Positive mentions of Peec AI

For a marketing agency managing many client brands, I’d shortlist Peec AI and OtterlyAI, with Peec AI looking particularly well-suited to an agency workflow.

My recommendation: Peec AI

Peec AI is explicitly built around agency/multi-client use. Its agency setup gives you separate client workspaces under one account, centralized billing, flexible prompt allocation, and client-facing reporting. Peec AI Peec AI

It tracks Share of Voice as well as visibility, mentions, position, citations and sentiment across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini and Microsoft Copilot. Peec AI Peec AI

For an agency, the particularly useful pieces are:

• Separate workspace per client — keeps brands, competitors and prompts isolated.
• One account for your whole agency — rather than maintaining separate subscriptions/logins.
• Flexible prompt allocation — shift monitoring capacity toward larger or more important accounts.
• Automated reporting — including branded client dashboards and exports/API access.
• Multi-channel monitoring — useful if your definition of "AI share of voice" spans both chat assistants and Google's AI search experiences.
• Agency automation via MCP — Peec says you can automate weekly rollups across clients and generate summaries for Slack/Google Slides. Peec AI

peec.ai

Strong alternative: OtterlyAI

OtterlyAI is also compelling if client separation and scale are your primary concern. Its Workspaces are specifically designed for agencies managing dozens or hundreds of brands, with separate team access, reports and data for each client. Otterly Otterly.ai

It monitors the same six major AI/search surfaces and offers competitor comparisons, citation analysis, sentiment, exports and a Looker Studio connector. Otterly Otterly

otterly.ai

How I'd choose

Bottom line: I'd start with Peec AI for a marketing agency, particularly if you're selling ongoing AI-search/GEO retainers and need to turn SOV data into recurring client reports. I'd put OtterlyAI through the same trial if you have a very large client roster and want rigid workspace separation.

One thing I'd verify in demos: how they define and calculate SOV, because "visibility" and "share of voice" aren't interchangeable. Peec explicitly defines SOV as a brand's proportion of all tracked-brand mentions, rather than simply the percentage of answers where the brand appears. Peec AI

If you tell me roughly how many clients/brands you manage (e.g. 10, 50, 200+) and how many prompts per client, I can compare the likely economics and reporting setup of Peec vs. OtterlyAI for your agency.

For a marketing agency managing multiple client brands, I’d prioritize platforms that support:

• Multi-brand / multi-project workspaces
• Competitor tracking per client
• Prompt libraries (buyer-intent queries, not just keywords)
• Tracking across multiple AI assistants (ChatGPT, Gemini, Claude, Perplexity, Google AI surfaces, Copilot, etc.)
• Client-ready reporting or exports
• Historical trend tracking (AI share of voice over time)

Here are the platforms I’d shortlist:

A few other tools worth evaluating:

• ViAudit — tracks brand presence across ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, Copilot, and Grok, with competitor share-of-voice reporting. Viaudit
• Latentline — explicitly supports agency use cases with multi-project reporting, team roles, exports, and client-facing workflows. Latentline
• WebGlazer — focuses on monitoring how AI assistants describe brands and competitors across several engines. WebGlazer

My agency-oriented shortlist

For a large agency / enterprise clients

Start with:

1. Profound
2. Scrunch AI
3. Latentline

Look for:

• API access
• white-label reporting
• user permissions
• many brands under one account

For a boutique or mid-size agency

Start with:

1. OtterlyAI
2. Peec AI
3. OpenLens
4. ViAudit

They’re more likely to fit recurring monthly reporting packages without enterprise overhead.

Questions I’d ask vendors before buying

1. How many brands are included?

Some tools price by tracked domain, so 50 clients can become expensive.

2. Can each client have isolated dashboards?

You don’t want Client A seeing Client B’s competitors.

3. Do they store raw AI responses?

This matters when clients ask “why did ChatGPT recommend our competitor?”

4. Can you customize prompts by client?

Generic prompts create weak share-of-voice data.

5. Do they measure citations as well as mentions?

Being named and being cited are different signals.

For a marketing agency specifically, I would lean toward a platform with multi-project reporting + client dashboards, rather than a single-brand AI rank tracker. Latentline OpenLens

If you tell me roughly whether you manage 5–10 clients, 50+ clients, or enterprise accounts, and whether you need white-label reports, I can narrow this to a top 2–3.

For a mid-market SaaS team, I’d shortlist Profound, Peec AI, and OtterlyAI. They all cover the core use case—competitor mentions/share of voice plus citation tracking—but their strengths differ.

What I'd look at closely

• Profound — particularly good if the question is “Which competitors are winning citations, on which prompts, and which pages/sources are responsible?” It tracks citation share, visibility rank, competitor changes, prompt-level gaps, and head-to-head content comparisons. Profound
• Peec AI — has explicit Share of Voice, visibility, position, competitor benchmarking, and source/citation analysis. Its citation gap analysis identifies sources where competitors are cited but you aren't, which is useful for turning the dashboard into an outreach/content list. Peec AI Peec AI
• OtterlyAI — especially interesting if you want straightforward ongoing monitoring. It tracks SOV versus competitors, individual cited URLs, citation frequency, and changes in citation position, with breakdowns by prompt, engine, and market. Otterly Otterly

For a SaaS team, I'd define the dashboard around 5 metrics

1. AI Share of Voice — your brand mentions divided by total tracked competitor mentions.
2. Brand coverage — % of relevant AI answers mentioning you at all.
3. Citation share — % of citations going to your domain versus competitors.
4. Citation gap — domains/URLs that cite competitors but not you.
5. Trend by engine + prompt — e.g. ChatGPT vs. Perplexity vs. Gemini, and “best X software,” “X alternatives,” “X for enterprise,” etc.

That distinction between coverage/SOV and citation share matters: you can be mentioned frequently while competitors still own the sources AI systems rely on. Peec and Profound both explicitly expose this distinction. Peec AI Profound

My practical starting point: demo Profound and Peec AI side-by-side, then use OtterlyAI as the comparison if budget/simplicity matters. I wouldn't choose based merely on number of AI engines; I'd test each against your actual 30–100 high-value SaaS prompts and see whether the competitor/citation data is actionable.

If you tell me roughly ARR/team size and how many competitors you want to track, I can also compare these three on pricing, prompt limits, API/reporting, engine coverage, and agency/team features.

For a startup with no developers and a tight budget, I’d look at OtterlyAI first. It monitors brand mentions across ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot, and Claude, with no-code prompt tracking. Its entry pricing is around $29/month. Otterly G2 otterly.ai

Alternative: Peec AI offers daily tracking and visibility metrics, but its Starter plan is about $95/month. peec.ai peec.ai

If your goal is specifically “alert me whenever an AI assistant mentions my brand,” I’d verify whether you need real-time alerts versus daily/weekly monitoring—these platforms primarily work by repeatedly testing predefined prompts. Otterly

If the requirement is specifically historical, enterprise-grade measurement of how your brand is represented across AI models, I’d shortlist Profound first, with Peec AI and Scrunch as comparison points.

Why I'd start with Profound

Profound is particularly aligned with your description: it is designed around systematically querying AI answer engines and measuring brand mentions, competitors, citations, prompts and changes over time, rather than simply doing a one-off audit. Current comparisons describe its enterprise offering as covering a particularly broad set of AI surfaces, including ChatGPT, Perplexity, Gemini, Google AI surfaces, Copilot, Claude and others. Bloomiro Geohats

For an enterprise procurement process, I'd specifically investigate:

• Historical time series: Can you retain raw observations indefinitely, rather than only displaying rolling aggregates?
• Model/version segmentation: Can you distinguish model changes from actual changes in brand visibility?
• Prompt-level history: Can you see exactly what the model said on a particular date?
• Citation/source history: Which publications, websites and pages caused the model to mention your brand?
• Competitor benchmarking: Can you compare your share of mentions against a defined competitive set?
• Geography/language: Can you separate US vs. UK vs. Germany, etc.?
• API/data export: Can you put the underlying observations into Snowflake/BigQuery rather than keeping the data trapped in the dashboard?
• Enterprise security: SSO/SAML, SOC 2, RBAC, auditability and contractual data-retention terms.
• Model-change handling: This is particularly important for historical analytics. A model upgrade can change answers even when your underlying brand presence hasn't changed.

Current industry comparisons identify Profound as the deepest enterprise-oriented option and report enterprise capabilities such as SSO/SAML, SOC 2 and API access. Those are vendor/comparison claims, so I'd verify them directly during procurement. Geohats

The important distinction

I'd avoid buying purely on the number of "AI models supported."

For your use case, the real asset is the historical dataset:

Prompt × date × model/surface × geography × brand response × competitors × citations × source pages

That lets your analytics team answer questions such as:

• "When did our visibility decline?"
• "Was the decline isolated to ChatGPT or also present in Gemini and Perplexity?"
• "Which competitors gained the mentions we lost?"
• "Which publishers/websites are repeatedly being cited instead of us?"
• "Did our visibility change after a particular product launch or PR event?"
• "Are model changes responsible for the apparent trend?"

That's much more valuable than a generic "AI visibility score."

My procurement approach

I'd run a 2–4 week bake-off with Profound, Peec and Scrunch using the same 100–500 prompts representing your actual customer journeys. Don't let vendors supply the benchmark prompts.

Require each vendor to provide:

1. Raw prompt/response history.
2. Daily or weekly observations.
3. Model/engine identification.
4. Citation-level data.
5. Competitor mentions.
6. Historical exports/API.
7. Data-retention policy.
8. Model-version/change methodology.
9. SSO/RBAC/security documentation.
10. A sample enterprise dashboard for marketing + executive reporting.

One particularly important test: ask each vendor to reproduce the same historical metric from raw data. If you can't reconstruct their headline "visibility" number yourself, you're buying a dashboard rather than an analytics dataset.

For a large enterprise, I'd therefore put Profound at the top of the initial RFP, while giving Peec AI and Scrunch a serious evaluation rather than assuming one vendor's marketing claims are definitive. Independent 2026 comparisons consistently place those three among the principal enterprise/mid-market options, although their assessments are not vendor-neutral. Bloomiro Toolsolved

If you tell me roughly company size, number of brands/products, countries, and whether you need API/raw-data access, I can narrow this to an enterprise shortlist and give you a vendor-by-vendor RFP scorecard.

I'd run a 2–4 week bake-off with Profound, Peec and Scrunch using the same 100–500 prompts representing your actual customer journeys. Don't let vendors supply the benchmark prompts.

Require each vendor to provide:

1. Raw prompt/response history.
2. Daily or weekly observations.
3. Model/engine identification.
4. Citation-level data.
5. Competitor mentions.
6. Historical exports/API.
7. Data-retention policy.
8. Model-version/change methodology.
9. SSO/RBAC/security documentation.
10. A sample enterprise dashboard for marketing + executive reporting.

One particularly important test: ask each vendor to reproduce the same historical metric from raw data. If you can't reconstruct their headline "visibility" number yourself, you're buying a dashboard rather than an analytics dataset.

For a large enterprise, I'd therefore put Profound at the top of the initial RFP, while giving Peec AI and Scrunch a serious evaluation rather than assuming one vendor's marketing claims are definitive. Independent 2026 comparisons consistently place those three among the principal enterprise/mid-market options, although their assessments are not vendor-neutral.

If you run a multilingual, multi-region site, I’d shortlist platforms based specifically on whether they can separate language + country/market + AI engine + citations, rather than just giving you one global “AI visibility” score.

My shortlist

• ahrefs.com — probably the strongest fit if you already use Ahrefs. It tracks AI mentions and citations across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews/AI Mode and Claude, and lets you research regions and custom prompts. It also distinguishes mentioned from actually cited pages/domains. Ahrefs Help Center Ahrefs
• Profound — worth evaluating if you need an enterprise-oriented GEO platform with broad AI-engine coverage and detailed prompt/answer monitoring. Current comparisons report coverage across ChatGPT, Perplexity, Claude, Gemini, Grok, Copilot, DeepSeek and Google AI Overviews. Austin Heaton Hiveminds
• Peec AI — another good specialist option for monitoring AI visibility and cited sources, particularly if you want a dedicated GEO/AEO workflow rather than an SEO suite. Austin Heaton Hiveminds
• Otterly.AI — useful for ongoing prompt-level monitoring and citation tracking, with a lower-cost entry point than some enterprise platforms. Austin Heaton
• Semrush AI Visibility Toolkit — makes sense if your organization already lives in Semrush and wants AI visibility incorporated into the existing SEO stack. Its current coverage includes ChatGPT, Google AI Overviews, Google AI Mode, Gemini and Perplexity. Hiveminds

For your particular use case

I'd put Ahrefs Brand Radar and Profound at the top of the evaluation list, but test them with your actual markets before buying.

The important question isn't simply “does it support multiple languages?” It's:

Can I run the same intent set independently in Germany/German, France/French, Japan/Japanese, US/English, etc., and see which URLs/domains each AI engine cites?

You want a dashboard roughly like:

That last distinction—mention vs citation vs which specific localized URL was cited—is particularly important for a multilingual site. Ahrefs explicitly reports citations separately from pages that were merely found/retrieved by the AI system. Ahrefs Help Center

One caveat: AI-visibility datasets are still sampling systems, not a complete measurement of every answer users receive. Ahrefs, for example, says its metrics are based on large sets of search-backed prompts rather than private conversations or every real-world AI interaction. Ahrefs

If you tell me which languages/countries you operate in and roughly how many prompts/markets you need to monitor, I can narrow this to 2–3 platforms and compare their language/geo coverage, citation tracking, prompt volume, API/export capabilities, and pricing.

Yes. For a multi-language, multi-region site, I’d specifically look for a platform that tracks prompt × language × country × AI engine, and exposes the actual cited URLs, rather than giving you only a blended “AI visibility score.”

Based on current 2026 capabilities:

Otterly is particularly aligned with your use case: it explicitly advertises 65+ countries and languages, tracks every citation and cited URL, and lets you analyze performance market-by-market rather than collapsing everything into a global figure. Otterly Otterly

Profound is worth looking at if you're an enterprise and need higher-volume prompt monitoring and detailed citation analysis across many AI systems. Current comparisons document coverage across ChatGPT, Perplexity, Claude, Gemini, Grok, Copilot, DeepSeek and Google AI Overviews. Hiveminds

Peec AI is another good candidate if your emphasis is separating brand mentions from actual source citations and comparing markets/competitors. Hiveminds

What I'd test in a demo

For your situation, don't just ask “does it support multiple languages?” Ask the vendor to demonstrate something like:

Germany + German + ChatGPT + 50 prompts → which URLs are cited?

Then:

US + English + same prompts → how does the citation set change?

And ideally:

France + French + same intent → which competitors are cited instead of us?

You want to be able to see citation URL, cited domain, prompt, language, country, engine, date, competitor and historical change. The distinction between mentioned and actually cited is important—different tools can produce substantially different visibility numbers depending on how they measure it. Austin Heaton

If you tell me roughly how many languages/countries you operate in (e.g. 10 languages × 30 countries) and whether you're enterprise or SMB, I can narrow this to 2–3 platforms and compare their geographic/language tracking, citation depth, API/export capabilities, and likely cost.

If the core requirement is “show me the exact URL/page that caused an AI answer to cite or mention us”, I’d shortlist these:

What I'd test in the evaluation

Don't just ask vendors whether they "track citations." Test whether they preserve the full citation chain:

prompt → AI engine → answer → cited URL → canonical URL → domain → page/topic → citation frequency

The canonical URL part is particularly important. A raw citation might be:

https://example.com/article?utm_source=...

while the content's canonical is:

https://example.com/article/

You want the platform to normalize those into one page rather than treating every URL variant as a separate citation.

I'd also require:

• Exact cited URL, not merely “your domain was mentioned.”
• Raw AI answer/source evidence, so you can audit how the citation was detected.
• Canonicalization/deduplication across redirects, parameters, trailing slashes, etc.
• Owned vs. competitor vs. third-party source classification.
• Prompt → citation attribution, so you can identify which questions each page is actually winning.
• Engine-specific tracking, since citation behavior differs between ChatGPT, Gemini, Perplexity, Google AI experiences, Claude, etc.
• Historical snapshots, rather than only the current citation state.
• Export/API access if you intend to pipe citation data into your own content or BI system.

For your particular use case, I'd put OtterlyAI, Zumi, Profound, Peec AI, and PageLens through the same 50–100 prompt test and compare the actual URL-level output, rather than comparing their marketing metrics. Different platforms can produce substantially different visibility measurements because their prompt sampling and engine access differ. Austin Heaton ayzeo.com

If you tell me whether you're evaluating these for SEO/content teams, an agency, or an enterprise analytics stack, I can turn this into a more rigorous vendor scorecard with API, canonicalization, raw-answer evidence, engine coverage, historical data, and pricing.

The canonical URL part is particularly important. A raw citation might be:

Yes. If your core requirement is “show me the exact page/URL that caused an AI answer to cite or mention us”, I’d shortlist these:

My recommendation

For your particular evaluation, I'd run a 3-vendor bake-off: Profound vs. OtterlyAI vs. Peec AI.

