Positive mentions of 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.

For a marketing agency managing multiple clients, my first choice would be Peec AI.

peec.ai

Why I’d pick Peec AI

• Built for agencies: one account can manage multiple client projects, with centralized billing and flexible prompt allocation. Peec AI Peec AI
• Actual AI Share of Voice: it measures the percentage of AI responses mentioning your brand versus competitors, rather than just counting raw mentions. Peec AI
• Client-ready reporting: branded dashboards, read-only client links, CSV/API exports, and automated reporting workflows. Peec AI
• Multiple brands/sub-brands: agency accounts are designed to separate tracking by client/brand while sharing prompt capacity across projects. Peec AI
• Useful beyond ChatGPT: it tracks visibility, citations and sentiment across multiple AI search channels, including Google AI surfaces. Peec AI
• Good fit for scaling: pricing is based primarily on tracked prompts/models, rather than requiring a completely separate platform/account for every brand. Peec AI

How I'd shortlist the market

Recent 2026 comparisons similarly position Peec as a strong agency/multi-brand choice, while Profound is generally aimed more at enterprise depth. Bloomiro AnswerManiac

For your use case, I'd demo Peec first. The key thing I'd test during the demo is whether its project/brand limits and prompt economics work at your actual scale—for example, 20 clients × 50 prompts × 5 AI engines—because that will matter much more than the headline feature list.

If you tell me roughly how many clients/brands you manage and how many prompts per brand, I can compare Peec vs Profound vs Otterly vs RocketBlue specifically for your agency and estimate which would be cheapest/best.

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. For an enterprise that specifically wants historical analytics of how its brand appears across AI models, I’d focus on platforms built for AI visibility / answer-engine analytics, rather than generic social-listening or SEO tools.

My shortlist

My first vendor evaluation would be Profound. Current 2026 comparisons consistently position it as the enterprise-oriented option, particularly for deep reporting, citation/source analysis and large-scale prompt tracking. Its Enterprise offering reportedly covers up to roughly 10 answer engines, including ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, Copilot, Meta AI, Grok, DeepSeek and Claude. baarely.combloomiro.com

What I'd require in an enterprise RFP

The important distinction is that you don't merely want to know "did ChatGPT mention us?" You want a longitudinal dataset that lets you answer:

• Mention rate: What percentage of relevant prompts mention our brand?
• Position/rank: Are we #1, #3, etc. when recommended?
• Share of voice: How do we compare with competitors?
• Sentiment / narrative: How does the model describe us?
• Citation share: Which of our URLs/content are being cited?
• Competitor displacement: When we disappear, who replaces us?
• Model differences: Does ChatGPT treat us differently from Gemini, Claude, Perplexity, etc.?
• Geographic differences: Does visibility change by country/market/language?
• Time series: Can we look back 3, 6, 12+ months?
• Raw answer preservation: Can we retrieve the actual AI responses behind the metrics?
• Prompt/version history: Can we distinguish changes in visibility from changes to the prompt set?
• API/export: Can the underlying observations go into Snowflake/BigQuery/BI?
• Enterprise governance: SSO/SAML, RBAC, audit logs, data retention and contractual data controls.

That raw-answer + historical-observation layer is particularly important. Otherwise, you're buying a dashboard rather than an enterprise intelligence dataset.

Profound vs. Peec

I'd put these two through a serious bake-off.

Profound — strongest candidate if this is becoming a corporate intelligence function involving brand, SEO, PR, product marketing and executives. Its enterprise positioning emphasizes large-scale monitoring, source/citation analysis and reporting. bloomiro.com

Peec AI — worth evaluating if your primary users are marketing/SEO teams and you want a cleaner analytics/benchmarking experience. It tracks visibility, competitors and multiple markets/models and is generally positioned below Profound in enterprise complexity. baarely.com

Otterly is a good third evaluation, especially if you want breadth without immediately committing to an enterprise platform. It currently tracks ChatGPT, Perplexity, Google AI surfaces, Gemini, Copilot and Claude, with daily tracking of mentions, sentiment, share of voice and citations. otterly.ai

One important caveat

I'd not select a vendor based simply on the number of "AI models" it claims to track.

There are really two different things:

1. Model-memory measurement — ask ChatGPT/Claude/etc. what they know about your brand.
2. AI-search measurement — measure the answers generated when the model has access to search/web sources.

Those can produce dramatically different results. A current 2026 comparison specifically notes that search-enabled versus memory-based surfaces can produce very different citation behavior. arbling.com

For an enterprise brand, I'd want your historical database to preserve which surface, model/version, search state, geography, prompt, date and sources produced each observation.

Bottom line: if you're buying this as enterprise infrastructure rather than an SEO team's dashboard, start with Profound, benchmark it against Peec, and use Otterly as the lower-cost control. I'd make the ability to export/retain the underlying historical observations—not just charts—the deciding criterion.

If you tell me roughly your industry, number of brands/markets, and whether you need API/Snowflake integration, I can also build you a more rigorous enterprise vendor comparison/RFP scorecard with ~15–20 criteria and recommended weights.

If your specific requirement is “show me the exact page/URL that an AI answer cited, and map that citation back to our canonical content”, I’d shortlist these:

• otterly.ai — strongest fit for URL-level citation tracking. Its citation analytics explicitly capture the URLs AI engines use, including owned vs. competitor sources, and its citation report can show which of your pages are actually cited. It covers ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot. Otterly Otterly
• semrush.com — strongest if you already use an SEO suite. Its Cited Pages view identifies the specific pages on your domain cited in AI answers, while its Cited Sources view shows the external sites influencing AI visibility. You can drill into the full response and its source URLs. Semrush
• tryprofound.com — worth evaluating for enterprise. It's one of the leading dedicated AI-search visibility platforms and is aimed more at enterprise-scale monitoring and analysis than lightweight rank tracking. CitationDesk TechnologyAdvice
• peec.ai — good middle ground for citation/GEO analytics. It focuses specifically on AI-search visibility rather than traditional SEO and is frequently grouped with Otterly and Profound among the leading dedicated platforms. Foglift UX Continuum
• ahrefs.com Brand Radar — good if you want AI visibility integrated with your existing SEO/content data. It's particularly interesting for teams that want AI citation information alongside conventional search and backlink analysis. UX Continuum Rankability

What I'd test in the demos

Don't just ask vendors whether they “track citations.” Ask them to demonstrate this exact chain:

Prompt → AI engine → answer → cited URL → canonical URL → page on your site → citation frequency over time

And specifically test whether they can:

1. Distinguish your canonical URL from redirects, tracking URLs, syndicated copies, PDFs, and URL variants.
2. Tell you which exact page was cited, not merely that your domain was mentioned.
3. Preserve the raw AI response and source URL so you can audit the measurement.
4. Aggregate /page-a, /page-a?utm=..., redirects, etc. back to one canonical page.
5. Separate “brand mentioned” from “page actually cited.”
6. Show citation share by URL, topic, prompt, and AI engine.
7. Export/API the underlying citation records rather than only exposing a dashboard.

