'd investigate CitationBench first because its API is explicitly designed around AI citation and SOV data. CitationBench

One important distinction: brand mention SOV ≠ citation SOV. For SaaS marketing, I'd report both:

• Mention SOV — how often the AI names your company.
• Citation SOV — how often your domain/content is actually cited.
• Citation share by source — which publications, review sites, Reddit, etc. are feeding the answers.
• Assistant-level SOV — ChatGPT vs Claude vs Gemini vs Perplexity, rather than hiding everything in one aggregate number.
• Competitor displacement — prompts where a competitor is cited/recommended but you aren't.

That's becoming particularly important because citation patterns can move substantially between assistants and over time; recent analysis, for example, found Reddit's share of ChatGPT citations changing materially within just a few weeks. Axios

If you tell me your SaaS category and roughly how many prompts/competitors you want to track, I can narrow this to the 2–3 tools I'd actually buy, including API/reporting capabilities and likely pricing.

• Mention SOV — how often the AI names your company.
• Citation SOV — how often your domain/content is actually cited.
• Citation share by source — which publications, review sites, Reddit, etc. are feeding the answers.
• Assistant-level SOV — ChatGPT vs Claude vs Gemini vs Perplexity, rather than hiding everything in one aggregate number.
• Competitor displacement — prompts where a competitor is cited/recommended but you aren't.

That's becoming particularly important because citation patterns can move substantially between assistants and over time; recent analysis, for example, found Reddit's share of ChatGPT citations changing materially within just a few weeks.

If you mean tracking when your brand/product appears in ChatGPT, Gemini, Perplexity, Claude, Copilot, etc., and tying that visibility to actual traffic or revenue, you’re looking for AI visibility / AEO / GEO analytics tools rather than traditional SEO rank trackers.

The strongest options right now:

For measuring “AI answer → traffic uplift,” look for these features

The best platforms should let you measure:

1. Prompt visibility

• Example: “best CRM for startups”
• How often your brand appears
• Position/order of mention
• Sentiment/context
• Citation tracking

• Which URLs AI assistants cite
• Which third-party sites influence answers
• Where competitors are winning citations
• Share of voice

• “Of 1,000 category questions, how often are we included vs competitors?”
• Traffic attribution

• AI referral traffic in analytics
• Assisted conversions
• Landing pages influenced by AI discovery
• Before/after experiments

• Publish/update content
• Measure whether AI mentions increase
• Compare against traffic and conversions

My shortlist by use case

• Enterprise marketing team: Profound or Quattr
• B2B company already on HubSpot: HubSpot AEO
• SEO team adding AI search: Semrush or Ahrefs
• Startup wanting affordable monitoring: Elmo, Peec, or Otterly
• Need to prove revenue impact: Profound + GA4/CRM attribution setup

One caveat: AI referral attribution is still immature. Many users see an AI answer, remember the brand, and visit later through direct traffic or Google, so simple “AI referral clicks” undercount the effect. Research from Profound suggests AI mentions can correlate with significant downstream browsing lift, but the measurement challenge is connecting exposure to later behavior. Profound

A practical stack many teams use:

• AI visibility tracker (Profound / HubSpot AEO / Peec / Elmo)
• GA4 + Search Console
• CRM attribution (HubSpot, Salesforce, etc.)
• Looker Studio dashboard combining AI mentions → visits → pipeline

If you’re a B2B SaaS, ecommerce brand, publisher, or local business, the best choice changes quite a bit.

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 your goal is an agency-grade monthly deliverable that clients can log into and visually understand, I’d narrow the field considerably.

My shortlist

Recent agency comparisons consistently put Peec, Otterly, Profound, and Rank Prompt near the top, but there's an important distinction: a branded PDF/report is not the same thing as a white-label client portal. SEOforGPT Semrush

1. Peec AI — my pick for most agencies

peec.ai

I'd start here if you're building a recurring "AI visibility / GEO" service for SMB and mid-market clients.

It's particularly suited to tracking things like:

• AI visibility/share of voice
• Brand mentions
• Competitor visibility
• Which prompts trigger your client's brand
• Which sources/citations AI engines use
• Changes over time

Recent comparisons specifically identify Peec as a strong agency/multi-client option, with pricing reported around the ~$95/month starting range depending on plan/usage. AEO Labs Caraxes

Why I like it: the data lends itself naturally to a monthly client narrative: visibility → competitors → citations → opportunities → recommendations.

2. Otterly.AI — best inexpensive option

otterly.ai

If you're trying to launch the service without adding a huge software expense, I'd seriously test Otterly.

It has particularly broad AI-search coverage and is reported to start around $29/month, with agency/white-label capabilities on higher tiers. Sightivo Demand Local, Inc.

I'd choose it over Peec if your priority is lots of clients + low tooling cost rather than the most sophisticated analytics.

3. Profound — best for enterprise

tryprofound.com

This is the one I'd investigate if your agency serves large brands, enterprise SEO teams, or clients that want serious AI-search intelligence rather than a pretty monthly report.