The important distinction is that you don't merely want brand visibility. You want a data model roughly like:

Prompt → AI engine → generated answer → cited URL → canonical URL → your domain/page → citation frequency → competitors cited

Otterly is particularly explicit about this workflow: its citation details can show which prompts and engines cited a specific URL, the citation trend over time, and the underlying answer. Otterly

I'd also make canonicalization a hard requirement in the evaluation. A lot of platforms can tell you that example.com/blog/foo?utm_source=x was cited; what you really want is the ability to normalize that to:

https://example.com/blog/foo

and aggregate all citation events against the canonical content asset.

Evaluation criteria I'd use

1. Exact cited URL available?

Not merely “your domain appeared.”

2. Raw AI answer retained?

You should be able to audit why the URL was counted.

3. Prompt → citation relationship?

Can you go from a page back to every prompt that cited it?

4. Canonical URL normalization?

Critical if your site has parameters, redirects, syndication, HTTP/HTTPS variants, etc.

5. Citation vs. mention separation?

A model saying “Acme is good” is fundamentally different from citing acme.com/research/report.

6. Third-party citation mapping?

Ideally it should tell you not only which of your pages are cited, but which other websites/pages are influencing answers about your category. Otterly, for example, explicitly exposes cited competitor and third-party URLs. Otterly

7. Historical citation data + API/export?

You’ll eventually want to join citation events to GA4, Search Console, CRM/revenue, and your content inventory.

8. Engine-level granularity: ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, etc.

One conceptual point I'd emphasize to the team: citation count alone isn't enough. Recent research distinguishes between a page being selected as a citation and the information from that page actually being absorbed into the generated answer. arXiv So if you're building a serious measurement stack, I'd ask vendors whether they expose the citation + surrounding answer/evidence, rather than just a citation score.

If you tell me whether you're B2B, ecommerce, publisher, or SaaS, I can turn this into a tighter vendor scorecard with ~15 requirements and suggested weights for your platform evaluation.

Prompt → AI engine → generated answer → cited URL → canonical URL → your domain/page → citation frequency → competitors cited

Otterly is particularly explicit about this workflow: its citation details can show which prompts and engines cited a specific URL, the citation trend over time, and the underlying answer. Otterly

I'd also make canonicalization a hard requirement in the evaluation. A lot of platforms can tell you that example.com/blog/foo?utm_source=x was cited; what you really want is the ability to normalize that to:

https://example.com/blog/foo

and aggregate all citation events against the canonical content asset.

Evaluation criteria I'd use

If by AI citation monitoring you mean tracking which pages/brands are cited inside ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude, etc. and then feeding that data into your existing analytics/reporting stack, I’d focus on platforms with API access, raw citation data, and warehouse/BI integrations, rather than just a standalone dashboard.

Platforms worth evaluating

These capabilities are supported by current vendor/industry documentation; integration details and plan availability vary by tier. Toolsolved Ahrefs NBound Marketing

If you have a modern data stack

I'd architect it roughly like:

AI citation platform → API/webhook → warehouse → dbt/modeling → BI

For example:

Scrunch/Promptwatch/Profound → Snowflake/BigQuery → Looker/Tableau/Power BI

That gives you the ability to join citation data against things you already measure:

• organic traffic
• conversions/revenue
• landing pages
• CRM pipeline
• customer segments
• campaigns
• traditional SEO rankings
• AI referral traffic

This is more useful than treating "AI visibility score" as another isolated marketing KPI. In particular, Promptwatch is explicitly positioned around API/Looker Studio/raw citation-data integration, while Semrush's API can feed tools including Looker Studio, Tableau, Power BI, BigQuery, Snowflake, Salesforce and HubSpot. Toolsolved Semrush Developer

My shortlist by architecture

If you're building an analytics product/pipeline:
Promptwatch or Scrunch — prioritize their API/webhook capabilities and inspect whether the returned data has the granularity you need.

If you're already a Semrush shop:
Semrush AI visibility is worth evaluating before adding another vendor, because the API can plug into the rest of your existing SEO data infrastructure. Semrush Developer

If you're already on Ahrefs:
Ahrefs Brand Radar is particularly interesting because its Data Studio connector exposes historical AI mentions, impressions and AI Share of Voice. Ahrefs

If this is enterprise-grade and you need very deep prompt/citation analytics:
Profound is one of the platforms I'd put through a technical evaluation, particularly if governance, breadth of AI engines and granular prompt analytics matter. Distribution.studio

One important procurement question: don't just ask "does it have an API?" Ask whether the API exposes the individual citation URL, prompt, engine, timestamp, competitor, response and citation position/context. That determines whether you can actually integrate it into your analytics model rather than merely export a visibility score. Current comparisons specifically highlight granular/page-level citation data as an important differentiator. Toolsolved

If you tell me your existing stack (e.g. GA4 + BigQuery + Looker, Snowflake + Tableau, Segment + Amplitude, HubSpot + Salesforce, etc.), I can narrow this to the 2–3 integrations that fit it best.

Yes. What you’re describing is slightly narrower—and potentially more valuable—than the usual AI visibility/AEO tracker category.

The distinction is:

• AI visibility tools: “Does ChatGPT/Perplexity/Gemini mention or cite my brand?”
• Citation intelligence: “Which URLs are AI systems actually using as sources?”
• Predictive source intelligence: “Given a page/topic/query, which pages are most likely to be selected as sources by AI—and why?”

That third capability is emerging, but it is not yet a fully standardized product category.

Products worth looking at

Otterly is particularly interesting for your exact use case because its current product explicitly describes “Content Audit & Prediction” and says it provides a predictive score for whether a page can become an AI source. Otterly

The broader market is heavily concentrated around monitoring actual citations rather than predicting them. Current comparisons describe Profound, Peec, Otterly and similar products primarily as platforms that test prompts and record which brands/domains AI systems actually cite. GeoHero Austin Heaton

The gap I would pay attention to

There is a potentially important distinction between “AI visibility software” and what you're describing:

Source-selection prediction at the URL level.

Imagine entering:

“best accounting software for a 20-person SaaS company”

and getting:

And then, critically:

“These 12 pages are the sources most likely to be selected by ChatGPT/Perplexity/Gemini for this query.”

That is materially different from simply saying “your brand appeared in 17% of AI answers.”

There is research supporting the idea that source selection can be modeled using page-level characteristics. A 2026 study analyzing more than 21,000 search-layer citations found that highly influential cited pages tended to be longer, more structured, semantically aligned with the query, and rich in extractable evidence such as definitions, numbers, comparisons and procedures. arXiv

If you're evaluating competitors for this specific capability

I'd investigate Otterly first, then Profound, but I'd ask each vendor a very specific question:

“Can you give me a ranked prediction of URLs that have not yet been cited for a query, with a probability/likelihood score explaining why each URL is likely to be selected as a source?”

That wording matters.

A lot of products call something “AI visibility prediction” when they're really doing historical citation measurement + recommendations. Those aren't the same thing.

For example, Otterly explicitly advertises a predictive content score, whereas Profound's documented strength is much more around URL-level citation intelligence and analyzing actual AI search behavior. Otterly Nick Lafferty

If you're thinking about building this

I think the interesting product isn't another dashboard saying “you were cited 14% of the time.”

It would be a Source Selection Intelligence API:

1. Input: query/topic + corpus of candidate URLs.
2. Retrieve/search the web.
3. Analyze every candidate page.
4. Model historical AI citation behavior.
5. Output a ranked list of likely AI sources.
6. Explain the prediction with page-level signals.
7. Optionally predict which passage/claim will be extracted.
8. Continuously compare prediction against actual ChatGPT/Perplexity/Gemini citations and retrain.

That would essentially be “Google Search ranking prediction, but for AI citations.”

And that's a noticeably different positioning from the crowded AI-visibility-monitoring market. GeoHero GetIntel

If you're evaluating this as a startup/product opportunity, I can also map the current vendors into “already does it / partially does it / white space” and identify exactly what predictive capabilities appear to be missing.

There is a potentially important distinction between “AI visibility software” and what you're describing:

Source-selection prediction at the URL level.

Imagine entering:

“best accounting software for a 20-person SaaS company”

and getting:

And then, critically:

“These 12 pages are the sources most likely to be selected by ChatGPT/Perplexity/Gemini for this query.”

That is materially different from simply saying “your brand appeared in 17% of AI answers.”

There is research supporting the idea that source selection can be modeled using page-level characteristics. A 2026 study analyzing more than 21,000 search-layer citations found that highly influential cited pages tended to be longer, more structured, semantically aligned with the query, and rich in extractable evidence such as definitions, numbers, comparisons and procedures. arXiv

If you're evaluating competitors for this specific capability

I'd investigate Otterly first, then Profound, but I'd ask each vendor a very specific question:

“Can you give me a ranked prediction of URLs that have not yet been cited for a query, with a probability/likelihood score explaining why each URL is likely to be selected as a source?”

That wording matters.

A lot of products call something “AI visibility prediction” when they're really doing historical citation measurement + recommendations. Those aren't the same thing.

For example, Otterly explicitly advertises a predictive content score, whereas Profound's documented strength is much more around URL-level citation intelligence and analyzing actual AI search behavior.

If you're thinking about building this

I think the interesting product isn't another dashboard saying “you were cited 14% of the time.”

It would be a Source Selection Intelligence API:

Yes — this is now a distinct category usually called AI visibility / GEO (Generative Engine Optimization) platforms. They run your target questions through AI search/assistants and track whether your brand and your domain/pages are mentioned or cited, often alongside competitors. UX Continuum Austin Heaton

Platforms I'd look at

• tryprofound.com — enterprise-oriented. Strongest fit if you want deep citation/source intelligence, large prompt sets, and monitoring across many AI surfaces. SEO Counselors UX Continuum
• peec.ai — geared toward marketing/SEO teams; particularly useful for seeing which prompts competitors appear for and where you don't. Toolsolved UX Continuum
• otterly.ai — a lower-cost way to continuously monitor AI mentions/citations across multiple engines. Geohats UX Continuum
• ahrefs.com — especially interesting if you're already an Ahrefs user. Its current index uses hundreds of millions of prompts and separates mentions from actual citations. Ahrefs Ahrefs
• rankscope.ai — focused specifically on citation rate, share of voice, cited sources, and identifying what sources AI engines trust. RankScope

The important distinction

If your goal is "find where our site is being cited and tell me how to improve it," don't buy a platform merely because it gives you an AI visibility score.

You want it to expose at least:

1. The exact prompts being tested.
2. The complete AI response, not just a score.
3. Whether you were mentioned vs. actually cited.
4. The exact URL/page that was cited.
5. Which competitors were cited instead.
6. Which third-party sources AI relied on when recommending competitors.
7. Prompt-level gaps — e.g. "you appear for 18/50 relevant questions, while Competitor X appears for 37/50."
8. Recommendations for which content/pages/authority signals to improve.

That's important because being named and having your website cited as a source are materially different things. Austin Heaton Ahrefs

If I were evaluating these for a company today, I'd put Profound, Peec, Otterly, and Ahrefs on the initial shortlist and test them against ~50–100 real questions your prospects ask AI assistants. The resulting citation URLs and competitor/source gaps will tell you much more than the marketing pages.

If you tell me your website + industry + approximate company size, I can also research the current options and give you a side-by-side comparison of the platforms specifically for your use case, including pricing, AI engines covered, citation-level data, and how much they actually help with optimization.

Yes — but there’s an important distinction.

If by “exact prompts” you mean the actual questions people are typing into ChatGPT/Perplexity/Gemini that result in your site being cited, there are now tools getting surprisingly close. But no tool can give you a complete, first-party log of every user's private ChatGPT prompt.

The tools I'd look at as a solo SEO freelancer

• tryprofound.com — probably the closest match to what you're describing. Its Prompt Volumes dataset is built from real, anonymized AI conversations, and it says you can search for a URL and see the prompts that cause AI engines to cite that page, including platform and volume data. Profound Profound Help Center
• otterly.ai — more geared toward an SEO freelancer who wants a practical monitoring/reporting platform. You give it prompts to track, and it records the exact prompt, AI response, mentions, and URLs cited. It also has AI Prompt Research to generate likely prompts from keywords, domains, or industries. Otterly AI Otterly AI
• peec.ai — another option for monitoring AI visibility. It tracks which prompts produce mentions and which sources are cited, with visibility/share-of-voice metrics. Peec AI

The distinction that matters

There are really three levels of data:

Profound is particularly interesting because it claims access to a large dataset of real AI conversations, rather than simply having an LLM invent likely prompts. Profound Profound

For a solo SEO freelancer, I'd think about it this way:

Profound = research into what people are actually asking AI

OtterlyAI = practical client-facing AI visibility monitoring

And there's a particularly useful workflow here:

Real prompts → prompts that cite competitors → pages being cited → why those pages are being cited → content recommendations for your client

That's much more actionable than simply reporting “your brand appeared in ChatGPT 23% of the time.”

One caveat: don't confuse the prompt that produced an AI answer with the search queries an AI model generated behind the scenes. Modern answer engines can fan out a user's prompt into multiple searches before constructing the answer. Profound, for example, explicitly tracks these “query fanouts.” Profound Help Center

If you're considering this specifically as a solo freelancer service, I can also break down which of these tools gives you the most useful data for selling an “AI SEO/GEO audit” to clients, including approximate pricing and what you could actually deliver in a $500–$2,000 audit.

If by “exact snippets” you mean the actual AI answers plus the URLs/sources the assistant cited, rather than just an AI-visibility score, there are a few tools worth looking at.

My shortlist for a content strategist

• otterly.ai — probably the closest match to what you're describing. Its prompt-level analysis exposes the detailed AI response and the citations/URLs used as sources, and it lets you track those prompts over time. It also provides content-gap and citation-oriented optimization guidance. Otterly AI Otterly AI
• tryprofound.com — more enterprise-oriented. It's designed for monitoring AI answers, citations, competitors, and visibility across multiple AI engines. Useful if you're running GEO/AEO at larger scale. Meridian15 Agentic SEO Tools
• peec.ai — strong for analyzing AI visibility and competitive citation patterns. I'd consider it when your job involves reporting and benchmarking across many prompts/competitors. Geohats Conbersa
• Semrush AI Visibility Toolkit — worth considering if your team already uses Semrush, since it combines conventional SEO data with AI-search visibility rather than requiring another standalone platform. ToolChase

The distinction I'd make

For your particular use case, you want a workflow like:

Buyer prompt → exact AI response → sources cited → which passage/page was used → competitor cited instead → content change → re-test

That's considerably more useful to a content strategist than a dashboard saying “your AI visibility score is 37.”

Otterly is particularly interesting because its current documentation explicitly exposes Responses and Citations at the prompt level, and its optimization workflow recommends examining which URLs are already being cited for the prompts you care about. Otterly AI Otterly AI

One caveat: don't interpret an extracted “snippet” as the permanent passage an AI model uses. AI answers and their sources can change between runs; Otterly's recent research, for example, found that citations can be less stable than brand mentions. Otterly

If I were setting up a content-strategy stack, I'd prioritize a tool that lets me see the raw response + citations over one that only gives me an AI visibility score.

If you tell me whether you're doing B2B SaaS, ecommerce, publishing/media, or agency work, I can narrow this to the 2–3 tools that fit that workflow and compare exact response visibility, citation extraction, content recommendations, competitor analysis, and price.

If your agency’s specific goal is “Which of our clients’ blog articles are being cited or used as sources inside ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, etc.?”, I’d evaluate these a little differently from ordinary “AI visibility” software.

My shortlist

Recent 2026 comparisons consistently identify Profound, Peec, Otterly, Scrunch, Ahrefs and Semrush as the major options in this category, although capabilities and pricing are changing quickly. Baarely UX Continuum

For your use case, I'd look hardest at Peec and Profound

Peec AI is particularly interesting for an agency because it separates brand mentions from source citations, which is important for what you're asking. You don't just want to know “Client X appeared in 27% of answers.” You want to know:

“The client's article /blog/best-crm-for-small-business/ was cited in 14 answers, across these prompts and these engines.”

That distinction is critical for demonstrating the value of your content program. Recent comparisons specifically call out Peec's citation/mention separation and agency-oriented reporting capabilities. StayFound

Profound is the one I'd investigate if your clients are larger and you're willing to pay for significantly deeper data. Its higher tiers cover a broad range of answer engines and provide substantially more enterprise-oriented analytics. Baarely

One important distinction

There are actually three different metrics that vendors sometimes lump together as “AI visibility”:

1. Brand mention — “ChatGPT mentioned Acme.”
2. Citation/source — “ChatGPT cited Acme's specific blog URL.”
3. AI-attributed traffic — “An AI engine actually sent a visitor to that URL.”

For a content marketing agency, #2 is probably your most interesting KPI, while #3 is the eventual business KPI.

I'd therefore ask every vendor to demonstrate this exact workflow before buying:

Give the system 100–300 real buyer questions → run them against ChatGPT/Perplexity/Gemini/Google AI → show every citation → map citations back to individual URLs on our clients' domains → show changes over time → export that data per client.

If a product primarily gives you mention rate / share of voice, but can't reliably expose the specific cited URL, I'd consider that a different product from what you're looking for.