For your stated use case, I'd start with OtterlyAI and Semrush, then add Profound for an enterprise-platform comparison. Otterly is particularly aligned with the “which URLs are actually being cited?” question; Semrush looks stronger if you also want to connect those citations to your broader SEO/content opportunity workflow. Otterly Semrush

One important distinction: canonical URL mapping isn't necessarily the same thing as AI citation tracking. A platform may correctly tell you that example.com/blog/foo was cited while still leaving you to normalize that URL against your CMS's canonical URL. I'd make that normalization capability a hard requirement in the evaluation rather than assuming it from the word “citation.”

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-selection layer, and there are already several adjacent products—but I don’t see a major product that perfectly nails the specific question:

“Given these 100 pages, which ones is an AI assistant most likely to retrieve/cite for this particular question, before we actually run the question?”

The market currently leans more toward observing citations after the fact and then recommending optimization.

Closest products

Otterly is particularly close: it explicitly tracks which URLs AI engines cite, and its content-audit product includes “Content Audit & Prediction.” otterly.ai

Profound is probably the strongest option if you want enterprise-scale data. Current comparisons describe it as having particularly deep prompt and engine coverage. geodocs.dev

But there's an important gap

The really interesting product would go one step earlier.

Imagine entering:

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

And your system produces:

Then it could say:

If ChatGPT answers this question 100 times, these are the pages most likely to become sources.

That's a different product from ordinary GEO monitoring.

There is evidence that this is technically viable

Researchers and vendors are starting to identify measurable characteristics of cited pages. For example, a 2026 study analyzing 3,217 citations across five AI assistants found strong associations between citations and things such as original research/statistics, outbound authoritative references, structured data, and recency. www.gobiya.com

Yext's much larger analysis—17.2 million citations—also argues that AI visibility is heavily influenced by retrieval logic and the availability of structured, authoritative source data, rather than simply traditional content quality. www.yext.com

And importantly, different assistants don't necessarily agree: one 2026 study found very low overlap in cited domains across five assistants. www.gobiya.com

That means a good predictive product probably shouldn't output one universal score. It should produce something like:

Citation probability by engine

• ChatGPT: 72%
• Perplexity: 84%
• Gemini: 51%
• Claude: 39%
• Google AI Mode: 67%

The product I'd look for

If you're evaluating this as a new tool/product opportunity, I'd define it as:

AI Source Probability / Citation Forecasting

Input:

• question/prompt
• target market
• optional competitor set
• candidate URLs/domains

Output:

1. Predicted probability of citation
2. Predicted rank among sources
3. Which AI engines are likely to use it
4. Why the page is likely/unlikely to be retrieved
5. Pages currently dominating that query
6. What evidence would increase citation probability
7. Confidence interval / uncertainty

The killer feature would be counterfactual prediction:

“If we add original statistics + update this page + add these citations + restructure the answer, estimated ChatGPT citation probability goes from 23% → 47%.”

That's much more valuable than simply saying “you were cited 4 times last month.”

There's also an interesting strategic wrinkle: recent research suggests that third-party pages are extremely important sources, not just a company's own website. One 2026 study found 40% of citations went to independent best-X/listicle pages, versus 34% to vendors' own sites. visibly.so

So the ultimate product might actually answer:

“What pages across the entire web are AI assistants most likely to cite for this query—and what can I do to get my brand into those sources?”

That's considerably more powerful than a conventional GEO dashboard.

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 usually called AI visibility / AI search monitoring / AEO tracking. These tools repeatedly run the questions your clients care about through AI answer engines and record whether the client is mentioned, how prominently, competitors mentioned, and which websites/sources get cited. Prism News The Rank Masters

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

• otterly.ai — probably the easiest place to start. It tracks brand mentions and website citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot, and exposes the underlying prompts/citations via an API. Pricing starts at $29/month. Otterly
• Peec AI — my other strong pick for an agency managing multiple clients. It focuses heavily on visibility analytics, competitive benchmarking and multi-brand tracking, with agency/white-label reporting available. Baarely Bloomiro
• Profound — the heavyweight option if you eventually have larger clients who want deep citation/source analysis and lots of reporting. It's more enterprise-oriented, so probably overkill for a small agency initially. Bloomiro
• Scrunch AI — worth considering if you want monitoring plus tools for making client websites more accessible/useful to AI agents. It's more of a broader platform than a simple visibility tracker. Baarely Bloomiro

What I'd choose for your agency

Start with OtterlyAI or Peec AI.

The key feature I'd prioritize isn't simply "does ChatGPT mention my client?" It's whether you can export a report like:

Client: Acme Dental
Tracked prompts: 100
AI visibility: 34%
Cited in: 27% of answers
Top competitors: Competitor A 42%, Competitor B 31%
Most frequently cited sources: Yelp, Healthgrades, NYT, Acme's website, etc.
Citation opportunities: 12 prompts where competitors are cited but Acme isn't

That gives you something you can turn into a monthly GEO/AEO deliverable, rather than just another SEO dashboard.

One important distinction: mention tracking and citation tracking aren't the same thing. A client can be named in an AI answer without its website being used as a source. For content agencies, I'd specifically require the tool to expose the actual cited URLs/domains and the prompts that generated them. Otterly explicitly says it tracks both mentions and citations and provides API access to citations/prompts. Otterly

If you tell me roughly how many clients you manage (e.g. 5, 20, 50) and your monthly software budget, I can narrow this to the best 2–3 options and compare their agency/white-label capabilities.

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.

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.