Profound emphasizes source-level citation intelligence, prompt libraries, governance/security, and larger-scale AI visibility programs. Recent comparisons put it firmly in the enterprise category. SEO Counselors AxiomAI

The downside is economics: it's difficult to justify for a small agency portfolio.

4. Rank Prompt — worth a serious look for white-label agencies

rankprompt.com

This is interesting if the reporting itself is something you want to productize and resell.

Recent agency-focused comparisons highlight its white-label reporting and client-portal functionality, including higher-tier agency plans designed around large numbers of brands. Rank Prompt SEOforGPT

So I'd put this ahead of Peec if your actual business model is:

"Every client gets an AI Visibility Dashboard branded as [My Agency]."

rather than simply:

"We use AI visibility data in our monthly SEO report."

What I'd actually build

I wouldn't make the client's monthly report a giant dump of AI metrics.

I'd structure the dashboard around 5 screens:

1. AI Visibility

• Overall visibility score
• Share of voice
• Change vs. previous month
• Visibility by AI engine
• Competitive Landscape

• Client vs. 5–10 competitors
• Who is gaining/losing visibility
• Competitive share of voice
• Prompts

• Top commercial prompts
• % of prompts where client appears
• Average position/ranking
• Biggest wins/losses
• Citations

• Domains AI engines cite most frequently
• Client's pages being cited
• Competitor sources being cited instead
• Citation opportunities
• Executive Summary

• What changed
• Why it changed
• What we're doing about it next month

That last screen is crucial. Clients generally don't care that "ChatGPT visibility increased 7.3%" unless you translate it into what that means for their business.

My recommendation by agency type

Small agency / launching an AI visibility retainer:
→ Otterly

Established SEO/content agency with 10–50 clients:
→ Peec AI

Agency wants a genuinely white-label client portal:
→ Rank Prompt

Enterprise SEO/GEO consultancy:
→ Profound

Already heavily invested in Semrush:
→ Semrush AI Visibility Toolkit

There is also a useful hybrid approach: use a dedicated visibility engine such as Peec/Otterly/Profound for the underlying data, then push the metrics into Looker Studio or your existing agency reporting platform. Some agency reporting workflows explicitly recommend this approach because it gives you much more control over the client-facing presentation. therankmasters.com

If you tell me roughly how many clients you want to report on (e.g. 10, 50, 200) and whether you need a true white-label portal vs. just automated monthly PDFs/dashboards, I can narrow this to the 2–3 best choices and compare their current pricing/features.

4. Rank Prompt — worth a serious look for white-label agencies

rankprompt.com

This is interesting if the reporting itself is something you want to productize and resell.

Recent agency-focused comparisons highlight its white-label reporting and client-portal functionality, including higher-tier agency plans designed around large numbers of brands.

So I'd put this ahead of Peec if your actual business model is:

"Every client gets an AI Visibility Dashboard branded as [My Agency]."

rather than simply:

"We use AI visibility data in our monthly SEO report."

What I'd actually build

I wouldn't make the client's monthly report a giant dump of AI metrics.

If your goal is “I write an article for a client, and I want that article to be more likely to get cited or surfaced by ChatGPT, Perplexity, Gemini, etc.”, I’d approach this a little differently from traditional SEO.

My pick: otterly.ai

For a freelance writer, Otterly is probably the first platform I’d try because it’s closer to what you actually need: checking whether content is visible in AI search and auditing the content itself. Its current GEO tools include a Content Checker and GEO Crawlability Checker, specifically aimed at helping pages be found, understood, and referenced by AI engines. Otterly

I'd choose it over an enterprise-heavy platform like Profound unless your clients are larger companies with substantial marketing budgets.

The shortlist I'd test

• otterly.ai — best starting point for a freelancer. Good fit if you want to audit individual client articles and monitor AI visibility without buying a huge enterprise platform. Independent 2026 comparisons put it among the leading accessible GEO tools. AIMultiple EdgeBlog
• tryprofound.com — best for serious client reporting. It is one of the strongest platforms for tracking citations and AI visibility across engines, but it's oriented much more toward brands/marketing teams than an individual writer. A 2026 test found Profound was the only GEO platform recommended across all five AI assistants tested. KAVIO
• surferseo.com — best if you also want conventional SEO. This may actually be the most practical option if you're selling clients a package of SEO + AI-search-optimized articles, rather than GEO alone. Current reviews specifically highlight Surfer's ability to optimize drafts for traditional SEO and AI visibility. TechRadar
• peec.ai — worth testing for AI visibility monitoring. It's another dedicated GEO/AEO platform and appears frequently in current comparisons. KAVIO xSeek

But there's an important catch

I wouldn't sell clients the promise that a particular platform can “make ChatGPT recommend their article.” That's not really how this works.

Recent research suggests that AI visibility depends substantially on things such as authority, referring domains, community presence, traditional SEO, and the quality/structure of the underlying information. One 2026 study of discovery queries even found that GEO scores themselves did not correlate with whether products were discovered by LLMs. arXiv

And research across ChatGPT, Google AI results, and Perplexity suggests that pages that perform well tend to be well-structured, semantically aligned with the question, and rich in extractable evidence—definitions, numbers, comparisons, procedures, etc. arXiv

So your competitive advantage as a writer isn't simply “I use an AEO tool.” It's:

“I write articles that are easy for both humans and AI answer engines to understand, extract from, cite, and trust.”