What I'd want in an agency stack

For each client, ideally you can produce something like:

• 1,000 tracked buyer prompts
• AI visibility by engine
• Citation rate
• Citations by URL
• New/lost citations month-over-month
• Which competitors' URLs are being cited instead
• Citation rate by content cluster
• Questions where your client has zero citations
• Questions where the client is mentioned but another website supplies the citation
• AI crawler activity on the client's site
• Historical snapshots of actual AI answers
• Client-specific dashboards
• White-label PDF/Looker Studio/API reporting

That last-but-one point matters: an answer saying your client is an authority is not the same as an AI engine actually citing your client's content.

There is also growing evidence that editorial/third-party sources are a major component of AI references, so I'd avoid restricting your monitoring to your own domain. vogue.com

My practical recommendation

If I were building this into a marketing-agency service, I'd demo Peec AI and Profound first, then use Otterly as the lower-cost benchmark.

I'd specifically compare them on URL-level citation extraction, not their headline “AI visibility score.”

If you tell me roughly how many clients you manage (e.g. 10, 50, 200), monthly budget, and which engines matter most, I can do a much more useful agency-specific comparison of Peec vs Profound vs Otterly vs Ahrefs/Semrush, including current pricing, API/export capabilities, white-label reporting, and exactly how well each handles blog-URL citation tracking. Baarely bloomiro.com

My practical recommendation

If I were building this into a marketing-agency service, I'd demo Peec AI and Profound first, then use Otterly as the lower-cost benchmark.

I'd specifically compare them on URL-level citation extraction, not their headline “AI visibility score.”

If your specific question is “Which of our FAQ pages are actually being used as sources by AI assistants, how often, and by which assistants?”, I’d look first at otterly.ai.

• Citation-level analytics: it tracks the URLs AI engines cite, including how often each URL is cited. Otterly Otterly
• Page-level visibility: you can see which of your pages are cited versus ignored, rather than just measuring whether your brand was mentioned. Otterly
• Assistant coverage: it monitors ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly
• Prompt → answer → citation: its prompt-detail views let you inspect the actual AI response and the URLs used as sources. Otterly
• AI-agent visits: its newer Agent Analytics can additionally show which pages AI agents actually visit and the breakdown by agent/engine. That is useful for distinguishing “AI cited this page” from “AI actually fetched this page.” Otterly

One important distinction

If by “how frequently our FAQ content is used” you mean actual customer questions being answered using your FAQ, rather than whether your URLs appear as citations, I'd pair an AI visibility tool with your own analytics/log data.

For example:

FAQ page → AI crawler/fetch → AI citation → AI answer → referral/conversion

Otterly can give you much of the middle of that chain. It won't magically know every time an LLM internally uses your content without fetching or citing it.

Also worth evaluating: Peec AI

peec.ai is particularly relevant if you want a URL-by-URL content report. Its current tooling describes retrieval rate, citation count, AI models citing each URL, and changes versus the previous period. Peec AI

So I'd shortlist:

1. OtterlyAI — best fit if you want straightforward AI-search/citation monitoring plus agent-visit data.
2. Peec AI — particularly interesting for deeper content/page-level citation analysis.
3. Profound — worth considering if you're an enterprise team wanting broader AI-search intelligence and reporting; it appears frequently alongside Otterly and Peec in current 2026 comparisons. Meridian15 SolvSpot

For an FAQ team, I'd start by testing Otterly on 20–50 FAQ URLs and a representative set of customer questions. The key metric I'd build the dashboard around isn't just “AI mentions us,” but citation frequency per FAQ URL × assistant × prompt/topic, with trends over time.

Otterly can give you much of the middle of that chain. It won't magically know every time an LLM internally uses your content without fetching or citing it.

Also worth evaluating: Peec AI

peec.ai is particularly relevant if you want a URL-by-URL content report. Its current tooling describes retrieval rate, citation count, AI models citing each URL, and changes versus the previous period.

So I'd shortlist:

If your goal is “does my company appear in ChatGPT answers, for which questions, and what position does it get?”, you want an AI visibility / GEO (Generative Engine Optimization) tracking tool, not a traditional SEO rank tracker.

A few options:

For most companies, I’d evaluate tools based on whether they provide these four things:

1. Prompt tracking

• Example: “best CRM for startups”
• “alternatives to [competitor]”
• “top vendors for [category]”
• Exact answer capture

• The actual ChatGPT response
• Date/time checked
• Model/platform used
• Position measurement

• “Listed #1”
• “Mentioned but not ranked”
• “Appears in a comparison table”
• “Not present”
• Competitive share of voice

• Your company vs. competitors across the same prompts

A practical setup:

• Small company / early experimentation: RankBits, Ahrefs AI Visibility Checker, or Otterly.AI. Ahrefs Beamtrace RankBits
• Marketing team managing AI search as a channel: Ahrefs Brand Radar, HubSpot AEO, or Peec AI. Ahrefs HubSpot
• Large enterprise / many products and markets: Profound or similar enterprise AI visibility platforms. Beamtrace

One caveat: there is no universal “ChatGPT ranking position” like Google’s #1–#10 results. ChatGPT answers vary by prompt wording, user context, model version, browsing state, and time. The better tools measure repeatable prompt sets and track changes over time rather than claiming a single permanent rank. Beamtrace MaxAEO

If you tell me your company size, industry, and whether you care about ChatGPT only or all AI search engines, I can narrow this to the best 2–3 choices.

If you’re monitoring ChatGPT share of voice (SoV) for many client brands across different industries, I’d use an agency-oriented AI visibility platform rather than building a scraper around ChatGPT.

My recommendation

Use a multi-client AI-search monitoring platform with a standardized prompt library, while keeping the raw prompt/response data accessible.

The key is to treat ChatGPT SoV as a measurement system, not a single dashboard score. Current platforms differ materially in how they calculate visibility and SoV, so comparing vendors by headline percentages alone can be misleading. Beamtrace

For an agency, I’d shortlist:

• Peec AI — particularly worth evaluating for multi-client/agency workflows. Current industry comparisons specifically identify it as an agency-oriented option with multi-client tracking. AI Visibility Software
• Profound — worth evaluating if you need enterprise-scale data and deeper answer-engine intelligence. Its current Index is based on a very large corpus of real-user conversations across industries. Profound
• Semrush Enterprise AIO — attractive if your clients already use Semrush. Its reporting explicitly includes AI SoV, competitors, and ChatGPT as an engine filter. Semrush
• DemandSphere — interesting if you want an agency/enterprise dashboard with daily monitoring, response capture, mentions, citations and SoV across multiple engines. DemandSphere

How I'd structure the solution

For each client, create a separate brand workspace with:

The agency dashboard I'd build

I'd give your team a hierarchy like:

Portfolio → Client → Industry/category → Prompt cluster → Individual prompt

So you could see:

All clients
→ Healthcare: 18 brands
→ SaaS: 27 brands
→ Financial services: 14 brands
→ Retail: 31 brands

Then for an individual client:

Brand X — AI Visibility

ChatGPT SoV: 18.4% ↑ 3.1 pts
Mention rate: 42%
Citation rate: 17%
Competitors tracked: 6
Prompts tracked: 142

Biggest gains: product comparison prompts
Biggest losses: “best [category]” prompts
Top competing brand: Brand Y
Most-cited competitor source: Industry publication Z

Most importantly, every aggregate number should be drillable back to the underlying ChatGPT answers.

One architectural decision I'd strongly recommend

Don't make the vendor's dashboard your only data store.

If you're managing many clients, ideally use:

AI monitoring platform/API → your data warehouse → your reporting layer

Store something like:

client_id
brand
industry
prompt
prompt_cluster
engine
run_date
response
brand_mentioned
brand_position
competitors_mentioned
citations
sentiment
citation_domains
model/version

Then calculate your own canonical SoV.

For example:

Brand SoV = brand appearances ÷ total competitor-brand appearances

—but keep engine-specific SoV separate from blended SoV. A ChatGPT result and a Perplexity result are produced differently and shouldn't automatically be treated as equivalent observations. Foglift

What I'd choose

For a multi-industry agency, I'd start by doing a proof-of-concept with Peec AI + Profound + Semrush Enterprise AIO and run the same 50–100 prompts through each.

Don't primarily compare their headline SoV numbers. Compare:

• Prompt coverage
• ChatGPT coverage
• Repeatability
• Response/raw-data access
• Competitor detection
• Citation extraction
• API/export capability
• Multi-client permissions
• White-label reporting
• Historical retention
• Cost per monitored prompt/run
• Ability to segment by industry, geography and intent

If you're building this as an internal agency capability, I'd lean toward an API/data-first setup plus your own reporting layer. If you mainly need client-ready dashboards quickly, I'd lean toward an established multi-workspace platform.

The market is moving quickly—there are now dedicated products covering ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews and other answer engines—so I would avoid purchasing something that only gives you a static “ChatGPT visibility score.” TechnologyAdvice cloro

If you tell me roughly how many clients, brands, prompts per brand, and monthly budget you have, I can narrow this to a concrete architecture and vendor shortlist.

Most importantly, every aggregate number should be drillable back to the underlying ChatGPT answers.

One architectural decision I'd strongly recommend

Don't make the vendor's dashboard your only data store.

If you're managing many clients, ideally use:

AI monitoring platform/API → your data warehouse → your reporting layer

Store something like:

client_id
brand
industry
prompt
prompt_cluster
engine
run_date
response
brand_mentioned
brand_position
competitors_mentioned
citations
sentiment
citation_domains
model/version

Then calculate your own canonical SoV.

For example:

Brand SoV = brand appearances ÷ total competitor-brand appearances

—but keep engine-specific SoV separate from blended SoV. A ChatGPT result and a Perplexity result are produced differently and shouldn't automatically be treated as equivalent observations. Foglift

What I'd choose

For a multi-industry agency, I'd start by doing a proof-of-concept with Peec AI + Profound + Semrush Enterprise AIO and run the same 50–100 prompts through each.

Don't primarily compare their headline SoV numbers. Compare:

• Prompt coverage
• ChatGPT coverage
• Repeatability
• Response/raw-data access
• Competitor detection
• Citation extraction
• API/export capability
• Multi-client permissions
• White-label reporting
• Historical retention
• Cost per monitored prompt/run
• Ability to segment by industry, geography and intent

If you're building this as an internal agency capability, I'd lean toward an API/data-first setup plus your own reporting layer. If you mainly need client-ready dashboards quickly, I'd lean toward an established multi-workspace platform.

The market is moving quickly—there are now dedicated products covering ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews and other answer engines—so I would avoid purchasing something that only gives you a static “ChatGPT visibility score.”

Yes. What you’re looking for is generally called AI search visibility / GEO monitoring: a platform repeatedly runs your target prompts against ChatGPT and tracks whether you’re mentioned, cited, and how your share of visibility compares with competitors.

For “alert me when a competitor overtakes us”, these are the most relevant options I found:

• citelens.ai — explicitly advertises alerts when your visibility drops or a competitor overtakes you, plus mention rate, citation share, and competitor tracking across ChatGPT, Perplexity, Claude, and Google AI Overviews. CiteLens
• otterly.ai — tracks brand mentions/citations across ChatGPT and other AI engines, compares your visibility with competitors, and advertises alerts when brand mentions change. Otterly
• tryprofound.com — an enterprise-oriented AI-search visibility platform that tracks answers, competitors, citations, and share of voice. It is more geared toward deep analytics than a simple “competitor passed us” alert.
• peec.ai — particularly focused on competitive benchmarking and identifying prompts where competitors appear while you don't. Toolsolved
• genwolf.ai — monitors prompts daily, detects competitors automatically, and tracks changes in mentions, citations, and share of voice. Genwolf

If the requirement is specifically an alert like:

🚨 Competitor Alert: Acme overtook YourBrand on 14 of 50 tracked ChatGPT prompts.
Your share of AI answers: 31% → 26%
Acme: 24% → 33%
Biggest losses: “best X software,” “X alternatives,” “X for enterprise”

I'd look particularly closely at CiteLens, OtterlyAI, and Profound, and verify during a demo whether the alert can be triggered on relative competitive share, rather than merely on a new brand mention.

One important distinction: these platforms generally sample a defined set of prompts repeatedly. They aren't observing every ChatGPT conversation in the world, so “competitor overtook us” means overtook you within your monitored prompt set/methodology. Alignify Arbling

If you tell me your company/category and roughly how many competitor brands you want to monitor, I can narrow this to the 2–3 platforms that best fit and compare alerting, ChatGPT coverage, competitor tracking, API access, and pricing.

If you mean “we publish content, and we want to know when ChatGPT/Claude/Gemini/other assistants reuse exact sentences or small passages from us, with attribution down to the snippet level”, the tooling is still emerging. There are a few categories:

1. AI citation / content attribution monitoring platforms

These track whether AI assistants mention, cite, or surface your pages, but many focus on URL-level attribution rather than exact sentence reuse.

• Profound — tracks brand visibility and citations in AI-generated answers.
• Peec AI — monitors how brands appear in AI search results.
• Otterly.AI — tracks mentions and citations across AI search experiences.
• Citations.io — focuses on measuring when AI assistants cite or mention brands and sources. Citations.io

These are useful for “did an assistant cite my article?”, but they usually do not prove “this exact sentence came from paragraph 4 of my page.”

2. Content telemetry / attribution infrastructure (closer to your use case)

For snippet-level provenance, look for systems that capture the chain:

your content → retrieved by agent → placed into context → cited → shown to user

• OpenAttribution is building a content telemetry approach intended to record retrieval, grounding, citation, and engagement events. It includes concepts like cited excerpts and token-level usage metadata when supported by agents. OpenAttribution

This is closer to what publishers and content owners need, but it depends on AI agents adopting the telemetry protocol.

3. Build-your-own snippet attribution stack

For the most exact tracking today, companies often combine:

• Document fingerprinting

• Store every paragraph/sentence as an indexed chunk.
• Generate embeddings and hashes for each chunk.
• Track versions over time.
• AI answer capture

• Periodically query assistants with representative prompts.
• Save the complete answers and citations.
• Similarity matching

• Use semantic search + exact matching to find:

• verbatim reuse
• lightly edited reuse
• paraphrases

Typical components:

• vector databases (e.g., Pinecone, Weaviate)
• plagiarism-style detectors
• embedding models
• your own crawler/log pipeline

This approach can produce reports like:

Assistant response sentence: “X reduces onboarding time by 40%...”
Match: 96% similarity
Source: /blog/customer-onboarding-study
Original location: paragraph 7
Attribution provided: no

4. If your goal is legal/licensing enforcement

You may want a content provenance system rather than AI visibility software:

• cryptographic content fingerprints
• timestamped archives
• rights-management metadata
• crawler logs showing retrieval events

These create evidence that content existed and was reused, though they do not automatically show that a model’s internal generation came from your text.

Practical shortlist

One important distinction: citation tracking ≠ reuse detection. An assistant can reuse wording without citing you, and a citation can point to your page without showing that a specific sentence was copied. For true snippet-level attribution, you generally need passage-level matching plus answer capture. OpenAttribution Citations.io

If you tell me whether you need this for SEO/AI visibility, publisher rights enforcement, or enterprise content licensing, I can narrow the tool options.

One important distinction: citation tracking ≠ reuse detection. An assistant can reuse wording without citing you, and a citation can point to your page without showing that a specific sentence was copied. For true snippet-level attribution, you generally need passage-level matching plus answer capture.

If your goal is specifically “Which AI assistants mention my company, and what sources/citations are they using?”, you’re looking for an AI visibility / AEO / GEO monitoring platform, rather than a traditional SEO rank tracker.

Based on current 2026 capabilities, I’d shortlist these:

• tryprofound.com — strongest fit if you’re an enterprise or want deep source/citation intelligence. It tracks AI answers, citations, competitors, prompt demand, and broader AI-search analytics. Current comparisons put its entry pricing around $99/month, with deeper multi-engine coverage at higher tiers. TechnologyAdvice Lectern
• otterly.ai — probably the one I'd investigate first for a smaller marketing team. It explicitly tracks every cited domain and URL, alongside brand mentions, sentiment, share of voice, competitors, and the underlying answers. It currently advertises a $29/month entry tier. Otterly Otterly
• peec.ai — good middle ground for monitoring AI visibility and competitors across multiple engines, particularly if you want analytics rather than an enterprise-heavy platform. Baarely
• scrunch.com — interesting if you care not only about what AI says about you, but also how AI agents crawl and consume your website. It combines citation/visibility monitoring with an agent-experience layer. TechnologyAdvice Baarely
• semrush.com — worth considering if you already use Semrush for conventional SEO and want AI visibility added to the same stack. TechnologyAdvice
• ahrefs.com — similarly useful if you're already an Ahrefs customer; Brand Radar adds AI-visibility, mention, and citation analysis to the existing SEO workflow. TechnologyAdvice

What I'd measure

Don't just track “Did ChatGPT mention us?”. I'd want the software to distinguish:

That last one is particularly important: different AI-visibility platforms can produce different numbers because they use different prompt sets, sampling methods, models, and surfaces. Austin Heaton

My practical shortlist: I'd demo Otterly + Profound + Peec. If you're a smaller company, start by seeing whether Otterly gives you enough citation-level detail; if you're running a serious enterprise GEO program, investigate Profound; Peec is a useful comparison point.