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 you mean a tool that can tell you when AI assistants quote or summarize your website, and pinpoint the exact source passages/URLs on your site, you’re looking for an AI visibility / answer engine optimization (AEO) monitoring tool or a citation tracking tool. There isn’t one universal tool that can see every AI assistant’s private outputs, but several can help:

• tryprofound.com — Tracks how brands appear in AI-generated answers, including citations and visibility across AI search experiences. Useful for identifying when your content is being referenced.
• otterly.ai — Monitors AI search results and citations, helping identify where your pages appear in AI answers.
• peec.ai — Tracks brand visibility in AI answer engines and can show cited sources.
• scrunch.com — Focuses on AI search visibility and how content is represented in AI-generated answers.
• ahrefs.com / semrush.com — Traditional SEO tools that can help find which pages are authoritative and likely being surfaced, though they do not directly reveal all AI quotes.

If you specifically need “AI assistant said this exact sentence — find the paragraph on my site it came from”, the workflow is usually:

1. Collect AI outputs (from ChatGPT, Gemini, Perplexity, Claude, etc.) using monitoring queries.
2. Extract quoted text or passages.
3. Run similarity matching against your site content using: - a crawler + vector database (e.g., embeddings with OpenAI, Pinecone, Weaviate, Elasticsearch)
4. plagiarism-style matching tools
5. custom scripts using semantic search.

For Perplexity-style citation tracking, tools like Profound, Otterly, and Peec are closer. For exact passage attribution at scale, you usually need a custom pipeline.

If you tell me which AI assistants you care about (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.) and whether you need monitoring or forensic matching of quotes, I can narrow down the best option.

The software category you’re looking for is usually called AI visibility tracking, Generative Engine Optimization (GEO), AI search optimization, or LLM monitoring. These tools try to show which prompts, queries, or topics cause AI assistants to mention or cite your website.

Some notable options:

A few important distinctions:

• If you want to know “Which exact prompts make ChatGPT/Claude/Gemini mention my site?” → tools like Profound, Scrunch AI, Otterly AI, and Peec AI are closest to that goal.
• If you want to know “Which pages on my site are likely to be cited by AI?” → look at AI citation monitoring plus traditional SEO tools (Semrush, Ahrefs, Google Search Console).
• If you want to know “How do I make my content more likely to be used by AI assistants?” → GEO tools analyze content structure, authority signals, and entity coverage.

Keep in mind that AI assistants generally do not expose a complete log of every user prompt that led to a citation. These platforms usually work by running their own sets of test prompts, monitoring AI outputs, and comparing results over time.

For a website owner, a practical setup is often:

1. Use an AI visibility tracker (Profound/Scrunch/Otterly/Peec) to monitor mentions.
2. Build a prompt library around your customer questions (e.g., “best software for X,” “alternatives to Y,” “how to solve Z”).
3. Compare which pages get cited and improve those pages with clearer answers, structured data, expert authorship, and topical depth.

If you tell me your website type (SaaS, ecommerce, publisher, local business, etc.) and which assistants matter most (ChatGPT, Perplexity, Gemini, Claude), I can suggest the best-fit tools.

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.

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.

Yes. The category you’re looking for is AI search visibility / GEO (Generative Engine Optimization) tracking.

Best fits

• tryprofound.com — probably the strongest fit if your key requirement is “alert me when my brand starts or stops appearing.” It runs tracked prompts daily, measures visibility/share of voice, and its automation system can trigger alerts when visibility drops below a threshold. Profound Knowledge Base Profound
• peec.ai — excellent for tracking how often your brand is mentioned in ChatGPT, position, sentiment, competitors, and the sources ChatGPT cites. It updates visibility metrics daily. Peec AI Peec AI

What I'd choose

If your requirement is specifically:

“Tell me when ChatGPT stops recommending/mentioning my brand for important prompts.”

I'd start with Profound, because it explicitly supports visibility monitoring and threshold-based alerts. Profound Knowledge Base

If you want a more marketing-oriented dashboard for ChatGPT + Gemini + Perplexity + Google AI, I'd also evaluate Peec AI. Peec AI

One important distinction: these tools don't continuously watch every possible ChatGPT conversation. They monitor a defined set of prompts/topics and measure whether/how your brand appears in the resulting AI answers. Profound, for example, runs tracked prompts daily. Profound Knowledge Base Profound

If you tell me your brand + industry, I can compare the best 3–5 tools specifically for alerts, ChatGPT coverage, pricing, and whether they test the real ChatGPT frontend versus an API.

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 your goal is specifically enterprise-grade monitoring and audit of how often your trademarks/brands appear in conversational AI answers, I’d put Profound at the top of the shortlist right now.

The category is usually called AI visibility monitoring, Answer Engine Optimization (AEO), or Generative Engine Optimization (GEO). These platforms repeatedly run controlled prompts against AI systems and measure brand mentions, position, citations, sentiment, competitors, and changes over time. TrustData TechnologyAdvice

My shortlist

1. Profound — my enterprise pick

tryprofound.com

Profound is the one I'd evaluate first if this is going into a large brand, legal, communications, SEO, or corporate reputation program. Current comparisons consistently position it as the enterprise-focused option, with answer-engine insights, prompt-volume data, citations, sentiment, and agent/crawler analytics. TechnologyAdvice Bloomiro

For trademark monitoring, the important distinction is that you don't merely want:

"Does ChatGPT mention Acme?"

You want something closer to:

"Across 10,000 commercially relevant prompts, how frequently does Acme appear, under which trademark variants, in what position, with what sentiment, compared with competitors, and which sources caused the answer to contain Acme?"

That's much closer to what Profound is designed to measure.

2. Scrunch — particularly interesting for technical teams

scrunch.com

Scrunch is compelling if your enterprise wants to connect what AI says about the brand with how AI systems crawl and interpret the company's web properties. It combines prompt/topic tracking, citation analysis, competitor benchmarking and AI-bot traffic/crawl information. TechnologyAdvice

I'd shortlist it alongside Profound if your SEO/web-platform team will be involved.

3. AthenaHQ — worth evaluating for brand integrity

AthenaHQ is particularly interesting if "audit" means more than counting mentions. Current comparisons highlight hallucination detection, competitor monitoring, cross-platform visibility and enterprise controls. TechnologyAdvice

That's potentially valuable for a trademark/legal department because a simple mention count doesn't tell you whether the AI is misrepresenting the trademark, product, ownership, affiliation, or reputation.