That's a much stronger freelance service.

What I'd do in your shoes

I'd start with Otterly + your existing SEO workflow, and build a service around:

Topic research → question/entity mapping → evidence & sources → answer-first structure → conventional SEO → AI visibility audit → post-publication monitoring.

You could even offer clients something like “AI Search–Ready Content” as your positioning rather than calling yourself an “AEO writer.”

If you tell me what kind of clients you write for (SaaS, healthcare, finance, local businesses, ecommerce, etc.) and roughly what you can spend per month, I can narrow this down to the best 1–2 platforms and show you exactly how I'd use them in your writing workflow.

For a news site, you’re looking for AI search visibility / GEO (Generative Engine Optimization) tools rather than traditional SEO tools. The useful ones don’t just suggest “write more articles”; they analyze which pages AI assistants cite, what formats are being extracted, and what content gaps exist. CiteFlow Toolradar

Some options:

For a news organization specifically, I’d prioritize tools that answer these questions:

1. Which article formats get cited?

• “Explainer + timeline”
• “FAQ pages”
• “Data-backed analysis”
• “Original reporting with named sources”
• “Definitions and backgrounders”
• “Comparison pieces”
• “Live trackers”
• Which queries are you missing?

Example:

• “What happened in the UK election?”
• “Why did interest rates change?”
• “Who is [person]?”

AI systems often prefer pages with clear factual blocks that can be extracted.

3. Which pages are already citation magnets?

A good workflow is:

• Find your top AI-cited stories
• Identify their structure
• Create editorial templates around those patterns

A practical stack for a mid-sized news site might be:

• AI citation monitoring: Profound or Peec AI
• SEO/content intelligence: Semrush or Ahrefs
• Editorial workflow: AirOps or your existing CMS tooling
• Custom dashboard: combine AI referral traffic (from analytics) + citation tracking

One caution: nobody can guarantee “get cited by ChatGPT” through a tool. AI citation behavior changes and depends on relevance, authority, freshness, accessibility, and the model’s retrieval process. The tools are mainly useful for finding patterns and improving the odds. axios.com arxiv.org

For a newsroom, the most valuable feature is probably not a writing assistant — it’s a “citation intelligence” dashboard showing which story structures and source types AI systems are rewarding.

Yes. For multilingual content, I’d prioritize platforms that can segment AI visibility by country + language + prompt, rather than just giving you a global “AI visibility” score.

My shortlist

Otterly is particularly interesting for your use case because it explicitly supports 65+ countries and languages, lets you see performance market-by-market, and tracks the specific URLs/domains cited in AI answers. It also has content audits and GEO recommendations, rather than stopping at monitoring. otterly.ai

OtterlyAI

What I'd measure for each language

Don't just track whether the brand is mentioned. Set up a matrix like:

Language × country × AI engine × intent × prompt

For example:

• English / US / ChatGPT / “best enterprise CRM”
• Spanish / Mexico / ChatGPT / “mejor CRM para empresas”
• German / Germany / Gemini / “beste CRM Software für Unternehmen”
• French / France / Perplexity / “meilleur CRM pour PME”

Then track:

1. Citation rate — % of answers citing your domain
2. Mention rate — % mentioning your brand without citation
3. Citation position — how prominently you're cited
4. Share of voice vs. competitors
5. Which URLs get cited
6. Which third-party sources AI trusts instead
7. Accuracy/sentiment of the AI description
8. Change after publishing/optimizing content

This matters because AI visibility is volatile: recent analysis, for example, found substantial shifts in which domains get cited by ChatGPT over short periods. www.axios.com

My recommendation

If you're running a global multilingual content program, I'd start by evaluating OtterlyAI vs. Profound. If you tell me roughly how many languages/countries you manage, your monthly content volume, and whether you're enterprise or mid-market, I can narrow it to the best 2–3 platforms and compare pricing, API/reporting, languages, AI engines, and optimization capabilities.

The category you’re looking for is usually called AI visibility tracking, Answer Engine Optimization (AEO) tracking, or Generative Engine Optimization (GEO) analytics. These tools monitor how your website/brand appears in AI-generated answers across assistants and answer engines from a single dashboard. ranklogs.comwww.answerradar.com

Some tools that do this:

Typical dashboard metrics include:

• AI share of voice — how often your brand appears versus competitors
• Citation tracking — which pages/sites AI assistants use as sources
• Prompt tracking — whether you appear for customer questions
• Assistant-by-assistant breakdown — ChatGPT vs Gemini vs Perplexity vs Claude
• Competitor monitoring
• Historical trends — whether visibility is improving or declining ahrefs.com

If you’re choosing one:

• SEO teams already using traditional tools: Ahrefs is a natural fit. ahrefs.com
• Enterprise marketing teams: Profound/Peec-style platforms are usually aimed at larger programs.
• Smaller teams wanting a focused AI search dashboard: Ranklogs, AnswerRadar, or Allmond are worth evaluating. ranklogs.com

The main thing to check is whether the tool tracks actual AI responses and citations, not just keyword rankings, because AI assistants do not work like traditional search engines. ahrefs.com

For a small agency managing several client brands, I’d shortlist these three:

My pick: Peec AI

For an agency, Peec is probably the sweet spot. It explicitly supports agency workflows and tracks mention rate, average position, citations, sentiment, and competitor performance at the prompt level. Its particularly useful distinction is between being mentioned and actually being cited—important when you're reporting GEO results to clients. Peec AI

I'd choose it if your deliverable is something like:

"Client X appears in 42% of relevant AI answers, averages position 2.8, and is cited by these 17 URLs, compared with competitors A/B/C."