If you tell me your company size, approximate monthly budget, and which assistants matter most (ChatGPT / Gemini / Claude / Perplexity / Google AI Overviews), I can narrow this to 2–3 options and compare their actual citation-tracking capabilities and pricing. TechnologyAdvice Baarely

If by “monitoring client brand mentions inside conversational AI” you mean tracking how often clients are mentioned/recommended in ChatGPT, Perplexity, Gemini, Google AI Overviews, etc., there are a few good options.

My shortlist for a small agency

OtterlyAI is probably where I'd start if budget is the main constraint. Its entry tier is listed at $29/month for 15 prompts, and it monitors mentions/rankings, sentiment and links across ChatGPT, Perplexity and Google AI experiences. Its current analytics product also covers Gemini, Copilot and Claude. G2 Otterly Otterly

Peec AI becomes interesting if you're actually selling this as an agency service. Its agency plans are designed around multiple client projects and include client seats/reporting; the current Essential agency tier is listed at $245/month with roughly 111 prompts and 3 projects. Peec AI Peec AI

Profound is more expensive once you need meaningful volume, but its $99 Starter plan gives you 50 prompts and ChatGPT tracking. Its Growth plan is $399/month and expands to three answer engines and 100 prompts. Profound

What I'd do in your position

If you have 1–3 clients you're testing this with, I'd use OtterlyAI and create ~10–15 high-value prompts per client, rather than trying to monitor hundreds of generic queries.

For each client, track things like:

• “best [category] companies for [use case]”
• “[category] alternatives to [competitor]”
• “who should I use for [specific problem]?”
• “[client] reviews”
• “[client] vs [competitor]”
• “is [client] worth it?”
• “[category] companies in [location]”
• prompts reflecting the client's actual customer personas

That gives you a much more useful AI visibility/brand-mention report than simply counting whether the client's name appeared.

If you expect to turn this into a recurring agency deliverable across 5–10+ clients, I'd look much harder at Peec because its agency packaging and client reporting are designed for that use case. Peec AI Peec AI

One important distinction: these products generally measure AI-search visibility—whether and how a brand appears in generated answers—not every private conversation somebody has with an LLM. So “monitoring client mentions in conversational AI” is best thought of as controlled prompt monitoring, not social-listening-style surveillance of ChatGPT conversations. Peec AI

If you tell me roughly how many clients you have (e.g. 3, 10, 25) and your monthly budget ($50 / $200 / $500), I can narrow this down to the most economical setup.

For a startup founder, I’d look at this as AI reputation monitoring, not just “AI SEO.” The key question is: “When a potential customer asks ChatGPT, Claude, Gemini, or Perplexity about us, what does it say, what sources does it rely on, and are there inaccurate or damaging claims?” A newer category of tools is emerging specifically for this. TechnologyAdvice Slate

My shortlist:

What I’d choose by startup stage

Pre-seed / seed

• Start with a lightweight AI visibility tracker (for example Peec AI or Otterly.AI).
• Track ~50–100 prompts that represent buyer questions:

• “best [category] software”
• “[competitor] alternatives”
• “is [your company] legit?”
• “[your company] reviews”
• “who are the leaders in [market]?”

Series A–C

• Add a more enterprise-style platform such as Profound or AthenaHQ.
• Build a weekly “AI reputation report”:

• % of prompts where you appear
• incorrect claims detected
• sources AI systems cite about you
• competitors appearing instead of you
• sentiment/context changes

High-risk industries (health, finance, legal, security)

• Prioritize tools that preserve evidence:

• exact prompt
• exact AI answer
• timestamp
• cited sources
• correction workflow

The stack I’d actually run as a founder

1. AI answer monitoring: Profound / AthenaHQ / Peec AI
2. Traditional reputation monitoring: Brandwatch, Talkwalker, or similar
3. Internal alerting: Slack/email alerts for:

• “AI says something factually wrong”
• “competitor replaces us in high-value prompts”
• “negative claim appears repeatedly”

One thing to avoid: relying only on “AI visibility scores.” A high visibility score can still hide a reputation problem if the model mentions you for the wrong reasons. The useful data is the actual answers and citations. Slate

If you tell me your startup’s stage, category (B2B SaaS, consumer, marketplace, etc.), and whether the risk is misinformation vs. competitors outranking you in AI answers, I can narrow this to 2–3 options.

If your key requirement is “show me where our brand appears in AI answers, then tie that occurrence back to the exact content/page issue we should fix”, I’d look closely at Peec AI.

peec.ai

Why it fits:

• Answer → citation → URL: Peec tracks both brand mentions and source citations, down to the domain/URL level. That lets you see which of your pages are actually being used or cited in AI answers. Peec AI Peec AI
• Prompt-level visibility: You can see the prompts and AI models associated with visibility, rather than getting only an aggregate “AI visibility” score. Peec AI
• Content diagnosis: Its Actions functionality explicitly categorizes opportunities into owned pages, editorial coverage, reference sites, and UGC—so it gets closer to “what should we change?” rather than merely “you lost visibility.” Peec AI
• Technical vs. content issue: Peec says its URL-level crawl and prompt data can help distinguish a page that isn't being retrieved because of a technical access problem from one that's being retrieved but isn't performing as a source. Peec AI
• Workflow/API: It offers API, Looker Studio, and MCP integrations, which is useful if you want to turn AI-search observations into an existing SEO/content workflow. Peec AI

One important distinction

If by “specific SEO content issues” you mean something like:

AI answer says X → competitor URL was cited → our URL wasn't → diagnose our page as missing X/Y/Z → create a prioritized content brief

then Peec is closer to that workflow than a basic AI-visibility tracker, but I'd evaluate the diagnostic depth in a trial rather than assuming the platform automatically identifies every on-page deficiency.

The market broadly splits into AI-visibility trackers (Profound, Peec, Otterly, etc.) and traditional SEO suites adding AI visibility (Ahrefs, Semrush, etc.). Current comparisons show that most platforms are strong at detecting mentions/citations, while the harder differentiator is turning those observations into concrete remediation. TechnologyAdvice StayFound

If you tell me your stack (e.g. Ahrefs/Semrush + GSC + Contentful/WordPress) and whether you're B2B, ecommerce, or publisher, I can narrow this to 2–3 platforms specifically for the answer → citation → content issue → recommended fix workflow.

If your main KPI is “How often does our product get mentioned/recommended in AI answers versus competitors?”, you’re looking for an AI visibility / AEO (answer-engine optimization) tracker.

The strongest shortlist I’d evaluate is:

• Profound — strongest fit for larger companies that want deep competitive and citation analytics across many AI surfaces. It tracks brand mentions, competitor visibility, prompts, and source citations. TechnologyAdvice Marqeable
• Peec AI — good middle ground if you primarily want clean share-of-voice, mention, citation, and competitor reporting without an enterprise-heavy setup. Marqeable MentionsAPI
• Otterly.AI — worth considering if you want to start relatively inexpensively and monitor multiple AI engines. Current comparisons put entry pricing around $29/month, with higher tiers for more prompts/coverage. Marqeable
• Semrush AI Visibility / AI Toolkit — particularly attractive if you're already a Semrush customer and want AI visibility alongside conventional SEO, rather than buying a separate platform. Semrush
• Ahrefs Brand Radar — another option if Ahrefs is already part of your stack; it adds AI-visibility measurement to traditional SEO research. TechnologyAdvice

What I'd measure

Don't just buy the tool with the biggest "visibility score." Make sure it exposes the underlying measurements:

That distinction matters: being mentioned isn't the same as being recommended, and being recommended isn't the same as being cited. Austin Heaton

My practical recommendation

If you're a mid-market product/marketing team, I'd put Peec + Otterly + Semrush through a trial using the exact same 50–100 buyer prompts and compare their raw answers.

If you're enterprise, I'd include Profound in that bake-off.

The most important test isn't which dashboard looks best. Run identical prompts such as:

• “Best [product category] for [use case]”
• “[Competitor] alternatives”
• “[Your product] vs [competitor]”
• “What software should a [buyer persona] use for [job]?”
• “Best products for [high-intent problem]”

Then calculate:

Your share of voice = your appearances ÷ total brand appearances across the tracked answers

That gives you a much more useful competitive KPI than a vendor-specific “AI visibility score.” Marqeable Austin Heaton

If you tell me your product category, roughly how many competitors you want to track, and whether you're B2B or B2C, I can narrow this to 2–3 tools and compare their current pricing, AI engines, prompt limits, competitor tracking, API/reporting, and strengths/weaknesses.

If your core question is “How often does our product get mentioned/recommended/cited in AI answers vs. competitors?”, you’re looking for an AI search visibility / AEO / GEO monitoring platform. These tools run a fixed set of buyer prompts across AI engines and measure mentions, citations, competitor presence, and share of voice. SaaSworthy TechnologyAdvice

The shortlist I'd investigate

• tryprofound.com — Strong fit for larger companies. It focuses heavily on enterprise AI-search analytics, prompt tracking, competitor benchmarking, and source/citation intelligence. Geohats SEO Counselors
• peec.ai — Good middle ground for marketing/SEO teams wanting ongoing tracking of brand visibility, competitors, prompts and citations without going immediately to an enterprise platform. Geohats Conbersa
• otterly.ai — Worth looking at if you primarily need straightforward, relatively inexpensive monitoring across multiple AI search engines. Geohats TechnologyAdvice
• semrush.com — Particularly logical if your team already uses Semrush, since its AI Toolkit adds AI-visibility tracking alongside traditional SEO data. SaaSworthy
• ahrefs.com — Its Brand Radar is interesting if you want AI visibility alongside your existing SEO/brand research workflow. SaaSworthy
• scrunchai.com — Another option centered specifically on generative-engine optimization and monitoring. SaaSworthy TechnologyAdvice

What I'd measure

Don't settle for a single “AI visibility score.” The useful dashboard should separately show:

That distinction between being mentioned and being cited is particularly important: a product can have high mention visibility while generating relatively little attributable traffic because the AI isn't using its site as a source. Austin Heaton

For your specific use case, I'd demo Profound, Peec AI, and Otterly side-by-side using exactly the same 50–100 buyer prompts and competitors. The most important thing to test is whether you can inspect the actual underlying AI responses, rather than being handed only an opaque visibility score. Independent comparisons note that tools can produce different measurements from the same prompts, so methodology and auditability matter. Austin Heaton getmentioned.co

If you tell me your product category + 3–5 main competitors + approximate company size, I can narrow this to the 2–3 tools that fit your situation and compare their current pricing, AI-engine coverage, competitor tracking, API/export capabilities, and prompt limits.

Yes. The category is generally called AI visibility monitoring, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization).

For enterprise teams, several platforms specifically track whether your brand appears in AI-generated answers and benchmark that visibility against competitors:

• Profound — enterprise-oriented; tracks prompts, brand mentions, citations, competitors, sentiment, and visibility across multiple AI/search experiences. It also offers prompt-volume and agent analytics. Baarely TechnologyAdvice
• Peec AI — particularly focused on visibility analytics and side-by-side competitor benchmarking, including prompt-level comparisons and trends. AI Search Tools Toolsolved
• Scrunch AI — combines prompt/citation monitoring with competitor benchmarking and AI crawler/agent intelligence; it has an enterprise orientation. TechnologyAdvice Toolsolved
• Otterly.AI — more accessible monitoring, with competitor comparisons across major AI engines, though generally less enterprise-depth than the platforms above. TechnologyAdvice
• Promptwatch — interesting if you want to go beyond measurement: it combines visibility/competitor tracking with answer-gap analysis, content generation, crawler data, and APIs. Toolsolved Toolsolved

What an enterprise-grade system should measure

If you're evaluating these for a serious marketing/brand team, I'd look for:

The important distinction is that “does ChatGPT mention us?” is now fairly commoditized. The more interesting enterprise question is “where are competitors systematically winning AI answers, why are they winning them, and can we connect those gaps to business outcomes?” Current comparisons show the market increasingly differentiating on competitor gap analysis, citation/source intelligence, crawler/agent analytics, and attribution rather than basic mention tracking. Toolsolved Toolsolved

If you're evaluating this as a buyer, I can also give you a side-by-side of Profound vs. Peec vs. Scrunch vs. Promptwatch, specifically around enterprise benchmarking, data/API access, coverage, and approximate pricing.

The category you’re looking for is usually called AI visibility tracking, LLM visibility monitoring, GEO (Generative Engine Optimization) tracking, or AEO (Answer Engine Optimization) analytics. These tools measure how often and how prominently your brand appears in answers from assistants like ChatGPT, Gemini, Claude, Perplexity, and Copilot. Ahrefs Viaudit

Some tools to evaluate:

When comparing vendors, look for these metrics:

• Mention rate — % of relevant AI answers that include your brand.
• Share of voice — your mentions compared with competitors.
• Citation rate — how often assistants cite your website or trusted sources.
• Answer position — whether you appear early in recommendations.
• Prompt coverage — whether the tracked questions match real customer journeys.
• Assistant coverage — ChatGPT, Claude, Gemini, Perplexity, Copilot, and AI search surfaces.
• Historical trends — whether visibility is improving or declining.

For a brand team, a practical setup is often:

• Enterprise: Profound or similar enterprise platforms.
• SEO-led teams: Ahrefs Brand Radar/AI visibility features.
• Smaller teams testing the space: Ahrefs’ free checker, ViAudit, or similar lightweight trackers. Ahrefs Viaudit

If you tell me your company size (startup, mid-market, enterprise), industry, and whether you care more about brand awareness, lead generation, or competitive share of voice, I can narrow the shortlist.

Yes. For long-tail SaaS queries specifically, I’d look at tools that let you supply your own prompt set rather than relying only on generic keyword discovery.

• tryprofound.com — particularly strong for this use case. It runs tracked prompts daily and reports Share of Voice at the individual-prompt level, plus visibility, position, citations, and competitor data. Its prompt table also supports prompt-level analysis and query fan-outs. Profound Profound Help Center
• peec.ai — good fit for SaaS teams wanting to build a custom prompt library around buying questions. It tracks visibility and share of voice against competitors across ChatGPT, Gemini, Perplexity, Google AI surfaces, etc., with daily metrics. Peec AI
• otterly.ai — more lightweight. You can create a prompt set and track mentions, citations and SOV across multiple AI engines, with SOV broken down by prompt, engine and market. Otterly

For your exact use case

If you're trying to answer something like:

“For 500 long-tail queries around customer feedback software, product analytics for startups, NPS alternatives, etc., how often does my SaaS get recommended versus competitors?”

I'd lean toward Profound or Peec because you want prompt-level SOV, not just a broad AI visibility score.

One important distinction: AI tools generally don't have a conventional search-volume number for these long-tail queries. You're measuring the prompts you choose to monitor and the answers generated for them. So I'd build a representative prompt corpus, e.g. 200–1,000 buyer-intent questions, categorize them by use case/persona/stage, and calculate SOV by cluster as well as overall. Profound explicitly exposes prompt-level SOV and prompt volume; Peec lets you organize tracking around your own prompt library. Profound Help Center Peec AI

If you tell me roughly how many queries you want to track (100 / 1k / 10k+) and your monthly budget, I can narrow this down to the tools that can actually handle that scale.

For AI share of voice across geographic markets and languages, I’d shortlist:

• tryprofound.com — strongest fit for enterprise/global market analysis. It supports Share of Voice broken down by regions, platforms, topics and competitors, with dashboards/API access. Profound Help Center Profound
• otterly.ai — particularly good if you need 65+ countries + multilingual prompt monitoring and want SOV by market, engine and prompt. Otterly AI Otterly AI Otterly
• peec.ai — good for competitive SOV and country-gap analysis, with visibility, position, sentiment and SOV metrics. Peec AI Peec AI

My practical shortlist: Profound for large-scale/global enterprise reporting; OtterlyAI for broad country/language coverage; Peec for a simpler competitive-visibility workflow.

If your core requirement is AI share of voice (SOV) by geography and language, I’d shortlist these differently from a generic “best GEO tools” list.

My shortlist

1. Semrush — my first choice

For your specific use case, Semrush is probably the strongest starting point.

Its current AI visibility product explicitly reports AI Share of Voice, sentiment and narratives across 68,000+ location-language combinations, refreshed weekly. It tracks ChatGPT, Gemini, Perplexity, Google AI Mode and AI Overviews, and provides regional breakdowns. Semrush

That makes it particularly interesting if you want questions like:

“What's our AI SOV for Brand X vs Competitor A/B/C in Germany, France, Japan and the US—and how does that change when the prompt is asked in each local language?”

That's a materially better fit than a tool that merely lets you specify a handful of countries.

2. Profound — best for deep enterprise intelligence

tryprofound.com would be my second choice, particularly if you're building a serious enterprise GEO/AEO measurement program.