4. OtterlyAI — best pragmatic monitoring option

otterly.ai

Otterly currently tracks mentions, citations, sentiment and share of voice across multiple AI engines, including ChatGPT, Perplexity, Google AI surfaces, Gemini, Copilot and Claude. Otterly

It's a good choice if the requirement is primarily:

"Give our marketing team a reliable dashboard showing how often our brands appear in AI answers."

rather than building a sophisticated enterprise brand-governance program.

One important caveat for trademark monitoring

I wouldn't select a vendor based on number of AI engines alone.

For an enterprise trademark/audit use case, I'd make these requirements mandatory:

• Custom trademark/entity lists — including registered marks, product names, abbreviations, misspellings and former names.
• Custom prompt libraries based on real customer questions, not just generic keywords.
• Prompt reproducibility — you need to know exactly what was asked, when, and against which model/surface.
• Raw answer retention — ideally storing the actual AI response so an auditor can inspect it later.
• Mention detection — including exact-match, variant and semantic/entity matching.
• Position/ranking — first recommendation vs. third recommendation matters.
• Citation/source tracking — what websites/documents led the model to mention the trademark.
• Sentiment/context — positive, neutral, negative, misleading, etc.
• Competitor comparison / share of voice.
• Model and engine segmentation — ChatGPT ≠ Gemini ≠ Claude ≠ Perplexity ≠ Google's AI surfaces.
• Historical snapshots — so Legal/Brand can establish an audit trail.
• Alerts for sudden disappearance, negative characterization, hallucinations or competitor displacement.
• API/export so results can enter your existing BI, GRC, brand-monitoring or legal systems.
• Enterprise security/RBAC/SSO/data-retention controls.

That last group is where I'd distinguish a marketing AEO tool from an actual enterprise monitoring/audit system.

If I were buying this for a Fortune 500 trademark portfolio

I'd run an RFP with Profound, Scrunch and AthenaHQ as the enterprise tier, and Otterly as the lower-complexity benchmark.

The key proof-of-concept would be a fixed corpus of perhaps 500–2,000 real customer prompts × 5–8 AI surfaces, run repeatedly. I'd then compare:

Trademark mention rate → correct identification → recommendation position → sentiment → citation → hallucination/error rate → competitor share of voice → change over time.

That will tell you much more than vendor demos.

One particularly important question to ask vendors is: "Can you give us the complete raw answer and provenance behind every trademark-mention metric?" If the answer is no, I'd be cautious about calling the resulting numbers an audit. Current tools vary considerably in how they define and calculate visibility. Otterly aeolabs.ai

If you tell me whether you're approaching this from Legal/IP, Brand/Marketing, SEO, or Corporate Communications, I can also give you a 10–15 vendor enterprise comparison matrix, including pricing, AI engines, API access, raw-answer retention, hallucination detection, SSO/RBAC, auditability, and trademark-specific capabilities.

That's much closer to what Profound is designed to measure.

2. Scrunch — particularly interesting for technical teams

scrunch.com

Scrunch is compelling if your enterprise wants to connect what AI says about the brand with how AI systems crawl and interpret the company's web properties. It combines prompt/topic tracking, citation analysis, competitor benchmarking and AI-bot traffic/crawl information. TechnologyAdvice

I'd shortlist it alongside Profound if your SEO/web-platform team will be involved.

3. AthenaHQ — worth evaluating for brand integrity

AthenaHQ is particularly interesting if "audit" means more than counting mentions. Current comparisons highlight hallucination detection, competitor monitoring, cross-platform visibility and enterprise controls. TechnologyAdvice

That's potentially valuable for a trademark/legal department because a simple mention count doesn't tell you whether the AI is misrepresenting the trademark, product, ownership, affiliation, or reputation.

4. OtterlyAI — best pragmatic monitoring option

otterly.ai

Otterly currently tracks mentions, citations, sentiment and share of voice across multiple AI engines, including ChatGPT, Perplexity, Google AI surfaces, Gemini, Copilot and Claude. otterly.ai

It's a good choice if the requirement is primarily:

"Give our marketing team a reliable dashboard showing how often our brands appear in AI answers."

rather than building a sophisticated enterprise brand-governance program.

One important caveat for trademark monitoring

If your goal is specifically “What percentage of AI answers for my target keywords mention my brand vs. competitors?”, I’d start with OtterlyAI.

otterly.ai

Why I’d pick it

• Keyword/prompt-level tracking: define the questions your prospects ask and monitor them over time.
• Actual AI Share of Voice: it calculates your share of answers mentioning your brand versus tracked competitors, broken down by prompt and AI engine. Otterly
• Brand-term monitoring: useful for both category queries (“best CRM for startups”) and branded queries (“[Brand] alternatives”).
• Broad engine coverage: ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly
• Competitive visibility: you can see which competitors are winning the same prompts and where you're absent.
• Citations + sentiment: it goes beyond “mentioned/not mentioned” and shows which pages AI cites and how the brand is described. Otterly

Other good options

One distinction I'd pay attention to: some products report brand coverage (“did you appear at all?”), while true share of voice compares your mentions against the other brands appearing in the same answer set. Otterly explicitly distinguishes those metrics. Otterly

If you tell me your budget (e.g. <$100/mo, $100–500/mo, enterprise) and whether you care more about ChatGPT specifically or all AI engines, I can narrow this to the best 2–3 options.

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. What you’re looking for is usually called AI search / LLM visibility monitoring or AI answer monitoring. These platforms repeatedly run controlled prompts against AI assistants, capture the resulting answers, and analyze brand mentions, citations, sentiment, competitors, and changes over time.

For compliance reviews, I’d prioritize the ability to retain the actual answer, not just a visibility score.

For compliance, I'd evaluate them differently

Your requirements should probably be:

1. Exact prompt recorded — e.g. “What are the leading providers of X?”
2. Exact AI response retained — not merely “Brand mentioned: yes.”
3. Timestamp and model/engine recorded
4. Country/language/context recorded
5. Citations and source URLs preserved
6. Change history — demonstrate what the assistant said on different dates.
7. Evidence export — PDF/CSV/API or preferably an immutable evidence archive.
8. Automated alerts when your brand is described inaccurately or in a potentially non-compliant way.
9. Competitor comparisons so reviewers can distinguish a systemic model behavior from a brand-specific issue.
10. Audit trail/access controls if the material is going into a regulated compliance process.