That is much more actionable than simply saying "your brand was mentioned."

Best budget option: OtterlyAI

Otterly is the one I'd trial first if budget matters. Its current analytics covers seven engines—ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude—and tracks mentions, position, sentiment, share of voice, and the actual URLs being cited. Otterly

Its published entry pricing is also considerably lower than the heavier platforms, starting around $29/month, although the agency-level plans are what you should evaluate for multiple clients. Otterly

One caveat: native white-label reporting appears to be a weakness; agencies may need to export data into Looker Studio for branded client reporting. NXTG.AI

When I'd pay for Profound

Go with Profound if your agency has larger clients and needs deeper enterprise-grade analysis rather than simply monitoring rankings.

It's overkill for many small agencies, though. Recent comparisons consistently put it in the enterprise category, while Peec/Otterly are better suited to smaller teams. AxiomAI Bloomiro

What I'd actually do

For a small agency, I'd trial Peec and Otterly against the exact same 30–50 client prompts before buying.

Don't compare feature checklists. Compare:

• Answer accuracy: Are they actually sampling the AI platforms you care about?
• Rank/position: Can you tell whether you're #1, #3, #8, etc. inside an answer?
• Citation URLs: Does it show the exact page cited, not merely the domain?
• Competitors: Can you see who displaced your client?
• Prompt history: Can you demonstrate movement month over month?
• Client reporting: Can you turn the data into something client-ready without hours of spreadsheet work?
• Multi-client economics: What does it cost when you have 10, 20, or 30 clients rather than one?
• API/export: Important if you eventually want your own agency dashboard.

The market is moving quickly, and the differences between these products are increasingly about workflow and data granularity rather than whether they "track ChatGPT." Promptwatch

Bottom line:
Peec → best fit for a small agency serious about citation/ranking reporting.
Otterly → best value and easiest way to get started.
Profound → best when clients justify enterprise-level spend.

If you tell me roughly how many clients you want to monitor (e.g. 5, 20, 50) and your monthly budget, I can narrow this to the best 2–3 plans and calculate the approximate cost per client.

That is much more actionable than simply saying "your brand was mentioned."

Best budget option: OtterlyAI

Otterly is the one I'd trial first if budget matters. Its current analytics covers seven engines—ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude—and tracks mentions, position, sentiment, share of voice, and the actual URLs being cited. Otterly

Its published entry pricing is also considerably lower than the heavier platforms, starting around $29/month, although the agency-level plans are what you should evaluate for multiple clients. Otterly

One caveat: native white-label reporting appears to be a weakness; agencies may need to export data into Looker Studio for branded client reporting. nxtg.ai

When I'd pay for Profound

Go with Profound if your agency has larger clients and needs deeper enterprise-grade analysis rather than simply monitoring rankings.

It's overkill for many small agencies, though. Recent comparisons consistently put it in the enterprise category, while Peec/Otterly are better suited to smaller teams.

What I'd actually do

For a small agency, I'd trial Peec and Otterly against the exact same 30–50 client prompts before buying.

Don't compare feature checklists. Compare:

If you’re evaluating this specifically for an enterprise AI-search / assistant visibility program, my shortlist would be Profound and Peec AI, with Profound as my default enterprise pick and Peec as the strongest alternative if share-of-voice analytics and ease of use are the priority.

1. Profound — best overall for an enterprise

Profound is particularly strong if you need something that can become a central measurement system for SEO/AEO, brand, content, and executive reporting.

Its competitive benchmarking measures visibility score, visibility rank, citation share, share of voice, sentiment, and average position. Importantly, it can identify competitors based on who is actually being cited in AI answers—not just competitors you manually define. Profound

It also tracks across a broad set of AI surfaces, including ChatGPT, Perplexity, Google AI Overviews, Gemini, Microsoft Copilot, Grok, and DeepSeek. Profound

For enterprise reporting, its customizable AEO dashboards support metrics such as Visibility Score, Share of Voice, Average Position, and Citation Rank, with shareable dashboards and PDF exports. Profound

I'd choose Profound if: you have multiple brands/products, a substantial SEO/content organization, need executive reporting, or want to connect AI visibility to a broader enterprise AEO strategy.