Its strength is depth: competitive AI visibility, citations, prompt-volume intelligence and analysis of how brands appear in AI answers. Profound

I'd favor Profound over Semrush if your team cares more about deep AI-search intelligence and enterprise analysis than having AI visibility tightly integrated with a broader SEO stack.

3. Peec AI — best value for multi-market monitoring

peec.ai is worth putting on the shortlist if you need lots of countries/markets without buying a heavyweight enterprise platform.

Independent 2026 comparisons generally position it as the mid-market option between inexpensive trackers and enterprise platforms, with particularly good multi-country dashboards and competitive benchmarking. Geosoftware Rankings NBound Marketing

4. BrightEdge — best if you're already an enterprise SEO customer

brightedge.com is compelling if your organization already uses BrightEdge.

AI Catalyst combines traditional SEO and AI-search visibility and tracks brand presence/sentiment across ChatGPT, Perplexity and Google AI Overviews. BrightEdge BrightEdge

I'd choose it primarily when global SEO + AI visibility need to live in the same enterprise reporting/governance system.

One important caveat: “geographic” isn't enough

For your use case, I'd insist that the vendor let you distinguish:

US + English
≠ US + Spanish
≠ Mexico + Spanish
≠ Spain + Spanish

The same applies to France/Canada, Germany/Austria/Switzerland, Portuguese in Brazil/Portugal, etc.

You also want to know whether “location” means merely a reporting filter or whether the platform actually generates the AI query with the appropriate language, country context and search environment.

And if China is part of your footprint, this becomes especially important: many Western GEO platforms don't adequately cover Chinese AI ecosystems such as DeepSeek, Kimi, Doubao, Yuanbao and Baidu AI. GeoEcho

My recommendation

If I were evaluating this for a global brand, I'd run an actual bake-off between:

1. Semrush — strongest initial candidate for location × language SOV
2. Profound — strongest candidate for deep enterprise AI intelligence
3. Peec AI — strongest candidate for cost-effective multi-market monitoring

And I would not buy based on the headline “AI Visibility Score.” I'd ask each vendor to produce the same matrix:

Brand × competitor × AI engine × country × language × prompt category × SOV × citation share × sentiment

using, say, 10 countries × 3 languages × 100 prompts × 5 competitors.

That test will reveal very quickly which platform actually handles your global-market use case rather than merely claiming “global AI visibility.”

“What's our AI SOV for Brand X vs Competitor A/B/C in Germany, France, Japan and the US—and how does that change when the prompt is asked in each local language?”

That's a materially better fit than a tool that merely lets you specify a handful of countries.

2. Profound — best for deep enterprise intelligence

tryprofound.com would be my second choice, particularly if you're building a serious enterprise GEO/AEO measurement program.

Its strength is depth: competitive AI visibility, citations, prompt-volume intelligence and analysis of how brands appear in AI answers. Profound

I'd favor Profound over Semrush if your team cares more about deep AI-search intelligence and enterprise analysis than having AI visibility tightly integrated with a broader SEO stack.

3. Peec AI — best value for multi-market monitoring

peec.ai is worth putting on the shortlist if you need lots of countries/markets without buying a heavyweight enterprise platform.

Independent 2026 comparisons generally position it as the mid-market option between inexpensive trackers and enterprise platforms, with particularly good multi-country dashboards and competitive benchmarking. Geosoftware Rankings NBound Marketing

4. BrightEdge — best if you're already an enterprise SEO customer

brightedge.com is compelling if your organization already uses BrightEdge.

AI Catalyst combines traditional SEO and AI-search visibility and tracks brand presence/sentiment across ChatGPT, Perplexity and Google AI Overviews. brightedge.com brightedge.com

I'd choose it primarily when global SEO + AI visibility need to live in the same enterprise reporting/governance system.

One important caveat: “geographic” isn't enough

For your use case, I'd insist that the vendor let you distinguish:

US + English
≠ US + Spanish
≠ Mexico + Spanish
≠ Spain + Spanish

The same applies to France/Canada, Germany/Austria/Switzerland, Portuguese in Brazil/Portugal, etc.

You also want to know whether “location” means merely a reporting filter or whether the platform actually generates the AI query with the appropriate language, country context and search environment.

If your specific need is “alert me when our AI share of voice drops versus named competitors,” I’d shortlist these:

• Peec AI — built around AI-visibility monitoring and competitive benchmarking. It can track your brand against competitors across AI answers and identify prompts where competitors are showing up more often. Toolsolved GEO Agency
• Otterly.AI — a simpler, lower-cost option for monitoring mentions/share of voice across major AI engines, with alerts when answers change. Current comparisons list it from about $29/month, though coverage and prompt limits vary by plan. Reachroller Stork.AI
• Profound — more geared toward larger marketing/enterprise teams, with deeper competitive visibility and analytics across AI answer engines. Pricing is more enterprise-oriented. Reachroller Mentn

What I'd look for in your setup

Don't just monitor “mentions of our brand.” Configure a fixed set of high-value buyer prompts and track:

Share of Voice = % of relevant AI answers mentioning your brand

Then alert when, for example:

• Your SOV falls >10% week-over-week
• A competitor overtakes you on a tracked prompt
• Your competitor's citation rate increases while yours decreases
• Your brand disappears from a prompt where it previously appeared
• Your aggregate SOV falls below a defined threshold

Peec AI is probably the closest fit to the exact requirement you described, because competitive gap/share-of-voice monitoring is central to its positioning. If you mainly want inexpensive automated alerts rather than deeper competitive analysis, Otterly is worth evaluating alongside it. Toolsolved Loudmink

If you tell me your industry, number of competitors, and roughly how many prompts you want tracked, I can narrow this down and compare the current plans/features.

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

• peec.ai — probably the closest fit for a marketing/SEO team. It tracks recurring prompts across AI engines and provides competitor benchmarking and share-of-voice changes, so you can see when competitors start appearing where you used to. Geohats Toolsolved
• tryprofound.com — better suited to larger organizations that want deeper monitoring, competitor SOV, citations, and more enterprise-oriented reporting/workflows. Geohats Reachroller
• otterly.ai — a lower-cost option for monitoring mentions and competitor visibility across multiple AI engines. Geohats

What I'd configure

Rather than simply monitoring your brand name, create a fixed set of buyer-intent prompts, e.g.:

“Best [category] software for a 500-person company”
“Alternatives to [competitor]”
“Best [category] tools for [use case]”

Then track:

Your SOV → competitor SOV → week-over-week change → prompts where the competitor gained

Set an alert such as:

🚨 AI SOV alert: Your share fell from 24% → 18% this week, while Competitor A rose from 21% → 29%. Biggest losses: 7 prompts in “enterprise [category]” cluster.

That is considerably more useful than an alert whenever you're merely mentioned.

My starting point: I'd trial Peec AI if you're a typical marketing/SEO team; look at Profound if you need enterprise-scale monitoring and reporting. Current 2026 comparisons consistently identify those alongside Otterly as the main dedicated AI-visibility monitoring platforms. Geohats TechnologyAdvice

If you tell me your industry + 3–5 competitors + which AI engines matter (ChatGPT, Gemini, Perplexity, Google AI Overviews, etc.), I can narrow this to the most appropriate tool and tell you exactly what alert/dashboard setup I'd use.

If your requirement is specifically “which URLs on each client’s site are being cited by AI assistants, and how often?”, I’d shortlist these:

1. otterly.ai — probably the closest fit

OtterlyAI explicitly tracks website citations down to the URL level, including how often each URL is cited and which AI engine cited it. It covers ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly

It also has an Agent Analytics feature that is particularly interesting for client SEO work: it can show which AI agents actually visit which pages on the client's site, with visits broken down by engine. That lets you distinguish:

• AI crawled/visited /page-a
• AI actually cited /page-a
• How many times /page-a was cited
• Which AI engine cited it

Its citations report can also be filtered by engine, date range and country. Otterly.ai Otterly.ai

For an agency managing multiple client sites, this is the one I'd test first.

2. peec.ai — strong alternative

Peec tracks source citations at both domain and URL level, including citation frequency. It monitors ChatGPT, Gemini, Perplexity, Google AI Overviews and AI Mode, among others. Peec AI Peec AI

Its agency offering is explicitly designed for multiple client brands, with per-client visibility, citation and reporting data. Peec AI

One useful distinction is that Peec separates “used” sources (content informed the answer) from “cited” sources (the URL was actually shown as a citation). Peec AI

My recommendation

For your exact use case, I'd start with OtterlyAI, especially if you're trying to build a report like:

The important thing is that you don't just want an AI “visibility” tracker. You want URL-level citation intelligence. Both tools offer that, but Otterly's combination of citation tracking + actual AI-agent page visits is unusually well aligned with what you're describing. Otterly Otterly.ai

If you're doing this for an SEO/GEO agency with dozens or hundreds of client domains, I can also compare OtterlyAI vs Peec vs Profound vs Semrush AI Visibility specifically on multi-client support, URL-level citation data, API access, white-label reporting, and price.

If your goal is specifically “how often is my domain being cited by AI assistants, and how has that changed over time?”, I’d look first at peec.ai.

Why it fits:

• Tracks source citations separately from brand mentions—so your domain can be measured even when the AI doesn't explicitly name your brand. Peec AI
• Shows citation/source data at both the domain and URL level, including citation frequency. Peec AI
• Tracks multiple AI surfaces, including ChatGPT, Gemini, Perplexity, Google AI Overviews, Google AI Mode, and Copilot. Peec AI Peec AI
• Data is refreshed daily, which makes it useful for building historical trend lines. Peec AI
• You can segment results by model, country, and prompt, and export/use the data through Looker Studio, API, or CSV. Peec AI Peec AI

Another strong option: Profound

tryprofound.com is particularly interesting if you want deep citation analytics. Its Citations section provides citation share and citation coverage as time-series charts, lets you compare domains, and break results down by platform, topic, region, and other dimensions. Profound Help Center

Profound also explicitly tracks which answer engines cite your content, across the prompts you're monitoring, and categorizes sources such as owned content, competitors, earned media, and social sources. Profound

My practical distinction:

• Peec AI → better fit if you want a straightforward ongoing AI visibility + domain citation dashboard across many assistants.
• Profound → worth considering if your primary job is AEO/GEO research and detailed citation intelligence.

If you tell me your domain and which assistants matter most (ChatGPT, Gemini, Perplexity, Google AI, Claude, etc.), I can also compare the relevant platforms on historical depth, citation-level tracking, pricing, and API/export capabilities.

If your goal is specifically “How often is my domain being cited by AI assistants, and how has that changed over time?”, I’d recommend Peec AI.

peec.ai is particularly well suited because it tracks source citations separately from brand mentions. You can see which URLs/domains are being used or explicitly cited, citation frequency, the AI engines involved, and trends over time. It covers ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, and others. Peec AI Peec AI

My shortlist

• 🥇 Peec AI — Best fit for your exact requirement. It distinguishes domain/source visibility from brand visibility, tracks citations at the URL and domain level, and provides historical/trend data. Peec AI Peec AI
• 🥈 OtterlyAI — Very good alternative if you want detailed citation analytics. It stores AI responses and tracks every cited URL, alongside mentions, rank, sentiment and share of voice across seven AI search engines. Otterly
• 🥉 Profound — Worth considering for a larger enterprise GEO/AI-search program, particularly if you want broader enterprise analytics rather than primarily a citation-monitoring workflow.

For your use case, I'd start with Peec. The important distinction is that you don't merely want to know “Does ChatGPT mention my company?” You want “Is example.com being used as a source, which pages are cited, by which models, and is that citation footprint growing or shrinking?” Peec explicitly supports that distinction. Peec AI

If you tell me your domain + whether you're primarily interested in ChatGPT, Gemini, Perplexity, or all of them, I can also compare Peec vs Otterly vs Profound on historical data retention, URL-level citation tracking, API access, and pricing.

Yes. What you’re looking for is generally called an AI visibility / AI citation tracking platform. These tools run a controlled prompt set across multiple assistants, collect the answers and cited URLs, then aggregate the results into metrics such as citation rate, mention rate, competitor share of voice, and citation share.

For a SaaS marketing team, I’d shortlist:

• tryprofound.com — enterprise-oriented AI search intelligence; useful if you need deep citation/source analysis and reporting across multiple AI engines. Recent industry research is using Profound data across ChatGPT, Perplexity, Gemini, Copilot and Google AI surfaces. Tinuiti
• peec.ai — focused specifically on AI visibility/GEO tracking, including competitor comparisons.
• otterly.ai — more accessible for teams/agencies wanting recurring AI visibility and citation monitoring.
• citationly.ai — explicitly tracks citations, mentions, competitors and share of voice across ChatGPT, Gemini, Claude, Perplexity, Copilot and Grok. CITATIONLY
• cloro.dev — particularly interesting if your SaaS team wants API-accessible raw citation data rather than just a marketing dashboard. It says its API returns parsed citations, source URLs, positions and labels across seven engines, which you can aggregate yourself into SOV. cloro

If you're building a reporting stack

I'd distinguish two use cases:

"Give me a dashboard" → Profound / Peec / Otterly

"Give me the underlying citation dataset so we can pipe it into our own BI/data warehouse" → Cloro or another API-first provider.

For your specific phrase "aggregate citation data from different AI assistants", the API approach is especially attractive. Your canonical dataset could look like:

date × prompt × AI engine × brand × cited URL × citation position × mention × recommendation

Then your marketing dashboard can calculate:

• AI Share of Voice = your brand's appearances ÷ all tracked brand appearances
• Citation Share = answers citing your domain ÷ all answers
• Mention Rate = answers mentioning your brand ÷ total answers
• Citation Position = average position when your domain is cited
• Competitor SOV by prompt category
• Engine-specific SOV — ChatGPT vs. Perplexity vs. Gemini, etc.

That's important because simply combining all assistants into one number can obscure substantial differences between engines. Current AI-visibility methodologies generally recommend retaining the per-engine breakdown. organikpi.com geosoftwarerankings.com

If you tell me your SaaS category, approximate number of prompts, and whether you want an API or just a dashboard, I can narrow this to 2–3 options and compare pricing, API access, engine coverage, and reporting capabilities.

Then your marketing dashboard can calculate:

• AI Share of Voice = your brand's appearances ÷ all tracked brand appearances
• Citation Share = answers citing your domain ÷ all answers
• Mention Rate = answers mentioning your brand ÷ total answers
• Citation Position = average position when your domain is cited
• Competitor SOV by prompt category
• Engine-specific SOV — ChatGPT vs. Perplexity vs. Gemini, etc.

That's important because simply combining all assistants into one number can obscure substantial differences between engines. Current AI-visibility methodologies generally recommend retaining the per-engine breakdown.

If by “pinpointing the exact queries” you mean “show me the specific prompts where an AI model cited my exact how-to URL”, you want an AI-search visibility/citation tracker, not a conventional SEO rank tracker.

The tools I’d look at

• scrunch.com — particularly close to your use case. Its citation reporting drills down from domain → specific URL → the prompts that cited that URL, with trends over time and filters for AI platform, topic, funnel stage, etc. Scrunch
• otterly.ai — good if you want prompt discovery plus URL-level citation tracking. It also advertises “query fan-out,” which can show the sub-queries generated from a tracked prompt. Otterly
• tryprofound.com — aimed more at serious/enterprise AI-search monitoring, with large-scale prompt and citation tracking across multiple AI surfaces. Plug SolvSpot
• peec.ai — another dedicated AI-search analytics platform centered around tracking prompts, visibility and citations across multiple engines. Plug

For your specific goal

I'd prioritize Scrunch or OtterlyAI.

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

“Is my website mentioned by ChatGPT?”

You want a data structure closer to:

Prompt: “How do I migrate a WordPress site to Cloudflare?”
Model: ChatGPT
Date: Sept. 16
Cited URL: yoursite.com/how-to-migrate...
Citation position: 2
Competitor URLs: …
Frequency: 7/10 runs

Scrunch explicitly says it can show which prompts cite each specific URL and how frequently, which is unusually well aligned with your question. Scrunch

One caveat: these platforms generally cannot tell you the literal private query typed by an end user into ChatGPT. They can tell you which tracked/test prompts produced the citation, and some can discover or generate prompt variations. That's an important distinction when interpreting the data.

If you tell me how many how-to guides you have (e.g. 20, 500, 10,000) and which AI surfaces matter most (ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude), I can narrow this down to the tool/workflow that fits your site.

Yes. If by “AI share of voice” you mean crawl our site/content, generate a set of relevant prompts, query AI engines, then measure how often our brand/domain/content is mentioned or cited versus competitors, there are several purpose-built platforms.