My shortlist would be Profound + OtterlyAI. Profound looks particularly interesting if the purpose is “prove what AI assistants were saying about our brand and identify inaccurate claims”; its current product explicitly includes an AI accuracy / FactCheck capability. help.tryprofound.comwww.tryprofound.com OtterlyAI is attractive if you want a simpler monitoring system with daily runs and API/export capabilities. otterly.ai

One important caveat: these products generally sample AI answers using predefined prompts; they aren't necessarily an exhaustive archive of every answer that ChatGPT, Gemini, etc. give to every real customer. For a formal compliance program, I'd therefore treat them as controlled monitoring/evidence collection, and ask vendors specifically about retention period, raw-response export, audit logs, and evidentiary integrity.

If you tell me your industry (e.g. financial services, healthcare, pharma, insurance) and whether you need SOC 2/SEC/FINRA/HIPAA-style evidence, I can narrow this to the 2–3 products that are most appropriate and compare their compliance/audit capabilities.

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

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

My ranking

1. OtterlyAI — best budget pick

• Entry plan is around $29/month for a small set of tracked prompts. AEO Labs Loudmink
• Tracks share of voice, mentions, competitors, sentiment, and the actual URLs AI engines cite. Otterly
• Covers ChatGPT, Google AI Overviews, Perplexity and Copilot on the entry tier; additional engines can cost extra. AEO Labs
• Particularly relevant for ecommerce because it now has AI Shopping Analytics, including how products surface and which retailers appear alongside you. Otterly
• Downside: 15 prompts isn't much, so you'll need to be selective about the questions you monitor.
• peec.ai — better if you can spend ~$90–100/month

• More attractive once you need a larger prompt set and deeper citation/source analysis.
• Several 2026 comparisons put it around $95/month at entry, with more substantial multi-engine monitoring. AEO Labs AEO Labs
• I'd choose this over Otterly if AI search is already producing meaningful revenue for you.
• tryprofound.com — overkill for you

• Excellent enterprise-level visibility/citation intelligence, but the economics don't make much sense for a small store. Loudmink SEO Counselors

What I'd actually track

Don't waste your 15 Otterly prompts on generic searches like "best running shoes." Build prompts around commercial intent and product discovery, e.g.:

• "Best [product category] for [use case]"
• "[Product category] brands recommended for [customer type]"
• "What are the best alternatives to [competitor]?"
• "Where can I buy [product type]?"
• "[Your brand] vs [competitor]"
• "Best [product category] under $X"
• "What should I look for when buying [product]?"

Then watch three numbers:

AI citation share → competitor citation share → which URLs are being cited.

The third one is arguably the most actionable. If ChatGPT consistently cites a competitor's buying guide while ignoring your product/category page, you've learned where your content/authority gap is—not merely that you have an AI visibility problem. Otterly explicitly reports the cited URLs and competitor citations. Otterly

Bottom line: If your budget ceiling is ~$30/month, pick Otterly. If you can justify ~$100/month and want more serious citation/share-of-voice analysis, pick Peec. I wouldn't spend enterprise money on Profound for a small ecommerce operation.

If you tell me what you sell + your monthly AI/SEO budget, I can also tell you exactly which 15 prompts I'd put into Otterly to get the most useful citation-share baseline.

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

My pick: Otterly.ai

• $29/month entry plan with 15 tracked prompts, making it the lowest-cost serious option I found. AEO Labs AEO Labs
• Tracks major surfaces including ChatGPT, Google AI Overviews, Perplexity, and Copilot on the entry tier. Loudmink
• Shows whether you're being mentioned/cited, your position, competitors, and citation/source URLs—the stuff you actually need to measure AI citation share. Loudmink Reachroller
• It's particularly appropriate if you're trying to answer: “When shoppers ask AI for products like mine, does my store get recommended?”

The catch: 15 prompts is pretty limited, and Gemini/Google AI Mode coverage can require paid add-ons. AEO Labs

When I'd choose something else

Peec is arguably the better value once you're willing to spend ~$95/month: its entry plan has substantially more prompt capacity and broader engine coverage, while Otterly's advantage is the much lower absolute cost. AEO Labs Ayzeo

What I'd do with a <$50/month budget

Don't waste the 15 prompts on generic searches. Build them around high-intent shopping queries, e.g.:

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

Then track citation share, not just mentions: How many relevant answers cite your store/product vs. competitors? Which third-party sites are being cited instead?

That last part is particularly important because your own domain may not be the source AI engines rely on; third-party reviews, comparisons, retailers, Reddit, and other sources can influence what gets recommended. AEO Labs

Bottom line: Start with Otterly at $29/mo for 1–2 months. If you discover AI search is generating meaningful visibility/opportunity and 15 prompts aren't enough, move to Peec rather than jumping straight to an enterprise tool.

If you tell me what you sell + your approximate monthly budget ($0, $30, $50, $100, etc.), I can recommend the cheapest setup and give you the exact prompts I'd track.

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.

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 your goal is specifically “I changed content on my site—did that change our AI share of voice?”, I’d shortlist these:

What I'd pick

Peec is probably the closest match to what you described. Its metrics explicitly include share of voice vs. competitors, and it updates them daily by AI engine. peec.ai

The important thing, though, is how you run the experiment. Don't just look at “AI visibility went from 18% → 24%.” Set up:

1. A fixed prompt set — e.g. 50–200 questions your buyers actually ask.
2. Baseline period — ideally 2–4 weeks before the content change.
3. Content-change date — record exactly which URLs/content changed.
4. Post-change tracking — continue running the same prompts.
5. Compare share of voice, mention rate, position, citations and competitor share before vs. after.
6. Segment results by URL/topic/prompt cluster and AI engine so you can tell which content change actually moved visibility.

That's important because AI answers can fluctuate substantially; a before/after measurement based on a handful of prompts can easily mistake normal variation for an SEO/GEO effect. The same prompts tracked repeatedly are much more informative. www.leanlabs.com

My ranking for your exact use case: Peec → Profound → Otterly → Scrunch.

If you tell me your monthly budget, approximate number of prompts, and whether you're B2B/B2C, I can narrow this to the best 2–3 and compare their change-detection / before-vs-after capabilities specifically.

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.