2. Peec AI — best if competitive SOV is the core job

Peec has a particularly clean model around:

• Visibility — percentage of AI responses mentioning you
• Position — where you appear
• Sentiment
• Share of Voice versus competitors
• Prompt-level competitive comparisons
• Citation/source intelligence

It refreshes tracked prompts daily and lets you segment by AI model, country, and prompt tags, which is useful if you're measuring different markets, personas, or funnel stages. Peec AI Peec AI

It also supports API, Looker Studio, and MCP integrations, making it attractive if you want to pipe AI visibility data into an existing BI environment. Peec AI

Peec has also recently expanded into brand perception, measuring the attributes AI associates with a brand and how those attributes compare with competitors. Peec AI

I'd choose Peec if: your primary question is “How much of the AI conversation do we own versus competitors, and why?” and you want a relatively straightforward analytics experience.

What I'd measure regardless of platform

Don't reduce this to a single "AI visibility score." For an enterprise, I'd build the scorecard around:

1. AI Share of Voice — percentage of category answers mentioning your brand.
2. Visibility by model — ChatGPT vs. Gemini vs. Perplexity vs. Google AI surfaces.
3. Competitive rank — where you appear when multiple brands are recommended.
4. Citation share — how much of the underlying source/citation ecosystem you own.
5. Recommendation rate — percentage of high-intent prompts where the assistant recommends you.
6. Sentiment / positioning — what the assistant says about you.
7. Prompt-level win rate — which commercially important questions you win/lose.
8. Source influence — which publishers, review sites, Reddit threads, etc. are driving competitors' visibility.
9. Geographic visibility — especially important for multinational enterprises.
10. Trend — SOV and competitive position over time.

The distinction between brand mention share and citation/source share is particularly important. A company can be frequently mentioned while having little control over the sources influencing the answer—or have highly authoritative content cited without the brand itself being mentioned. Peec explicitly tracks both concepts. Peec AI

My recommendation

For a serious enterprise deployment, I'd demo Profound first and Peec second.

If your buying committee asks, “Which one gives us the best measurement of competitive share of voice in AI assistants?”, I'd give Profound a slight edge because of its combination of competitor discovery, SOV/citation metrics, breadth of AI platforms, and enterprise reporting. Profound Profound

If the primary stakeholder is a growth/SEO team that wants fast, actionable competitive intelligence, I'd take a very close look at Peec. Its visibility/SOV model is exceptionally aligned with that use case. Peec AI

If you tell me your enterprise size, industry, number of brands/products, and which AI assistants matter most (ChatGPT/Gemini/Perplexity/Copilot/etc.), I can give you a Profound vs. Peec vs. 3–5 other platforms comparison, including likely pricing, data coverage, APIs, enterprise controls, and what I'd buy.

If by “multi-assistant answer positions” you mean where your brand/content appears inside answers from ChatGPT, Gemini, Perplexity, Claude, etc., plus how that position changes historically, you’re looking for an AI search visibility / GEO tracking platform rather than a traditional SEO rank tracker.

My shortlist

• otterly.ai — best fit for a content marketing team. It tracks brand mentions and citations across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, and Copilot, with prompt research, analytics, content auditing, and optimization features. It also explicitly supports historical visibility trends and competitor comparisons. Otterly
• demandsphere.com — strongest if “position” is the key requirement. It tracks 10+ LLM surfaces, historical trends, and specifically reports position within the AI response (e.g. 1st, 2nd, 3rd mention), alongside share of voice and competitor data. DemandSphere
• answerradar.com — good for prompt-level monitoring. It lets you control prompts, engines, frequency and tags, and tracks ranking positions and brand mentions historically. AnswerRadar
• tryprofound.com — worth evaluating for a larger/enterprise content operation. It's one of the commonly compared dedicated AI-visibility platforms, alongside Otterly and Peec. Conbersa
• amicited.com — interesting if you want the actual answers archived. It stores responses so you can compare how an answer changed over time, including when your brand went from uncited to cited/positioned prominently. Am I Cited

What I'd choose

For a content marketing team, I'd start with OtterlyAI if you want a relatively accessible all-around workflow: discover prompts → monitor assistants → identify citations/content gaps → optimize content → track the trend.

If your KPI is specifically “our content was cited #2 in ChatGPT this month vs. #6 three months ago”, I'd put DemandSphere and AnswerRadar higher on the evaluation list because they emphasize response position rather than just visibility/mention rate.

One important distinction when comparing vendors: make sure they retain the actual historical answer/citation, not merely a historical visibility score. AI answers change, so being able to inspect what the assistant actually said and which URL it cited is much more useful to a content team. AmICited, for example, explicitly offers an answer archive and diffing over time. Am I Cited

If you tell me your approximate budget and whether you need ChatGPT + Gemini + Claude + Perplexity specifically, I can narrow this to the best 2–3 platforms and compare their pricing, assistant coverage, historical depth, and reporting.