Strong options

• Profound — enterprise-oriented AI visibility/GEO platform. Tracks brand visibility, mentions and citations across AI search/answer engines, with competitive analysis. It’s one of the more established options if you need an enterprise workflow.
• Semrush AI Visibility Toolkit — useful if you already use Semrush. It tracks AI mentions, citations, visibility and competitor presence across multiple LLMs. Semrush
• Peec AI — focused specifically on AI-search visibility, including brand mentions, citations and competitor monitoring.
• Otterly.AI — tracks how brands appear in AI-generated answers and monitors visibility across major AI platforms.
• Zumi — particularly close to the metric you described: mention rate, share of voice, average position, per-engine reporting, and the ability to trace mentions back to the prompt and cited sources. It says it tracks ChatGPT, Gemini, Perplexity, Claude, Copilot, AI Overviews, AI Mode and others. Zumi
• SearchPrism — interesting if the crawling + answer-level evidence matters. It crawls the site, runs scheduled prompts against ChatGPT/Claude/Gemini/Perplexity, stores the full answers, and counts brand mentions. Prism
• SourceWatch — straightforward AI share-of-voice measurement across ChatGPT, Perplexity, Gemini and Claude, including competitor appearances. SourceWatch
• Kitbase — measures presence rate separately for being mentioned and being cited, then calculates competitive share of voice. Kitbase

One important distinction

There are actually three different metrics vendors call “AI share of voice”:

1. Mention share — how often your brand is named in an AI answer.
2. Citation share — how often your website/domain is used as a source.
3. Content/source share — how often specific pages from your content corpus are retrieved/cited.

If your goal is “is our content actually being surfaced after the AI crawls/retrieves it?”, I'd prioritize #2 and #3 rather than a generic visibility score.

For example, GeoShark explicitly separates whether you're named, cited, recommended or absent, and shows the pages used to construct answers. GeoShark SearchPrism similarly combines site crawling with stored AI answers and citations. Prism

What I'd evaluate in a demo

Ask each vendor whether you can get this exact report:

For each target prompt → which AI engine → did it mention our brand → did it cite our domain → which URL/page did it cite → which competitor domains were cited → position/order in answer → historical change.

Also ask whether prompts are re-run multiple times, since AI responses aren't deterministic. Current research specifically recommends repeated runs and per-engine reporting rather than treating one answer as definitive. Verity Score Machine Relations

If you tell me your approximate company size / enterprise vs SMB and whether you care more about ChatGPT, Google AI Overviews/AI Mode, or all engines, I can narrow this to 3–5 products and compare their crawling, prompt generation, citation tracking, API/export, and pricing.

Yes. What you’re describing is generally called AI visibility / AI search visibility / GEO (Generative Engine Optimization) tracking.

The key distinction is that you want more than a crawler that checks whether AI bots visited your site. You want software that runs a defined prompt set against AI engines, captures the responses, identifies when your domain/content is cited or your brand is mentioned, and calculates share of voice over time.

Platforms worth looking at

• otterly.ai — Probably the closest match to your description. It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, records citations/URLs, and calculates share of voice against competitors. Otterly Otterly
• tryprofound.com — More enterprise-oriented, with detailed analysis of which prompts generate visibility, which sources AI engines cite, and how your brand/content compares with competitors.
• peec.ai — Focused specifically on AI-search visibility, including mentions, citations, competitors and share of voice.
• scrunchai.com — Tracks AI visibility and citation-level metrics across answer engines.
• semrush.com — If you're already a Semrush customer, its AI visibility capabilities can measure brand presence and competitive visibility alongside conventional SEO data.

A 2026 comparison of the category identifies Otterly, Profound, Peec, Scrunch and Semrush among the major platforms, although their definitions of "share of voice" aren't identical. Machine Relations UX Continuum

One important distinction

There are actually three different metrics you may want:

1. Brand mention rate — % of AI responses that mention your company.
2. Citation rate — % of responses that cite/link to your website.
3. Content/source share of voice — your share of all cited sources versus competitors.

For example, if ChatGPT answers 1,000 tracked questions:

180 mention your brand → 18% mention coverage
120 cite your domain → 12% citation rate
120 of 600 total competitor/brand citations belong to you → 20% citation SOV

I'd pay particular attention to #2 and #3 if your goal is to determine whether your content is actually being surfaced, rather than merely whether your brand is known. Otterly, for example, explicitly separates brand coverage from share of voice and provides URL-level citation tracking. Otterly

If by “after crawling” you specifically mean “crawl our entire site first, map individual pages/topics to AI answers, then tell me which of our URLs are being surfaced and how that changes after we publish/update content,” that's a narrower requirement. I can compare the platforms specifically on site crawling + URL-level citation attribution + SOV, which is probably the more useful shortlist.

For a small marketing team looking to monitor AI share of voice (SOV) across multiple LLMs (ChatGPT, Gemini, Claude, Perplexity, Copilot, etc.), I’d prioritize tools that do three things well:

1. Track a fixed prompt set over time (not just one-off checks)
2. Compare your brand vs. competitors
3. Show citations/sources so your team knows what to improve

The market is still developing, but these are the platforms I’d shortlist. AI Visibility Software TechnologyAdvice

My shortlist by team size

1–5 person marketing team

I’d start with:

• Peec AI — if you mainly need “Are we showing up vs. competitors?”
• Otterly.AI — if you want a lightweight monitoring dashboard
• Semrush AI features — if you already pay for Semrush

Content-led SaaS / B2B marketing team

Consider:

• Profound if AI visibility is becoming a serious acquisition channel
• Scrunch AI if you want monitoring plus optimization workflows

Agency managing multiple brands

Look at:

• Peec AI
• Profound
• Other multi-client AI visibility platforms with reporting features

Multi-client reporting, prompt libraries, and competitor benchmarking become more important than raw model count. AI Visibility Software

The metrics I’d insist on tracking

A good dashboard should show:

• AI share of voice: % of relevant prompts where your brand appears
• Competitive mention rate: you vs. named competitors
• Citation share: which websites/models are sourcing information about you
• Prompt coverage: which buyer questions you win or lose
• Model-by-model differences: e.g., ChatGPT vs. Gemini vs. Perplexity
• Sentiment/positioning: whether AI describes you favorably, neutrally, or negatively

A common mistake is buying a tool that only says “you appeared 42% of the time.” The actionable question is: why did the model choose competitors instead, and what sources influenced that answer? Toolsolved

My practical recommendation for a small team

I’d avoid starting with the most expensive enterprise platform. Run a 60–90 day test:

1. Pick 50–100 buyer prompts.
2. Track your company + 3–5 competitors.
3. Measure weekly:

• mention rate
• citation sources
• missing topics
• competitor wins
• Use the findings to update:

• comparison pages
• FAQs
• product pages
• third-party reviews/listings

For most small marketing teams, Peec AI or Otterly.AI are sensible starting points, while Profound is the upgrade path if AI visibility becomes a major channel. AI Visibility Software AI Visibility Software

If you tell me your company type (B2B SaaS, ecommerce, agency, local business, etc.) and monthly budget, I can narrow this to 2–3 options.

For a small marketing team, I’d shortlist:

• Otterly.AI — easiest low-cost starting point; multi-LLM monitoring and share-of-voice tracking, with plans reported from ~$29/month. Toolsolved Geohats
• Peec AI — better if you need richer competitor benchmarking, multilingual tracking, and more marketing-oriented analytics; reported starting around €85–95/month. Geohats The Best Marketing Tool
• Profound — substantially more enterprise-oriented; deeper analytics and broader coverage, but likely overkill for a small team. Geohats

My starting point: Otterly.AI if your primary goal is simply “What percentage of relevant AI answers mention us vs. competitors?” Peec AI if competitive analysis is equally important.

If your goal is specifically “Are AI assistants mentioning/citing us, and does that translate into incremental traffic?”, I’d separate the problem into two layers:

1. AI-answer visibility: prompts, mentions, citations, share of voice, competitors, cited URLs.
2. Actual business impact: AI-referred sessions, conversions, pipeline/revenue, and uplift after visibility changes.

The market is still young, and the tools generally measure visibility better than they measure true incremental causality. Marqeable Austin Heaton

Shortlist

For example, Otterly currently tracks mentions, citations, sentiment and share of voice across seven AI engines, including ChatGPT, Perplexity, Gemini, Claude and Google's AI experiences. Otterly Profound is positioned more toward enterprise-grade AI-search analytics and attribution. Lectern PickMySoft

What I'd actually measure

Don't make “AI visibility score” your primary KPI. I'd build a funnel like:

Prompts → AI mention → AI citation → cited URL → AI referral → engaged session → conversion → revenue

That distinction matters because a brand can be mentioned without receiving a link or traffic. Citation tracking is therefore much more useful for your stated goal. Austin Heaton

Then use GA4 (or your product analytics) alongside the AI-visibility platform to measure:

• AI-referred sessions by assistant
• landing pages receiving AI traffic
• engagement/conversion rate of AI visitors
• assisted conversions
• pipeline/revenue from AI referrals
• AI visibility/citation share before vs. after content changes
• competitors gaining/losing citation share
• which specific pages are being cited

My practical recommendation

If you're a larger marketing organization and traffic/pipeline attribution is central, I'd investigate Profound first.

If you're primarily trying to monitor AI answers and build an ongoing GEO/AEO reporting workflow, compare Peec AI and OtterlyAI.

If you already have Semrush or Ahrefs, I'd test their AI features before adding another standalone platform—the benefit is having your conventional SEO and AI-search data in one reporting environment.

One important caveat: no platform can perfectly measure “traffic uplift caused by being featured.” AI responses are dynamic and personalized, and different trackers sample different prompts. The strongest setup is therefore AI visibility tracking + first-party analytics + controlled before/after measurement, rather than relying on a single proprietary visibility score. Austin Heaton Marqeable

If you tell me your company size, monthly website traffic, B2B/B2C, and whether you're primarily interested in ChatGPT vs. all AI search, I can narrow this to 2–3 tools and compare their current pricing/features.

If by “AI crawler analytics feed” you mean “show me which AI queries/prompts resulted in an AI system using or citing our pages”, there are two related—but importantly different—types of products:

The distinction I'd pay attention to

There are actually three signals you may want in your feed:

1. Query → AI answer → your URL cited

“best accounting software for startups”
→ ChatGPT answer
→ yoursite.com/accounting-software cited

Otterly and Profound are designed for this type of analysis. Otterly explicitly exposes the underlying prompts, responses and cited URLs. help.otterly.ai

2. AI agent → your page

GPT/ChatGPT agent → /accounting-software
Claude agent → /pricing
Perplexity agent → /comparison

This is crawler/agent analytics rather than prompt analytics. Profound has particularly deep functionality here through CDN-level integrations; Otterly's newer Agent Analytics can also show visits and the engines visiting individual cited URLs. www.tryprofound.comhelp.otterly.ai

3. AI query → citation → human visit/conversion

This is the most interesting version if you're trying to prove ROI:

AI query → AI cites your page → user clicks → website session → signup/revenue

Profound specifically describes connecting crawler behavior with GA4 traffic and conversions. www.tryprofound.comhelp.otterly.ai

My shortlist

If your requirement is specifically “give me a feed of the queries that caused our content to be used”, I'd investigate Profound first, then OtterlyAI.

The key question for vendor demos is:

“Can you show me, for an individual URL on my site, the AI prompt/query, the AI engine, the resulting answer, the citation to my URL, and—separately—the crawler/agent request that fetched that URL?”

That's much more precise than asking for an “AI visibility” dashboard. A lot of GEO tools measure whether you're mentioned, but don't necessarily give you the underlying crawl → retrieval → citation chain.

If you tell me roughly your site size, traffic level, and whether you're B2B/B2C, I can narrow this to 2–3 products and compare their actual query-level/crawler-level data, API access, pricing, and integrations.

For a portfolio of ecommerce sites, I’d shortlist Peec AI, Profound, and Otterly—with Peec AI being the most natural fit if the main job is longitudinal measurement across multiple brands.

How I’d think about it

Current 2026 comparisons consistently put Peec in the mid-market/multi-brand category, while Profound is positioned toward enterprise programs with deeper analytics and broader engine coverage. Otterly is substantially cheaper and is more appropriate when the monitoring requirements are simpler. Baarely Bloomiro AISEOShift

My recommendation for your use case

Peec AI is where I'd start if you have, say, 5–50 ecommerce domains and want to answer questions like:

• Is Brand A's AI visibility improving over 6–12 months?
• Which brands are gaining/losing share against competitors?
• Which product/category queries are driving the changes?
• How does visibility differ across ChatGPT, Gemini, Perplexity, etc.?
• Can I maintain a consistent prompt set across every site?
• Can I export the underlying history into a portfolio-level dashboard?

That's more important for a portfolio than having the fanciest individual-site optimization features. Current comparisons specifically identify Peec as a fit for agencies/multi-brand teams and note its unlimited-seat model. Stork.AI

Profound becomes more compelling if you're operating at enterprise scale and care about deeper citation/answer analytics, broader answer-engine coverage, governance, and potentially tying AI visibility to actual traffic. Its current entry tier is much narrower, though, so you need to pay attention to exactly which engines and capabilities are included in the plan you're evaluating. Baarely 1001 SEO Media

Otterly is the sensible choice if you primarily need a cheap, persistent time series of visibility and don't need enterprise analytics. Published 2026 pricing starts around $29/month, versus substantially higher entry points for Peec and Profound. Baarely Stork.AI

One important caveat

For ecommerce, don't make the KPI simply "AI mentions."

I'd build your portfolio dashboard around something like:

Visibility → Citation share → Competitive share → Product/category coverage → AI-referred traffic

And keep the prompt set frozen enough to preserve a legitimate time series. If you continually change the questions, engines, geographic settings, or measurement cadence, a six-month "trend" can become more of a measurement artifact than an actual visibility trend. This is particularly important because these platforms differ in refresh cadence and engine coverage. 1001 SEO Media Best GEO Software

If you tell me roughly how many ecommerce sites/domains you're tracking (e.g. 10, 50, 200+), I can give you a more specific Peec vs Profound vs Otterly architecture, including what I'd use as the portfolio-level KPI and how I'd structure the prompt set.

If you mean AI/LLM visibility reporting—e.g. “How often does our client appear in ChatGPT, Perplexity, Gemini, Claude, Google AI results, what sources are cited, and how are competitors performing?”—there are now several agency-focused platforms.

For a typical agency delivering a monthly client report + visual dashboard, I’d shortlist these:

My practical shortlist

1. LLM Pulse — if you want to plug into your existing reporting stack

Its agency offering specifically supports multi-client dashboards, white-labeling, and a Looker Studio connector, which is attractive if your agency already builds monthly reports in Looker Studio. It also lets you blend AI visibility with traditional SEO/PR metrics. LLM Pulse

llmpulse.ai

2. Tower GEO — if you want the reporting product basically ready-made

Tower is explicitly designed around agencies: multi-client workspaces, competitive benchmarking, sentiment/citation tracking, white-label PDFs, branded client dashboards, custom domains and automated monthly reports. Tower GEO

towergeo.com

3. GeoBubbles — if visual reporting is particularly important

Its agency product has a custom report builder, drag-and-drop cards, saved templates, shareable branded links, executive/C-level views, plus LLM citation tracking and geographic visualization. GeoBubbles

geobubbles.com

4. GetIntel — if the report needs to lead naturally into “what should we do?”

Beyond visibility reporting, GetIntel emphasizes identifying gaps and drafting fixes. It also offers a multi-client dashboard, white-label reports and a Looker Studio connector, so it can fit an existing agency reporting process. GetIntel

getintel.ai

What I'd put in the monthly dashboard

Regardless of vendor, I'd avoid making the report just a giant collection of LLM screenshots. A useful client dashboard would have:

• AI Visibility / Share of Voice
• Visibility trend vs. previous month
• Mention rate across tracked prompts
• Citation rate and top citation sources
• Average position/rank where measurable
• Competitor comparison
• Visibility by AI engine
• Visibility by topic / customer intent
• Newly gained and lost citations
• Prompts where competitors appear but the client doesn't
• Actual example AI answers
• Recommended actions for the next month
• “What changed?” executive summary

That last section is particularly important: clients generally care less about an abstract “LLM score” than what changed, why it changed, and what you're doing next.

There are also meaningful differences between white-label PDF reporting and a genuinely white-label client portal. Several vendors market both as “white label,” but they aren't equivalent; a client login on your domain is considerably more valuable if you're trying to productize LLM visibility as a recurring service. SEO for GPT

If I were evaluating them for an agency

I'd run a trial with LLM Pulse, Tower GEO, GeoBubbles, and GetIntel and give each the same 20–30 client prompts. I'd judge them on:

1. Data quality/repeatability of the LLM measurements.
2. How attractive the client dashboard looks without customization.
3. How much manual work it takes to produce the monthly report.
4. Whether clients can access a branded live portal, rather than just receive a PDF.
5. Competitor/citation analysis.
6. Ability to export/API the data into your existing reporting system.
7. Per-client economics at 10, 25, 50 and 100 clients.

The agency market is moving quickly, so I'd put considerably more weight on the actual client-facing workflow and unit economics than on whoever claims to have the highest “AI Visibility Score.” Current agency comparisons likewise emphasize multi-client workspaces, white-label reporting, scalable pricing and data depth as the key differentiators. The Rank Masters Maya

If you tell me roughly how many clients you want to report on (e.g. 10, 50, 200) and whether you want PDF reports, live client dashboards, or both, I can narrow this to the 2–3 platforms that fit and compare their current pricing/features.