For long-tail SaaS keywords, you want an AI visibility / GEO (Generative Engine Optimization) tracking tool that lets you define your own prompts (not just broad categories) and measures brand mentions, citations, competitor presence, and share of voice in AI answers. Scout LLM Visibility.so

Good options:

For a niche SaaS, I would evaluate them on these capabilities:

• Custom prompt sets: Can you add queries like: - “best SOC 2 compliance automation tool for 20-person startups”
• “alternatives to [competitor] for healthcare SaaS”
• “best API monitoring platform for fintech teams”
• Prompt clustering: Can it group hundreds of long-tail questions into themes?
• Competitor SOV: Does it show “you vs competitors” rather than only your mentions?
• Citation tracking: Which websites/pages are causing AI engines to recommend competitors?
• Historical snapshots: Can you prove that AI visibility improved after content/PR/product changes? Visibility.so Rankscale.ai

For a niche B2B SaaS, my shortlist would usually be:

1. Scout LLM — if you want straightforward AI SOV monitoring. Scout LLM
2. Visibility.so — if keyword/prompt-level reporting matters most. Visibility.so
3. Peec / Profound — if this is for a larger marketing org with reporting needs. The Rank Masters

A practical setup is to track 100–500 buyer-intent prompts, not traditional keywords. AI answers are generated from natural-language questions, so “share of voice” is usually more meaningful at the prompt-cluster level than at the single-keyword level. aishareofvoice.io

If your core requirement is AI share of voice (SOV) by geographic market × language × prompt set, I’d narrow the field to Profound, Peec AI, and Otterly.ai, with Profound the strongest choice for a large multinational.

My ranking

1. Profound — best overall for global enterprises

This would be my first demo if you're trying to answer questions such as:

“What percentage of AI answers recommend us in Germany vs. France vs. the US, and how does that change when the prompt is asked in German vs. English?”

Profound is positioned toward enterprise-scale AI visibility, with broad engine coverage, competitive SOV, citation/source analysis, and deeper analytics. Current comparisons put it at the top end of the market for enterprise analytics. Ayzeo AnswerManiac

Why I'd choose it: if you have dozens of markets, thousands of prompts, multiple competitors, and need historical reporting, this is the category's strongest enterprise option.

Potential downside: expensive and more sales-led than the self-serve alternatives.

2. Peec AI — probably the best value for a global marketing team

Peec is particularly interesting if SOV is the KPI you care about most rather than building a huge enterprise intelligence stack. Independent comparisons specifically highlight its competitive share-of-voice capabilities and multi-country tracking. Ayzeo GEO Agency

I'd shortlist it if you're managing, say:

• 10–30 countries
• multiple languages
• 50–500 strategic prompts per market
• 5–20 competitors
• regular market-by-market SOV reporting

It is considerably easier to justify than an enterprise Profound deployment if you're a marketing team rather than a huge global organization.

3. Otterly.ai — best inexpensive starting point

Otterly is compelling if you want to prove the business case before spending heavily. It tracks mentions, citations, competitors and SOV across major AI surfaces, but its analytics are shallower than Profound. licheo.com Omid Saffari

I'd use it for a pilot rather than a sophisticated global measurement program.

4. Scrunch AI

Worth including in an enterprise RFP, particularly if you want the platform to go beyond measurement into diagnosing and improving AI visibility. Current comparisons put it in the higher-priced enterprise tier. Ayzeo Stork.AI

The feature I'd scrutinize most

Don't just ask vendors whether they support “countries” and “languages.” There are three different dimensions you want them to demonstrate:

Market: US / UK / Germany / France / Japan, etc.

Prompt language: English / German / French / Japanese, etc.

AI-search location: the geographic context presented to the model.

Those aren't necessarily equivalent. A tool saying “we support Germany” doesn't necessarily mean you can run the same German prompt with a German-localized AI experience and compare it against the equivalent French prompt in France.

I'd make vendors run this exact test in the demo:

Same 100 commercial-intent prompts × 10 countries × native language, across ChatGPT, Google AI Overviews/AI Mode, Gemini, Claude and Perplexity. Show me brand SOV, competitor SOV, citations, sentiment, and trend over time, with results segmented by country and language.

If they can't show that natively, I'd be cautious.

My recommendation

If this is a serious multinational measurement program: Profound.

If you're a marketing/SEO team looking for the best balance of SOV analytics, geographic tracking and cost: Peec AI.

If you're testing the category or have a modest budget: Otterly.ai.

One other option worth investigating is ReachLLM, which explicitly positions itself around AI-search visibility across multi-brand enterprises and combines measurement with diagnosis/execution; its current plans start at $399/month. ReachLLM

If you tell me how many countries/languages, approximate number of prompts, and which AI engines matter most, I can give you a much tighter 3–5 vendor shortlist and an RFP-style feature matrix specifically for global AI SOV.

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. 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 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

If you mean “which parts of my website are being surfaced, quoted, or cited by AI answer engines (ChatGPT, Perplexity, Google AI Overviews, Claude, Bing Copilot, etc.)?”, the category is usually called AI visibility / AI search analytics / LLM citation tracking.

Tools that can help:

For specific paragraphs or snippets, rather than just “your site was cited,” the capabilities are more limited. The strongest approaches are usually:

1. Citation extraction
   • Run a set of target prompts in AI engines.
   • Capture answers and cited URLs.
   • Compare cited pages against your HTML/text to find the referenced passages.

2. Content-level instrumentation
   • Add unique phrases or “fingerprints” to important sections (for testing).
   • Monitor whether those phrases appear in AI outputs.

3. Log-based analysis
   • Analyze server logs for AI crawler activity (e.g., GPTBot, ClaudeBot, Google-Extended).
   • Note: crawler visits do not prove that a snippet was used in answers.

4. Search Console + AI visibility tools
   • Combine traditional search queries with AI citation tracking.

If your goal is specifically “show me the exact sentences from my pages that ChatGPT/Perplexity are quoting”, I’d look first at tools like Profound, Peec AI, or Otterly.ai, then supplement with your own prompt testing because exact snippet-level attribution is still an emerging capability and many AI systems do not expose it.

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.

Yes — the category you’re looking for is usually called AI visibility / AI search monitoring / GEO (generative engine optimization) software.

The important distinction is that there are two related measurements:

1. AI Share of Voice (SOV): how often your brand/content is mentioned relative to competitors in AI-generated answers.
2. Citation/source visibility: how often the AI actually cites or links to your URLs as sources.