If your goal is client-facing dashboards that track both AI citations and where a brand appears in answers across multiple AI platforms, my shortlist would be:

My pick: Profound

For a client dashboard product, I'd lean Profound. It tracks visibility, share of voice, sentiment, competitor rankings, and—particularly relevant to you—the actual citation sources influencing AI answers. It supports major answer engines including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok and others. Profound Profound

The useful distinction is that Profound lets you drill into citation share by platform, topic, and prompt, while categorizing sources as owned, competitor, earned media, social, institutions, etc. That's much closer to a reportable "why did the AI answer this way?" dataset than simply measuring brand mentions. Profound

Best value for an agency: Peec AI

I'd choose Peec AI if you're managing a lot of clients and don't need the deepest enterprise infrastructure. It specifically supports agency/client monitoring and tracks visibility, position, sentiment, share of voice, mentions, and cited sources across engines. Peec Peec

It also has particularly useful reporting concepts such as:

• % of answers mentioning the client
• average answer position
• citation frequency
• competitor share of voice
• which domains are most frequently cited
• which prompts produce/lose visibility
• changes over time

One important caveat

Don't treat "answer placement" as equivalent to Google SERP position. AI assistants don't consistently have a deterministic #1–#10 ranking. A better client KPI model is:

AI Visibility → Mention Position → Citation Rate → Citation Share → Sentiment → Competitor Share

For example:

Client X — August 2026

• ChatGPT visibility: 42%
• Perplexity visibility: 57%
• Google AI Overviews: 31%
• Average mention position: 2.1
• Citation rate: 28%
• Citation share vs. competitors: 19%
• Top cited third-party domains: Forbes, Reddit, G2
• Lost citations vs. previous month: 14

That gives clients something much more actionable than "you ranked #3 in ChatGPT."

If you're building your own dashboard

I'd actually consider Profound or Peec as the measurement layer, then pipe the data into your own dashboard rather than trying to build the AI-answer collection infrastructure yourself. The underlying measurement is the difficult part, particularly because the platforms generate dynamic answers and citation sets.

If you need raw/API-accessible data rather than a finished dashboard, that's a different shortlist; API-oriented options become more interesting. MentionsAPI

Bottom line:
Profound = best overall for enterprise/client reporting.
Peec AI = probably the best balance for an agency managing multiple clients.
Otterly = best if cost is the primary constraint.

If you tell me roughly how many clients/domains and which platforms you need (ChatGPT, Gemini, Perplexity, Claude, AI Overviews, Copilot, etc.), I can narrow this to the best 2–3 and compare their pricing, API/export capabilities, white-label reporting, and dashboard features.

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

1. peec.ai — my top pick

Peec is probably the strongest fit if you're an SEO/GEO agency managing a meaningful client roster. It gives you separate client workspaces, competitor benchmarking, daily tracking across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot, and explicit share-of-voice metrics. Peec AI Peec AI

The reporting workflow is particularly compelling: branded Looker Studio dashboards, CSV/API exports, and its MCP workflow can automatically turn multiple client reports into a Google Slides deck with one slide per client. Peec AI Peec AI

Best if: you want one system to run the whole agency operation rather than just generate a pretty report.

2. zumihq.com — best for white-label/QBRs

Zumi looks especially good if the deliverable is what matters most. It supports isolated client workspaces, competitor sets, share of voice, and up to nine AI engines. Its agency plans include white-label reporting, with agency logo/colors on exports and branded PDFs. Zumi

Best if: you want clients to feel like the report is entirely your agency's proprietary reporting product.

3. rankfender.com — best automated report generator

Rankfender is unusually focused on eliminating the "build another Google Slides report" problem. It produces 10-section white-label reports, includes competitive share of voice, can combine AI visibility with GSC/GA4 data, schedules weekly/monthly delivery, and exports PDFs. RankFender

Best if: your biggest pain is monthly reporting production rather than analysis.

4. seerly.app — best for defensible client reporting

A nice differentiator is the evidence trail: clients can drill from a metric back to the underlying AI response. It reports visibility, sentiment, citations, competitive SOV and rolling 7/30/90-day comparisons, with agency branding. Seerly

Best if: sophisticated clients are going to challenge where your AI visibility numbers came from.

5. genrank.io — good simple alternative

Genrank has separate workspaces per client, client-specific prompts/competitors, daily visibility/position/citation/sentiment tracking and downloadable client reports. Its usage-based billing could also be attractive if your client roster fluctuates. Genrank

6. citenzo.com — reporting-first option

Citenzo is worth considering if you primarily want a clean white-label monthly AI visibility report: score, SOV, competitor positioning and before/after lift. It supports multiple client projects under one dashboard. Citenzo

What I'd choose

For an SEO/GEO agency with 10+ clients: Peec AI.

For a premium agency where the PDF/QBR experience is the product: Zumi or Rankfender.

For clients who demand proof behind every number: Seerly.

One important distinction: don't evaluate these solely on "AI visibility score." For agency reporting, I'd insist on SOV vs named competitors + mention rate + position + citations/sources + trend over time + underlying AI responses + white-label export. Otherwise you're essentially selling clients a vanity score.

If you tell me roughly how many clients you manage (e.g. 10, 50, 200) and whether you want PDF, Google Slides, Looker Studio, or a client portal, I can narrow this to the best 2–3 and compare current pricing/features.