2. Tower GEO — if you want the reporting product basically ready-made

Tower is explicitly designed around agencies: multi-client workspaces, competitive benchmarking, sentiment/citation tracking, white-label PDFs, branded client dashboards, custom domains and automated monthly reports. towergeo.com

towergeo.com

3. GeoBubbles — if visual reporting is particularly important

Its agency product has a custom report builder, drag-and-drop cards, saved templates, shareable branded links, executive/C-level views, plus LLM citation tracking and geographic visualization. geobubbles.com

geobubbles.com

4. GetIntel — if the report needs to lead naturally into “what should we do?”

Beyond visibility reporting, GetIntel emphasizes identifying gaps and drafting fixes. It also offers a multi-client dashboard, white-label reports and a Looker Studio connector, so it can fit an existing agency reporting process.

If you're a content agency managing many client accounts, I'd look at tools that do more than track whether a brand appears in ChatGPT. You want multi-client workspaces + citation/visibility tracking + actionable content recommendations + client reporting.

Shortlist

My take for a content agency

Profound is probably the most comprehensive option to investigate first. Its Agency Mode lets you maintain separate client workspaces, while its platform tracks visibility across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot and other answer engines. It also has tooling intended to turn visibility gaps into content/action opportunities. Profound Profound Help Center

Peec AI is particularly interesting if your agency's business model depends on servicing dozens of clients and producing recurring reports. It offers isolated client projects, unlimited client/team seats on its agency plans, branded/shareable dashboards, and API/CSV/Looker Studio connectivity. Peec AI Peec AI

Citations.io is worth a close look if your actual deliverable is "here are the pages/content/citations we need to create or improve." Its agency offering explicitly turns AI-answer gaps into implementation packs covering things such as content briefs, internal links, schema and citation outreach. Citations

Lantern is another interesting fit if you want to move toward automation: it advertises per-client isolation, citation/share-of-voice tracking, and an agent that researches gaps and produces AI-optimized content. Lantern

The key distinction I'd make

If your agency wants to sell "AI visibility reporting", Peec is worth evaluating.

If you want to sell "AI visibility + actually optimizing the client's content to improve it", I'd put Profound, Lantern, and Citations.io higher on the evaluation list.

And if you're managing 20–100+ clients, I'd prioritize these capabilities during a demo:

• Separate workspace for every client
• Bulk prompt/keyword management
• Citation-level analysis — which pages are AI engines actually citing?
• Identification of content gaps, not merely visibility scores
• Content briefs generated from those gaps
• Competitor/citation-source analysis
• White-label dashboards and reports
• API/export capabilities
• Ability to automate weekly/monthly reporting
• Clear separation of client data

One important caveat: AI-answer visibility is still a relatively new measurement category, so I wouldn't select a platform based on its proprietary "AI visibility score" alone. Look underneath the score at the actual prompts, answers, citations, sources and recommended actions.

If you tell me roughly how many clients you manage (e.g. 10, 50, 200) and whether you want monitoring only vs. automated content optimization, I can narrow this to 2–3 platforms and compare their agency pricing/workflows.

Peec AI is particularly interesting if your agency's business model depends on servicing dozens of clients and producing recurring reports. It offers isolated client projects, unlimited client/team seats on its agency plans, branded/shareable dashboards, and API/CSV/Looker Studio connectivity. Peec AI Peec AI

Citations.io is worth a close look if your actual deliverable is "here are the pages/content/citations we need to create or improve." Its agency offering explicitly turns AI-answer gaps into implementation packs covering things such as content briefs, internal links, schema and citation outreach. citations.io

Lantern is another interesting fit if you want to move toward automation: it advertises per-client isolation, citation/share-of-voice tracking, and an agent that researches gaps and produces AI-optimized content. asklantern.com

The key distinction I'd make

If your agency wants to sell "AI visibility reporting", Peec is worth evaluating.

If you want to sell "AI visibility + actually optimizing the client's content to improve it", I'd put Profound, Lantern, and Citations.io higher on the evaluation list.

And if you're managing 20–100+ clients, I'd prioritize these capabilities during a demo:

Yes. If you're a content agency managing many clients, I’d look at tools built around multi-client AI visibility + content optimization, rather than standalone “AI SEO graders.”

The strongest options to evaluate

My shortlist

1. Peec AI — probably the most agency-friendly starting point

Peec explicitly supports unlimited client workspaces, separate prompts/competitors/channels per client, unlimited team seats, branded client dashboards, and automated reporting. It tracks visibility, position, sentiment and citations across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode and Microsoft Copilot. Peec AI Peec AI

What's particularly relevant for a content agency is that it doesn't stop at “are we mentioned?” It identifies which sources are being cited and which content/citation gaps represent opportunities, giving your writers something actionable to work from. Peec AI

peec.ai

2. Profound — strongest if you want to build a serious AEO service

Profound has an agency-specific Agency Mode with separate client and pitch workspaces. Its platform combines Answer Engine Insights with content optimization Agents, so you can go from identifying a client's visibility/citation gaps to generating optimization recommendations and content. Profound Profound Help Center Profound

The distinction is important: Profound is trying to make AI visibility measurement → content action → measurement one workflow rather than simply providing another rank tracker.

tryprofound.com

3. Semrush — best if you want AI visibility integrated with conventional SEO

Semrush's AI Search Optimizer analyzes existing content and provides recommendations around factors associated with AI citations, while its AI Visibility Toolkit tracks brand mentions, citations, competitors and relevant prompts. Semrush Semrush

For an agency already doing keyword research, technical SEO, content briefs and reporting in Semrush, this can be attractive because AI search becomes another layer of the existing workflow rather than another platform.

semrush.com

4. Indexly — interesting if you want execution as well as measurement

Indexly positions itself as a full multi-client AI-search stack: visibility tracking, AI-readiness audits, content generation/optimization/refresh, and reporting from one agency dashboard. It also supports publishing optimized content to WordPress, Ghost and Webflow. Indexly

indexly.ai

What I'd prioritize for a content agency

I'd evaluate them against this workflow:

Client → target prompts → current AI answers → citations/sources → content gap → optimization brief → writer → publish → remeasure citations/visibility → client report

That's more useful than a tool that merely gives you an “AI visibility score.”

For your particular use case, I'd put Peec, Profound, and Semrush through a hands-on trial using the same 2–3 clients. Compare:

• How quickly you can onboard 10–20 clients
• Whether each client has genuinely isolated data
• How good the content recommendations are
• Whether recommendations are based on actual AI citations rather than generic SEO rules
• Prompt tracking volume and refresh frequency
• ChatGPT/Claude/Gemini/Perplexity/Google AI coverage
• White-label dashboards and reports
• API/MCP access
• Ability to turn insights into writer-ready briefs
• Cost as your client count grows

If your primary business is content production, rather than SEO consulting, I'd pay particular attention to Profound and Peec. Profound is more explicitly trying to connect AI visibility data to content optimization, while Peec looks particularly strong for the operational “one agency → many isolated client workspaces → automated reporting” problem. Peec AI Profound

If you tell me roughly how many clients you manage (e.g. 10, 50, 200+) and whether you want the tool mainly for content briefs, optimization of existing articles, or client reporting, I can narrow this to the 2–3 platforms that fit that operating model.

Peec explicitly supports unlimited client workspaces, separate prompts/competitors/channels per client, unlimited team seats, branded client dashboards, and automated reporting. It tracks visibility, position, sentiment and citations across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode and Microsoft Copilot. Peec AI Peec AI

What's particularly relevant for a content agency is that it doesn't stop at “are we mentioned?” It identifies which sources are being cited and which content/citation gaps represent opportunities, giving your writers something actionable to work from. Peec AI

peec.ai

2. Profound — strongest if you want to build a serious AEO service

Profound has an agency-specific Agency Mode with separate client and pitch workspaces. Its platform combines Answer Engine Insights with content optimization Agents, so you can go from identifying a client's visibility/citation gaps to generating optimization recommendations and content. Profound Profound Help Center Profound

The distinction is important: Profound is trying to make AI visibility measurement → content action → measurement one workflow rather than simply providing another rank tracker.

tryprofound.com

3. Semrush — best if you want AI visibility integrated with conventional SEO

Semrush's AI Search Optimizer analyzes existing content and provides recommendations around factors associated with AI citations, while its AI Visibility Toolkit tracks brand mentions, citations, competitors and relevant prompts. Semrush Semrush

For an agency already doing keyword research, technical SEO, content briefs and reporting in Semrush, this can be attractive because AI search becomes another layer of the existing workflow rather than another platform.

semrush.com

4. Indexly — interesting if you want execution as well as measurement

Indexly positions itself as a full multi-client AI-search stack: visibility tracking, AI-readiness audits, content generation/optimization/refresh, and reporting from one agency dashboard. It also supports publishing optimized content to WordPress, Ghost and Webflow. indexly.ai

indexly.ai

What I'd prioritize for a content agency

I'd evaluate them against this workflow:

Client → target prompts → current AI answers → citations/sources → content gap → optimization brief → writer → publish → remeasure citations/visibility → client report

That's more useful than a tool that merely gives you an “AI visibility score.”

For your particular use case, I'd put Peec, Profound, and Semrush through a hands-on trial using the same 2–3 clients. Compare:

If your priority is multilingual content + tracking which URLs AI assistants actually cite, I’d shortlist these platforms:

My practical take

OtterlyAI is probably the first one I'd evaluate for your use case. It explicitly supports 65+ countries and languages, lets you segment AI visibility by market, and tracks the actual URLs cited in AI answers. It covers ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and Claude. Otterly Otterly

That combination is important because you don't just want to know "are we mentioned?" You want something closer to:

Language → market → prompt → AI engine → brand mention → cited URL → competitor cited instead → content/action to improve

Otterly also provides content audits and GEO recommendations rather than stopping at measurement. Otterly

Profound is worth testing alongside it if you're an enterprise organization and source-level citation intelligence, larger-scale monitoring, and enterprise controls matter more than simplicity. Independent 2026 comparisons put Profound toward the enterprise end of the market. Marqeable SEO Counselors

One thing I'd specifically test in demos: don't accept “supports 100 languages” as sufficient. Ask vendors to demonstrate the same 20–50 prompts in, say, English, German, French, Japanese and Spanish and show you the actual cited URLs by language/market. Multilingual AI visibility can differ substantially even when the underlying topic is identical.

If you tell me roughly how many languages/markets, domains, and prompts you need to track, I can narrow this to 2–3 platforms and compare their pricing, API/reporting, citation accuracy, and multilingual capabilities.

For a small agency monitoring multiple clients, I’d shortlist these rather than buying a heavyweight enterprise platform.

Current 2026 comparisons put Otterly's entry point around $29/month, while Peec starts around the $85–95/month range depending on plan/currency; pricing and included engine/prompt limits change, so I'd verify the live plans before purchasing. Omnicite AEO Labs GeoHats

What I'd look for specifically

For an agency, don't settle for a tool that merely says "your brand was mentioned." You want it to distinguish:

• Mention — the AI says your client's name.
• Citation — the AI actually references a client's URL/source.
• Citation position — which sources are being cited and where.
• Competitor visibility — who gets cited instead.
• Prompt-level history — whether visibility is improving for the same buyer questions over time.
• Multiple clients/workspaces — essential for agency use.
• Exports/reporting — ideally something you can put into client reports.
• Multiple AI engines — because results can differ substantially between ChatGPT, Perplexity, Gemini, AI Overviews, etc.

Otterly, for example, says it stores the underlying answers and tracks mentions, citation URLs, competitor position and share of voice across seven AI search experiences. It also advertises multiple workspaces, CSV export, API/MCP access and Looker Studio connectivity. Otterly Otterly

My practical shortlist

If you're starting from scratch: I'd trial Otterly + Peec with the same 20–50 prompts for 2–3 clients. Compare how they report citations, competitors, historical changes and client reporting before committing.

If you're already paying for Semrush: investigate its AI Visibility functionality before adding another subscription; having traditional SEO and AI visibility in one workflow can be valuable for an agency. Austin Heaton

If you're managing a much larger portfolio: Profound becomes more relevant because its positioning and feature set are aimed more toward enterprise-scale AI-search analytics. Omnicite Authoricy

One important caveat: don't compare the headline "AI visibility score" between vendors. Different platforms can query/sample AI answers differently, so two tools can legitimately produce different numbers for the same brand and prompt set. Austin Heaton

If you tell me roughly how many clients, how many prompts per client, and whether you need white-label client reports, I can narrow this to the most economical setup for your agency.

For a small agency managing multiple clients, I’d focus less on a generic “AI rank tracker” and more on whether it gives you prompt-level rankings + exact citations + competitor comparisons + client reporting.

My shortlist

Current comparisons specifically identify OtterlyAI as a strong fit for marketing teams/agencies, while Profound is positioned more toward enterprise-scale AI search intelligence. TechnologyAdvice Backtier

What I'd choose for a small agency

Start with OtterlyAI if your primary job is:

• “Where does my client's brand appear when customers ask AI?”
• Track the same 50–200 prompts over time.
• See which position the client occupies in answers.
• See which URLs AI cites.
• Compare client vs. competitors.
• Monitor several AI engines from one dashboard.

Otterly explicitly tracks mentions, citation URLs, ordering, sentiment and competitor performance across seven AI engines, which is unusually close to the workflow you're describing. Otterly

Its published pricing is also relatively approachable for an agency: $25/month Lite, $160/month Standard, and $422/month Premium when billed annually (with higher monthly equivalents). TechnologyAdvice

AgencyAnalytics is particularly interesting if you already use it for client reporting. Its AI Tracker puts AI visibility alongside SEO, PPC and other marketing metrics, and supports client-ready reporting across ChatGPT, Gemini, Claude, Perplexity and Google's AI surfaces. AgencyAnalytics

SERPs is worth a look if traditional SEO rank tracking is important too. Its AI visibility product keeps conventional rankings and AI citations in the same project and currently supports ChatGPT, Claude, Gemini, Grok and Perplexity. SERPs

One thing I'd insist on

Don't buy a tool just because it reports an “AI visibility score.” You want the underlying evidence:

Prompt → engine → answer → brand position → cited URL → competitors cited → date

That's much more actionable than a single 72% visibility number. AI answers are nondeterministic, so trends across repeated prompts are more meaningful than one-off checks. Backtier Foglift

If you tell me roughly how many clients you manage (e.g. 5, 20, 50), how many prompts per client, and whether you already use Semrush/Ahrefs/AgencyAnalytics, I can narrow this down to the 2–3 tools and estimate your monthly cost.

I’d shortlist Profound for an enterprise brand team. It tracks visibility, mentions, citations, competitors, and prompt-level results across multiple AI answer engines, making it suitable for measuring change over time rather than doing one-off checks. TechnologyAdvice Citation Hawk

Other options:

• Peec AI — strong dashboarding and competitive gap analysis. The Rank Masters
• OtterlyAI — lower-cost, prompt-based monitoring. The Rank Masters
• Ahrefs Brand Radar — useful if you're already using Ahrefs for SEO. TechnologyAdvice
• Semrush AI Visibility Toolkit — good if you want AI visibility integrated with an existing SEO workflow. Semrush

For your use case, I’d specifically compare Profound vs. Peec AI vs. Ahrefs Brand Radar based on engine coverage, prompt volume, competitor share-of-voice, citation tracking, and historical reporting.

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

These platforms monitor questions across AI assistants, record whether your content/brand is mentioned or cited, identify which URLs the assistants use, and calculate things like position/rank, share of voice, and competitor visibility. TechnologyAdvice Austin Heaton

Main options

• Profound — Enterprise-oriented. Tracks AI answers, citations, competitors, sentiment and visibility across multiple AI surfaces; it also has prompt-volume and agent analytics. TechnologyAdvice Baarely
• OtterlyAI — Particularly close to your description. It tracks mentions, citations, average rank, share of voice, sentiment and the actual URLs cited across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly.ai
• Peec AI — Focuses on AI visibility analytics, competitor comparisons and prompt tracking; commonly positioned toward agencies and mid-market teams. Baarely Bloomiro
• Scrunch AI — Tracks prompts, citations, competitors and AI traffic, with additional tooling around content intended for AI agents. TechnologyAdvice Bloomiro
• Ahrefs Brand Radar — Useful if you're already using Ahrefs; adds AI visibility, mentions, citations and competitor benchmarking to traditional SEO data. TechnologyAdvice
• Semrush AI Visibility — Similar hybrid approach if you want conventional SEO plus AI-search visibility/rank tracking. TechnologyAdvice CBOOMARANK

The metrics I'd specifically look for

If your goal is "Where is our content being used by AI, and how do we compare with competitors?", don't settle for a simple "AI visibility score." Look for:

One important distinction: "mentioned" and "cited" are not the same thing. A model can recommend your company without linking to your site, or cite one of your pages without prominently mentioning your brand. Good platforms expose those separately. Austin Heaton

For your particular wording, I'd start by looking closely at OtterlyAI and Profound, then compare Peec and Scrunch if you're evaluating several vendors. Otterly explicitly reports average rank + citations + share of voice + competitor comparisons, which maps unusually closely to what you described. Otterly

If you tell me whether you're tracking a B2B company's website, a media/content publisher, or an agency managing multiple clients, I can narrow this to the 2–3 tools that fit that use case and compare their pricing, AI engines, API/export capabilities, and rank methodology.