If your goal is specifically “we publish/crawl content → how often does that content subsequently get surfaced in AI answers?”, I’d look at these:

My shortlist

1. Profound — probably closest to what you're describing

Profound is particularly interesting if you want to connect content → AI crawler activity → AI answer visibility. Its positioning includes AI crawler analytics in addition to monitoring generated answers. That gives you more of the causal chain than a simple “does ChatGPT mention us?” tracker. Profound Geodocs

tryprofound.com

2. OtterlyAI — easiest if you mainly want the SOV number

Otterly runs your defined prompt set across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, then records mentions, rankings, citations and competitors. It explicitly calculates Share of Voice and Brand Coverage. Otterly Otterly AI

otterly.ai

The distinction is useful: Brand Coverage = percentage of answers where you appear; SOV = your proportion of the brand mentions within those answers. Otterly

3. Peec AI — worth evaluating alongside Profound

Peec is another purpose-built AI visibility platform focused on measuring how brands appear across AI engines and comparing them against competitors. It tends to be positioned between enterprise platforms like Profound and lighter-weight monitoring tools. Conbersa The Rank Masters

peec.ai

One important caveat

If by “after crawling” you literally mean:

We know an AI crawler visited URL X on Monday, and we want to know whether URL X subsequently appeared in AI answers on Tuesday/Wednesday.

That's a more sophisticated requirement than ordinary AI SOV tracking.

Most tools do:

Prompt → AI response → mention/citation → SOV

Whereas what you're describing is:

Your content → AI crawler discovers content → content enters model/search index → AI response → URL/content is surfaced → SOV

Profound is one of the more interesting options for the latter because it combines AI-answer monitoring with AI crawler analytics; Otterly, for example, explicitly focuses on answer/citation visibility rather than showing which AI crawlers visited which pages. Profound

So if you tell me whether you're measuring a brand, a large content site/publisher, or an SEO/content agency, I can narrow this down to the 2–3 products that actually fit your use case, including what each one can and can't attribute at the URL/content level.

Yes. What you’re describing is usually called AI search visibility / GEO (Generative Engine Optimization) tracking: crawl/index your site, then repeatedly query AI engines and measure how often your brand/domain/pages are mentioned or cited, usually against competitors.

The strongest options right now are:

The important distinction in your question

There are actually two different measurements you may want:

1. AI Share of Voice — “How often does our brand/content appear in AI answers?”

Otterly, Profound, Peec, Scrunch, etc. are designed for this. For example, Otterly explicitly calculates the share of AI answers in which your brand appears versus competitors and tracks the URLs AI engines cite. Otterly Otterly

2. AI crawler/indexing activity — “Did GPTBot/ClaudeBot/etc. actually crawl our content, and what happened afterward?”

Profound is particularly interesting here. Its Agent Analytics connects AI crawler activity at the CDN level with subsequent citations and traffic, giving you a chain like published page → AI crawler visit → AI citation → referral → conversion. Profound

That second capability sounds particularly close to what you mean by “after crawling.”

If your goal is specifically content-level attribution

I'd shortlist:

Profound → if you want to understand which of our pages are being crawled, which subsequently get cited, and how our AI share of voice changes.

OtterlyAI → if you primarily want a relatively simple dashboard answering “What percentage of relevant AI answers mention us/cite our pages?” It tracks individual cited URLs and can show which of your pages AI engines actually reference. Otterly

Peec AI → worth evaluating if you have a large prompt set or agency/multi-brand use case.

A recent 2026 benchmark of these tools found Otterly and Profound among the most frequently surfaced/cited tools themselves, which is at least a useful indication of their current category prominence. foglift.io

If you tell me whether you mean “our brand is mentioned” or “our actual website/content URL is cited,” I can narrow this down to the 2–3 tools that best measure exactly that—and explain how each calculates AI share of voice.

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.

If your goal is specifically “Are AI assistants recommending/citing us, and is that producing incremental traffic?”, I’d separate the market into AI-visibility measurement and actual traffic attribution. No single platform is perfect at both yet.

My shortlist

These are broadly consistent with current 2026 comparisons: Profound is generally positioned toward enterprise AEO analytics, Otterly toward accessible AI-search monitoring, and Peec toward deeper GEO analytics. TechnologyAdvice ToolChase

1. Profound — my pick for enterprise

tryprofound.com

Profound is probably the closest fit if you're trying to build an “AI search → business impact” measurement program, rather than simply watching whether ChatGPT mentions your brand.

It tracks things such as:

• AI answer visibility
• Brand mentions and sentiment
• Which sources/URLs are cited
• Prompt demand
• AI crawler/agent activity
• Competitive visibility

Its Agent Analytics component is particularly interesting because it moves beyond “what answer did the user see?” toward understanding how AI agents interact with and interpret your website. TechnologyAdvice

Best for: enterprise SEO/GEO, brand teams, PR, and organizations that need executive reporting.

2. OtterlyAI — best starting point

otterly.ai

If you want something you can deploy quickly without buying an enormous enterprise platform, I'd look very closely at Otterly.

It currently tracks ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude, including mentions, citations, sentiment, share of voice and competitor positioning. Otterly Otterly

The particularly useful part for your question is citation tracking: you can see which URLs AI engines are using as sources and how those citations change over time. Otterly

Best for: SaaS/content teams that want an AI equivalent of a traditional rank tracker.

3. Peec AI — best for analyzing why visibility changes

peec.ai

Peec is compelling if your team cares about GEO analytics rather than just a visibility score. It focuses heavily on prompt research, brand monitoring, citations, competitors and recommendations.

I'd put it ahead of Otterly if your primary question is:

“What topics/prompts are changing, which competitors are winning, and what sources are influencing the answers?”

rather than:

“Give me a simple weekly AI visibility report.”

DataDab ToolChase## The important caveat: AI visibility ≠ traffic attribution

This is where I'd be careful when evaluating vendors.

A platform can tell you:

Prompt → AI answer → your brand mentioned → your URL cited

But that's not necessarily:

AI answer → user clicked → user landed on your site → conversion/revenue

For the latter, I'd use the AI-visibility platform alongside your analytics stack.

For example:

AI visibility tool
→ tracks prompts, mentions, citations and share of voice

GA4 / your product analytics
→ tracks AI referral sessions

CRM / attribution system
→ tracks leads, pipeline and revenue

Then build a dashboard around:

• AI mentions
• AI citation rate
• Share of AI voice
• Average position in AI answers
• Number of cited URLs
• AI-referred sessions
• AI-referred engaged sessions
• AI-referred conversions
• AI-referred pipeline/revenue
• Conversion rate vs. organic/direct/referral traffic

That's much more defensible than saying “our ChatGPT visibility increased 40%, therefore AI generated $X.”