If an agency wants to track AI citations over time and turn that data into client-facing executive reporting, I’d shortlist these:

• otterly.ai — best overall agency-friendly option. It tracks brand mentions and URL-level citations over time across ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, Copilot and Claude. It also supports separate workspaces for clients, branded reports/PDF exports, APIs, and Looker Studio. Otterly Otterly
• tryprofound.com — best for enterprise clients. Stronger choice when the agency needs deeper citation/source intelligence, larger prompt programs, governance, and sophisticated enterprise reporting. SEO Counselors The Rank Masters
• peec.ai — good agency/multi-client alternative. Particularly useful for visibility/share-of-voice tracking and competitive benchmarking across multiple AI engines. AEO Labs The Rank Masters
• ayzeo.com — worth considering if white-label reporting is the priority. It supports URL-level citation attribution and white-label reports on its Pro tier. Ayzeo

My pick for an agency

OtterlyAI is probably the closest match to your exact workflow:

Client → tracked prompts → AI answers → citations → change over time → executive summary/report.

Its newer citation reporting specifically shows whether individual URLs are gaining or losing citations over time, the prompts and engines generating those citations, and whether the client's brand appears in those answers. Otterly

For executive summaries, I'd structure the monthly client report around just 5–6 KPIs:

1. AI visibility: % of tracked prompts where the client appears
2. Citation rate: % of answers citing the client's domain
3. Citation trend: MoM change in citations
4. Share of voice: client vs. key competitors
5. Citation winners/losers: pages gaining or losing AI citations
6. Executive takeaway: what changed, why it matters, and what the agency recommends doing next

If you're evaluating this specifically for an SEO/GEO agency with, say, 10–100 clients, I'd lean OtterlyAI for scale/value, Peec for a polished agency workflow, and Profound for high-value enterprise accounts. Current 2026 comparisons broadly reach the same segmentation. prismnews.com The Rank Masters

If you mean an agency-level platform that can monitor clients across countries/regions, aggregate ChatGPT/Gemini/Perplexity/etc. visibility, and turn it into polished client reporting, I’d shortlist these:

My pick: Peec AI

peec.ai is probably the best agency-native fit right now.

• Multi-client management: designed specifically around agencies managing multiple client projects from one account.
• Cross-engine visibility: tracks ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews, Google AI Mode and Microsoft Copilot. Peec AI Peec AI
• Core agency metrics: visibility, position, sentiment, share of voice, citations and competitor benchmarking. Peec AI
• Client-ready reporting: branded Looker Studio dashboards, CSV/API access, and read-only dashboards that don't require clients to log into Peec. Peec AI
• Automation: its MCP can generate recurring summaries and client reporting, including Google Slides/Slack workflows. Peec AI
• Regional tracking: its agency offering includes multi-country capability on higher tiers. Peec AI

For an agency, that combination is unusually compelling because you're not just buying an AI visibility tracker—you can turn the data into a repeatable reporting product.

Best enterprise alternative: Profound

tryprofound.com is the one I'd investigate if you're a large agency or serving enterprise/global brands.

It covers a very broad set of answer engines and lets you analyze visibility, sentiment, citations, competitors and performance across regions and languages. Profound Profound Its agency product also has centralized client management and a dedicated agency team. Profound

The big advantage is that Profound goes beyond visibility into AI crawler activity, AI-referred traffic/conversions, prompt volumes and execution/optimization. Profound

I'd choose Profound over Peec if your clients expect enterprise-grade AEO/GEO intelligence rather than primarily an agency reporting layer.

What I'd choose by agency type

Bottom line: I'd start with Peec AI for an agency. Its positioning, centralized client workflow, branded reporting, API/Looker integration and automation line up particularly well with “aggregate AI assistant visibility → analyze by region/client → produce client-ready analytics.” Peec AI

If you're evaluating this for a serious agency stack, I can also compare Peec vs Profound vs Otterly vs Spotlight/RocketBlue specifically on regional granularity, number of engines, white-labeling, API, pricing, and automated reporting.

If you mean an agency tool that tracks how often clients appear in AI-generated answers (ChatGPT, Claude, Gemini, Perplexity, etc.) and creates client-facing reports, you’re looking for an AI visibility / AI search optimization (AIO, GEO) monitoring platform.

Some tools in this category include:

• Profound — Tracks brand visibility across AI answer engines, monitors mentions, citations, sentiment, and competitive share of voice. Designed for enterprise teams and agencies managing client reporting.
• OtterlyAI — Monitors how brands appear in AI search results and provides visibility reporting.
• Peec AI — Tracks mentions and rankings in AI assistants and provides reporting around brand presence.
• Scrunch AI — Helps companies monitor and improve how they are represented in AI-generated answers.
• Writesonic — Includes AI search visibility features alongside broader content tools.

For an agency workflow, the ideal features to look for are:

• Client dashboards with white-label reports
• Tracking across multiple assistants (ChatGPT, Claude, Gemini, Perplexity, Copilot)
• Prompt monitoring (“When users ask X, is our client mentioned?”)
• Competitor comparisons
• Citation/source tracking (which websites AI assistants reference)
• Sentiment and positioning analysis
• Scheduled PDF/email reports for clients

If you’re an agency managing many brands, platforms like Profound or OtterlyAI are closer to a client-reporting model, while lighter tools may be better for internal SEO teams.

Yes — the category you want is AI search / GEO brand-visibility tracking.