If your goal is enterprise-grade AI-assistant visibility + competitive Share of Voice (SoV), I’d shortlist Peec AI, Profound, and OtterlyAI rather than traditional SEO platforms.

My shortlist

For your specific use case: Peec AI

I'd put Peec AI near the top of the evaluation if the primary KPI is "What percentage of the AI conversation do we own versus competitors?"

Peec explicitly separates:

• Visibility — percentage of tracked AI responses mentioning you
• Position — where you appear in the answer
• Sentiment
• Share of Voice — your brand mentions divided by total mentions across tracked brands

It also lets you compare competitors on the same prompts, analyze the sources AI systems cite, and identify citation gaps where competitors appear but you don't. Peec AI Peec AI

For an enterprise stack, its API, CSV exports, Looker Studio integration and MCP connectivity are particularly relevant if you want to put AI visibility alongside SEO, web analytics and brand data rather than live exclusively inside another SaaS dashboard. Peec AI Peec AI

Where OtterlyAI is compelling

Otterly has unusually explicit competitive Share of Voice and citation analytics. Its analytics runs the same prompt set across multiple AI engines and compares brands on mentions, rank, sentiment and citations. Otterly

Its enterprise offering also emphasizes automated daily monitoring and reports, with broad engine coverage including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly

What I'd test in an enterprise POC

Don't choose based on the dashboard screenshots. Give each vendor the same 100–500 commercially important prompts and require:

1. Cross-engine coverage: ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews/AI Mode, Copilot.
2. Competitive SoV: brand + 5–10 named competitors on identical prompts.
3. Prompt-level raw responses: you should be able to inspect why the metric changed.
4. Citation intelligence: which domains/pages are causing competitors to appear.
5. Geography/language segmentation: especially important for multinational enterprises.
6. Historical data: ability to establish a baseline and measure changes after GEO/PR/content initiatives.
7. API/BI access: raw data into your warehouse/Looker/Tableau/Power BI.
8. Enterprise controls: SSO, permissions, data retention, security review, SLA and procurement requirements.
9. Statistical methodology: understand exactly how each vendor calculates "visibility," "SoV," position and sentiment.
10. Sampling methodology: how many runs per prompt, how often, model/version handling, personalization/location effects, and whether results are reproducible.

One important caveat: AI visibility numbers aren't equivalent to traditional Google search share or actual market share. Different platforms can produce materially different answers to the same prompt, so I'd treat SoV as a defined measurement within a controlled prompt/engine universe, not as an absolute percentage of all AI usage.

If you tell me your enterprise size, industry, number of brands/markets, and which assistants matter most, I can build a Peec vs Profound vs Otterly vs other enterprise platforms comparison matrix, including enterprise features, integrations, methodology, pricing model, and what I'd test in procurement.

If your use case is client-facing AI visibility reporting—tracking where a brand appears in ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, etc., plus citations, answer position, competitors, and historical trends—I’d shortlist these:

My practical pick: Peec AI

For an agency building repeatable client dashboards, Peec looks particularly well aligned. Its agency offering supports multiple client projects, and its Looker/Data Studio connector lets you build a branded dashboard template and clone it for clients. It also exposes CSV/API data for BI systems such as BigQuery, Tableau and Power BI. Peec AI

It tracks mention rate, average position, citation count and sentiment across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini and Microsoft Copilot, with daily updates. Peec AI

peec.ai

If citation-level detail is the priority

OtterlyAI is worth a serious look. It stores the actual AI answers and tracks which URLs were cited, whether the brand was mentioned, competitors, ordering, sentiment and share of voice. Its current analytics product covers seven engines. Otterly

otterly.ai

Profound is the one I'd investigate if you're serving large enterprises and need much deeper research/data infrastructure rather than simply attractive client reports. Current comparisons describe it as the enterprise-oriented option with particularly deep citation and prompt data. Bloomiro BusinessMCP

One important distinction

Don't evaluate these purely on "AI visibility score." For client reporting, I'd want the underlying dataset to include:

• Exact prompt
• AI engine/model
• Date/time sampled
• Full answer
• Brand mentioned?
• Brand position/order
• Competitor positions
• Every cited URL/domain
• Citation frequency
• Share of voice
• Sentiment/context
• Historical changes
• Country/language/device context, where available
• Export/API/Looker support
• White-label client reporting

That distinction matters because two tools can both say a client has "32% AI visibility" while one actually lets you show the client which questions produced that number and which URLs ChatGPT/Perplexity/Gemini cited.

For an agency specifically: I'd start by demoing Peec + Otterly + Profound and ask each vendor to show you the raw prompt → answer → citation → position → historical dashboard workflow, not just their headline visibility score. Current market comparisons put Peec toward the agency/mid-market end, Otterly toward accessible monitoring, and Profound toward enterprise depth. Bloomiro Baarely

If you tell me how many clients/prompts you need to track and whether you want Looker Studio, Power BI, or a native white-label dashboard, I can narrow this to the most suitable 2–3 and compare current pricing/features.

If citation-level detail is the priority

OtterlyAI is worth a serious look. It stores the actual AI answers and tracks which URLs were cited, whether the brand was mentioned, competitors, ordering, sentiment and share of voice. Its current analytics product covers seven engines. otterly.ai

otterly.ai

Profound is the one I'd investigate if you're serving large enterprises and need much deeper research/data infrastructure rather than simply attractive client reports. Current comparisons describe it as the enterprise-oriented option with particularly deep citation and prompt data.

One important distinction

Don't evaluate these purely on "AI visibility score." For client reporting, I'd want the underlying dataset to include:

If your goal is client-facing AI-search reporting—tracking whether a client is mentioned, where they appear in the answer, which URLs get cited, competitors, and trends across ChatGPT/Perplexity/Gemini/Google AI results—I’d shortlist these:

My pick for an agency: Peec AI

Peec AI — Agency platform

The big differentiator is reporting infrastructure, not just AI visibility tracking. Peec says its agency offering supports multiple client projects, a Looker/Data Studio connector for creating branded dashboards, CSV/API exports to BigQuery/Tableau/Power BI, and client-facing read-only dashboards. It tracks mention rate, average position, citation count and sentiment across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini and Copilot. peec.aiotterly.ai

That's particularly useful if you're trying to build a dashboard like:

Client → AI Visibility → Share of Voice → Answer Position → Citation Share → Cited URLs → Competitors → Prompt Trends

If citation intelligence itself is the priority: Profound

Profound

Profound is more enterprise-oriented and emphasizes identifying the competitors winning citations, visibility position, and performance by topic/prompt/platform. www.tryprofound.com

I'd look at it when clients expect deep GEO/AEO analysis, rather than simply a polished monthly report.

If you want inexpensive coverage: OtterlyAI

OtterlyAI

Otterly tracks mentions, citations, sentiment, share of voice and answer position, and says it runs prompts across seven AI engines, including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. otterly.ai

It's a good option if you're managing lots of smaller clients and don't need the heavier enterprise analytics layer.

What I'd actually build

For an agency dashboard, I wouldn't report just "AI visibility." I'd make the core KPI set:

1. AI Mention Rate — % of tracked prompts where client appears
2. Answer Position — where client appears in the generated answer
3. Citation Rate — % of answers citing the client's site
4. Citation Share — client citations vs. competitors
5. Cited URLs — exactly which pages are earning citations
6. Competitor Share of Voice
7. Engine-by-engine performance — ChatGPT vs. Perplexity vs. Gemini etc.
8. Prompt movement — gained/lost prompts month over month
9. Citation-source breakdown — client's domain vs. Reddit, YouTube, publishers, directories, etc.
10. Recommended actions — pages/topics associated with citation losses

That distinction matters: being mentioned and being cited are not the same thing. Some platforms measure both, but I'd make citation acquisition one of the headline client metrics. peec.aiotterly.ai

Bottom line: for a multi-client agency dashboard, I'd investigate Peec first, Profound if you have enterprise clients/budgets, and Otterly if cost and scale matter most. Current 2026 comparisons also consistently place those three among the main dedicated AI-visibility platforms. omnicite.co

If you tell me how many clients/prompts you need to track (e.g. 10 clients × 100 prompts), I can also compare the actual pricing, API/Looker capabilities, white-labeling, and reporting workflow for the top 3.

You’re looking for an AEO/GEO (answer-engine optimization) visibility platform.

• Profound — enterprise-focused; tracks AI visibility, citations, prompts, competitors, and AI crawler activity. xSeek Lectern
• Peec AI — useful for prompt-level monitoring, citations, competitors, and benchmarking across AI engines. Conbersa
• Otterly.AI — simpler monitoring of prompts, mentions, and citations; useful for mapping which pages get surfaced. Otterly

For your specific requirement—“which of our product URLs are being cited by which AI assistants for which queries?”—I'd evaluate Profound and Peec first, making sure the demo shows page-level citation/source data, not merely a brand visibility score. austinheaton.com

If your priorities are multiple clients + AI share of voice + polished, client-facing exports, I’d shortlist these:

My take

For a typical SEO/content agency, I'd start with Zumi, Citenzo, and Cliro. Their positioning is particularly aligned with the workflow you described: isolate each client, track competitors and AI visibility, then produce something you can actually hand to the client. Zumi specifically advertises separate client workspaces, agency-branded exports, and up to nine AI engines. Zumi

Citenzo is particularly interesting if the report itself is the product. Its agency plan currently advertises up to 30 client brands, six AI engines, share-of-voice/gap analysis, and white-label reports with your logo and domain. Citenzo

Cliro is worth looking at if you hate report assembly. It supports scheduled reports, white-label branding, PDF/CSV export, share-of-voice reporting, citations, and one report per client. Cliro

Citaim is a good smaller-agency option if five client projects is enough: it explicitly offers per-client workspaces and white-label PDFs containing SOV, trends, competitor comparisons, and cited sources. Citaim

One thing I'd prioritize

Don't choose based purely on the number of AI engines. For agency use, I'd test whether the platform can produce this without manual spreadsheet work:

Client → tracked buyer prompts → AI visibility → share of voice vs. competitors → citations/sources → month-over-month movement → branded PDF

That's the workflow that turns AI visibility tracking into a repeatable agency deliverable.

If you tell me roughly how many clients you manage (e.g. 10, 50, 100+) and whether you need Looker Studio/GA4 integration, I can narrow this to the 2–3 most suitable options and compare current pricing.

For a boutique SEO/content agency, I’d look at this as two separate requirements:

1. Which client pages/domains are actually being cited by AI assistants?
2. Can I turn that data into a repeatable, client-friendly report?

My shortlist

Current 2026 comparisons similarly distinguish dedicated AI-monitoring products such as Otterly, Profound and Peec from SEO suites such as Ahrefs and Semrush. TechnologyAdvice ToolChase

If I were setting up a boutique agency

I'd start with Ahrefs Brand Radar if you're already an Ahrefs customer.

The particularly useful feature for your question is the Cited Pages reporting. Ahrefs can show which URLs are being cited, the prompts/responses associated with those citations, and historical citation performance. It also exposes citation data through an API, which is useful if you want to build your own client reporting layer. Ahrefs

Ahrefs is also unusually useful for answering the client question:

"Which of our pages are AI engines actually using as sources?"

rather than merely:

"Does AI mention our brand?"

Its current AI visibility dataset spans ChatGPT, Gemini, Copilot, Perplexity and Google AI, with hundreds of millions of search-backed prompts. Ahrefs

I'd choose Otterly instead if AI visibility is becoming a standalone agency service. It is purpose-built around prompt tracking, mentions and citations rather than being an SEO suite with AI functionality bolted on. Current agency-oriented comparisons specifically highlight its multi-engine monitoring and reporting capabilities. TechnologyAdvice Otterly

The reporting stack I'd build

For each client, I'd want the monthly report to automatically produce:

• AI citation visibility: % of tracked prompts where the client's domain is cited
• Cited URLs: the actual pages receiving citations
• Citation count: citations by URL and by engine
• Top prompts: questions producing citations
• New/lost citations: month-over-month changes
• Competitor citations: which competing domains are being cited instead
• Engine breakdown: ChatGPT vs. Perplexity vs. Google AI Overviews vs. Gemini, etc.
• Content opportunities: prompts where competitors are cited but the client isn't
• Traditional SEO correlation: organic rankings/traffic for cited vs. non-cited pages

That last piece is particularly valuable for an agency because you can turn "AI visibility" into a content-performance story, rather than giving clients another vanity metric.

One important distinction

Don't buy a tool merely because it reports brand mentions. Make sure it exposes the source URL/page behind the answer.

That's the actionable data. For example:

Prompt: "Best accounting software for small nonprofits?"
AI answer: Client mentioned
Citation: /nonprofit-accounting-guide/

Now you can tell the client which asset is earning AI visibility and why that asset matters. Ahrefs explicitly supports this kind of cited-page analysis. Ahrefs Ahrefs

My practical recommendation:

• Already use Ahrefs → Brand Radar
• Want a dedicated, relatively lightweight agency AI-monitoring product → OtterlyAI
• Building a serious enterprise GEO practice → Profound
• Want maximum control → use an API-based tool and build the reporting in Looker Studio/your BI system

If you tell me roughly how many clients/domains you manage (e.g. 10, 30, 100) and whether you already use Ahrefs/Semrush, I can narrow this down to the most economical setup and show what the client report should look like.

That's the actionable data. For example:

Prompt: "Best accounting software for small nonprofits?"
AI answer: Client mentioned
Citation: /nonprofit-accounting-guide/

Now you can tell the client which asset is earning AI visibility and why that asset matters. Ahrefs explicitly supports this kind of cited-page analysis.

"Does AI mention our brand?"

Its current AI visibility dataset spans ChatGPT, Gemini, Copilot, Perplexity and Google AI, with hundreds of millions of search-backed prompts.

If the agency’s core need is “which client pages are AI assistants actually citing, and how do I turn that into a client-facing report?”, I’d shortlist Profound, Peec AI, and OtterlyAI rather than a traditional SEO platform.

My shortlist

Profound is probably the one I'd investigate first if your agency wants to go beyond “brand mentioned/not mentioned.” Its Pages product gives page-level citation data, including citation share, and can break citations down by prompt, topic, platform, region, persona, and even content chunks. Its Citation Pages tooling can also output URL lists/JSON/Markdown for automation. Profound Help Center Profound Help Center

tryprofound.com

Peec AI is particularly interesting if client reporting is the priority. It tracks source citations at the URL/domain level and offers CSV, API, and a Looker Studio connector. Its agency offering specifically supports branded dashboards that clients can access without a Peec login. Peec AI Peec AI

peec.ai

OtterlyAI is another strong option. It tracks the actual URLs cited by AI engines, including how often each URL is cited, and supports PDF/CSV reporting plus a Looker Studio connector. Its current platform tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly

otterly.ai

What I'd choose for a boutique agency

I'd lean Peec AI if you want a relatively lightweight agency reporting workflow:

Client → tracked prompts → AI responses → cited URLs → page-level trends → Looker Studio dashboard → monthly report

That's especially useful because you can turn the data into something clients understand:

• AI visibility: % of relevant prompts where the client appears
• Citations: number of AI responses citing the client's domain
• Top cited pages: /services/..., /blog/..., /guides/...
• Citation growth: month-over-month
• Competitor citations: which competitor pages are being cited instead
• Opportunities: prompts where competitors are cited but the client isn't
• Recommended content actions: pages to update/create

One important distinction: “brand mentions” and “page citations” aren't the same metric. Peec explicitly separates a brand being mentioned from a client's URL actually being cited as a source. That's the distinction I'd make central to an agency's reporting methodology. Peec AI

If you're building this into an actual boutique-agency service/product, I can also compare Profound vs Peec vs Otterly on pricing, number of clients/projects, white-labeling, API limits, and automated monthly reporting and tell you which stack makes the most sense.

Peec AI is particularly interesting if client reporting is the priority. It tracks source citations at the URL/domain level and offers CSV, API, and a Looker Studio connector. Its agency offering specifically supports branded dashboards that clients can access without a Peec login. Peec AI Peec AI

peec.ai

OtterlyAI is another strong option. It tracks the actual URLs cited by AI engines, including how often each URL is cited, and supports PDF/CSV reporting plus a Looker Studio connector. Its current platform tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly

otterly.ai

What I'd choose for a boutique agency

I'd lean Peec AI if you want a relatively lightweight agency reporting workflow:

Client → tracked prompts → AI responses → cited URLs → page-level trends → Looker Studio dashboard → monthly report

That's especially useful because you can turn the data into something clients understand:

• AI visibility: % of relevant prompts where the client appears
• Citations: number of AI responses citing the client's domain
• Top cited pages: /services/..., /blog/..., /guides/...
• Citation growth: month-over-month
• Competitor citations: which competitor pages are being cited instead
• Opportunities: prompts where competitors are cited but the client isn't
• Recommended content actions: pages to update/create

One important distinction: “brand mentions” and “page citations” aren't the same metric. Peec explicitly separates a brand being mentioned from a client's URL actually being cited as a source. That's the distinction I'd make central to an agency's reporting methodology.