What I'd buy

If you're an enterprise: Profound + GA4/CRM

If you're a growth-stage SaaS: OtterlyAI + GA4

If you're an SEO-heavy organization already using Semrush: Semrush's AI Visibility Toolkit rather than adding another standalone system. Current comparisons put Semrush among the stronger options for combining traditional SEO and AI visibility. TechnologyAdvice ToolChase

If AI-referred traffic/revenue is the #1 KPI: I'd also evaluate Scrunch, because its positioning specifically includes AI traffic alongside citation and prompt intelligence. TechnologyAdvice

One thing I'd insist on in a vendor demo

Ask them to demonstrate this exact workflow:

“Show me every AI answer in the last 90 days that mentioned/cited our domain, the exact prompt, the AI engine, the cited URL, whether the user could click it, and then show me how you connect that exposure to an actual website session and conversion.”

If they can only show you visibility scores and screenshots of AI answers, they're an AI rank tracker, not an actual AI traffic attribution platform.

If you tell me your company type (B2B SaaS, ecommerce, publisher, agency, etc.) and approximate monthly organic traffic, I can narrow this to the 2–3 tools I'd actually trial.

The important caveat: AI visibility ≠ traffic attribution

This is where I'd be careful when evaluating vendors.

A platform can tell you:

Prompt → AI answer → your brand mentioned → your URL cited

But that's not necessarily:

AI answer → user clicked → user landed on your site → conversion/revenue

For the latter, I'd use the AI-visibility platform alongside your analytics stack.

For example:

If your goal is long-term LLM visibility tracking across a portfolio of ecommerce sites, I’d shortlist Profound and Peec AI, with Profound as my first choice for a serious multi-site portfolio.

My ranking

1. Profound — best overall

For your use case, this is the one I'd evaluate first.

Profound tracks visibility, share of voice, citations, sentiment, positioning, competitors, regions and topics over time. More importantly for ecommerce, it has a dedicated Shopping product that goes down to the SKU level, tracking product placement, merchant attribution, product attributes and competitive positioning in ChatGPT Shopping. Profound Profound

It also runs tracked prompts daily and says it queries the actual consumer-facing experiences rather than relying solely on model APIs, which is valuable when you're trying to establish a consistent longitudinal dataset. Profound Profound Knowledge Base

Why I'd pick it for a portfolio:

• Multiple brands/sites and competitive sets
• Historical visibility/share-of-voice trends
• Engine-by-engine analysis
• Citation/source tracking
• Product/SKU-level ecommerce visibility
• AI crawler and AI traffic analytics
• Real prompt-volume data
• Stronger enterprise reporting/analysis

The big advantage is that you can eventually connect "Are we being seen?" → "Which products are being recommended?" → "Which sites are influencing the answers?" → "Is AI actually sending us traffic?"

tryprofound.com

2. Peec AI — probably the best alternative

I'd look very closely at Peec if your primary requirement is clean longitudinal visibility analytics rather than a broader enterprise AEO platform.

It explicitly tracks visibility, position, sentiment and share of voice, with daily trends and competitor comparisons. Its dashboard can be segmented by country, topic and model, which is particularly useful when you're managing multiple ecommerce categories/markets. Peec AI Peec.ai Docs

A particularly useful distinction is that Peec separates:

• Brand visibility — AI mentions your brand
• Source visibility — AI actually cites your domain/content

That distinction is extremely useful for ecommerce SEO because being mentioned by an LLM isn't necessarily the same thing as having your product/category pages become trusted sources. Peec.ai Docs

Peec has also added ecommerce-oriented product visibility, including individual-product appearance, win rate, position, share of voice and competitive products in AI shopping results. Peec AI

peec.ai

What I'd actually track

For a portfolio, I wouldn't make "LLM visibility" a single KPI. I'd build a portfolio-level AI visibility scorecard around:

1. Brand visibility %
2. Share of voice vs. competitors
3. Average answer position
4. Citation rate
5. Share of citations to your own domains
6. Product/SKU visibility
7. Category visibility
8. AI Shopping placement
9. Sentiment / attribute accuracy
10. AI-referred sessions and revenue
11. Visibility by engine
12. Visibility by country
13. Visibility by prompt/topic cluster

The important one for an ecommerce portfolio is SKU/category visibility over time. A site can have stable brand visibility while losing its most commercially important product queries to competitors.

Bottom line

If you have 5–50+ ecommerce sites/brands: I'd start with Profound.

If you want a more analytics-focused platform and potentially a simpler deployment: I'd trial Peec AI alongside it.

I would not choose purely based on how many LLMs a vendor claims to monitor. For a multi-year program, the more important question is whether the platform gives you stable prompt cohorts, historical data, competitor baselines, source/citation data, and product-level tracking. Those are what make the dataset useful 12–24 months from now. Peec.ai Docs Profound

If you're choosing this for an agency/portfolio company environment, I can also compare Profound vs Peec vs Otterly vs Scrunch specifically on multi-domain limits, historical data, API/export, pricing, and white-label reporting.

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 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 you mean “tell me when ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, etc. cite one of our URLs in their answers,” you want an AI visibility / AEO (answer-engine optimization) monitoring tool.

My top two:

• otterly.ai — probably the best fit if your primary need is citation monitoring. It tracks your prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and specifically reports which of your URLs are cited and how often. It monitors tracked prompts daily. Otterly Otterly AI
• tryprofound.com — stronger if you're doing this at an enterprise/content-strategy level. It tracks citation visibility across answer engines, lets you analyze citation share by platform/topic/prompt, and identifies the specific pages being cited. Profound Profound

The distinction that matters

There are actually two different things you might want to monitor:

1. “Did an AI assistant mention our brand?”

→ AI visibility/brand monitoring.

2. “Did an AI assistant actually cite/link to our content?”

→ AI citation tracking. This is the more precise tool for what you're describing.

For example, Otterly's citation report can show every cited URL, whether it belongs to you or a competitor, and which AI engines are citing it. Otterly

If your goal is specifically “alert me whenever any AI answer engine cites any article/page on our domain”, I'd lean OtterlyAI for a straightforward monitoring setup, and Profound if you need enterprise-grade analysis and content strategy.

If you tell me roughly how many URLs/content pieces you have and which AI assistants matter most, I can compare Otterly vs. Profound vs. Peec vs. Semrush and tell you which is the best fit.

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 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.