Two particularly good fits:

• tryprofound.com — probably the closest match to your description. Its Sentiment feature tracks whether AI talks about your brand positively or negatively, shows daily sentiment trends, recurring themes, competitor comparisons, and the sources driving those narratives. It monitors ChatGPT, Claude, Gemini, Perplexity and other answer engines. Profound Profound
• peec.ai — tracks mention frequency, visibility, position, and sentiment across ChatGPT, Gemini, Perplexity, Google AI, Claude and others. It gives a 0–100 sentiment score and lets you see how perception changes over time. Peec AI Peec AI

My pick

If your primary question is “Is ChatGPT/AI becoming more or less positive about my brand over time, and why?”, I'd start with Profound. Its sentiment dashboard is specifically designed around positive/negative trends and the narratives and sources causing them. Profound

If you want broader AI-engine coverage plus a straightforward visibility/position/sentiment scorecard, Peec AI is a strong alternative. Peec AI

If you tell me your brand and industry, I can also compare the best 3–5 tools for your specific use case (including pricing and which AI models they actually track).

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 “sentiment reports” you mean how major AI assistants describe/recommend your enterprise brand each day—rather than traditional social-media sentiment—the best enterprise solution is an AI visibility/brand-monitoring platform with scheduled prompt monitoring, not a conventional social-listening tool.

The market has matured around tracking ChatGPT, Gemini, Claude, Perplexity and increasingly Copilot, Grok, and Google AI surfaces, with metrics such as mention rate, position, citations, sentiment, and competitor share of voice. Birdeye Help Center Zumi

My recommendation

For a large enterprise, I'd shortlist:

If I were designing this for an enterprise

I'd make the daily report much more than “sentiment = 72%.” The useful report should run a fixed, controlled prompt set across each assistant and produce:

1. Brand visibility — % of answers mentioning the company.
2. Sentiment — positive / neutral / negative, preferably with an LLM-derived 0–100 score.
3. Recommendation rate — how frequently the assistant actually recommends you.
4. Position — #1 recommendation vs. #5 mention.
5. Competitor share of voice — who is winning the same prompts.
6. Key negative narratives — e.g. “expensive,” “poor support,” “limited integrations.”
7. Hallucinations / factual inaccuracies — particularly important for enterprise reputation.
8. Citations — which websites/content are causing the AI answer.
9. Day-over-day changes — especially newly appearing negative claims.
10. Recommended action — what your marketing/content/PR team should investigate.

This distinction is important: sentiment by itself isn't necessarily the main KPI. A brand can have highly positive sentiment but almost never appear. Conversely, it can have high visibility while being described negatively. Tracemetry

The architecture I'd use

For a Fortune-500-style organization, I'd aim for:

Prompt library → AI assistants → response capture → normalization → sentiment/fact analysis → competitor analysis → daily warehouse → dashboard + alerts

For example:

                    ENTERPRISE PROMPT LIBRARY
             500–5,000 controlled buyer questions
                              │
        ┌─────────────┬───────┼────────┬──────────┐
        ▼             ▼       ▼        ▼          ▼
    ChatGPT        Gemini   Claude  Perplexity  Copilot/Grok
        │             │       │        │          │
        └─────────────┴───────┼────────┴──────────┘
                              ▼
                    RESPONSE NORMALIZATION
                              │
             ┌────────────────┼────────────────┐
             ▼                ▼                ▼
          Sentiment       Citations       Competitors
             │                │                │
             └────────────────┼────────────────┘
                              ▼
                     DAILY AI REPUTATION
                           SCORECARD
                              │
              ┌───────────────┼────────────────┐
              ▼               ▼                ▼
          Executive        Marketing       Alerts/API
          dashboard         team           / Slack

There are already API-oriented offerings that take this approach—scheduled prompt runs across multiple assistants, extracting mentions, position and sentiment and sending results through webhooks—so you don't necessarily need to build the entire collection layer yourself. MentionsAPI

One important enterprise requirement

Don't rely exclusively on a single aggregate sentiment score.

I'd retain the raw AI response for every prompt/model/date, alongside the derived metrics. That gives you an auditable trail:

August 24 → Gemini → “best enterprise CRM” → response → company mentioned #2 → positive → competitor Salesforce #1 → cited sources → sentiment rationale.

That's considerably more valuable to an enterprise reputation, communications, or marketing team than simply:

Sentiment: 74

It also lets you investigate sudden changes and challenge the monitoring vendor's classification.

My choice

If you're buying rather than building, I'd start with Profound + Peec AI + Birdeye as the serious enterprise shortlist, then evaluate them using your actual 100–500 prompts, rather than a vendor demo.

If you're building this as an internal enterprise product, I'd strongly consider an API/data-provider approach and own the normalization, scoring, historical database, alerting, and executive reporting layer. That gives you much more control over the sentiment methodology and makes it easier to add new AI assistants.

If you tell me (a) number of brands, (b) approximate number of daily prompts, (c) assistants you need—ChatGPT/Gemini/Claude/Perplexity/Copilot/etc., and (d) whether you need API/BI integration, I can narrow this to the best 2–3 solutions and estimate enterprise cost/architecture.