Answers that mention Peec AI

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

• Why: Its Lite plan is currently $29/month and tracks 15 prompts across ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot, with daily tracking. It also includes link/citation analysis and a free trial. Otterly Otterly AI
• For product pages: You can use those 15 prompts for high-value searches such as “best [product category] for…”, “[product type] under $X,” and “[product category] alternatives,” then see whether your brand/site is mentioned and cited.
• If you need SKU-level tracking: peec.ai has more ecommerce-specific functionality, including product-catalog uploads and SKU-level visibility/win-rate tracking. But its Starter plan is $95/month for 50 prompts, so I'd consider it once you have enough products/queries to justify the extra spend. Peec AI
• I wouldn't start with Profound: its Starter plan is currently $99/month for 50 prompts and primarily tracks ChatGPT at that tier. Profound

My practical recommendation

If you're spending under $50/month, use OtterlyAI + Google Search Console/Analytics. Track perhaps 10–15 commercially important prompts rather than trying to monitor every product.

If you tell me roughly how many products you have and your monthly budget (e.g. $0, $30, $100), I can suggest a specific setup and the prompts I'd track.

Yes. For a mid-market SaaS team, I’d shortlist the AI-search/GEO platforms that explicitly separate brand mentions, competitor share of voice, and citations rather than giving you a single “AI visibility” score.

The two I'd demo first

Peec AI looks particularly aligned with your stated use case. Its product reports competitor SOV on the same prompts, broken down by AI engine, while its sources/citations views show which URLs and domains are being cited and where competitors have citation gaps. Peec AI Peec AI

OtterlyAI is another direct fit: it tracks mentions, citations, sentiment and SOV across multiple AI engines, with competitor benchmarking and historical trends. It also exposes which URLs are being cited and which rival is being cited instead. Otterly Otterly

Profound is worth adding to the evaluation if you expect this to become a serious cross-functional measurement program. Current category research describes it as particularly strong on surface coverage and citation analysis, while Peec is differentiated more toward competitive SOV. Benchline Reports

What I'd make a buying requirement

For SaaS, I'd insist the tool can report these separately:

• Mention share of voice: % of tracked AI answers mentioning you vs. competitors.
• Citation share: % of source citations going to your domain vs. competitors.
• Average position: where you appear when multiple vendors are recommended.
• Prompt-level trends: which buyer questions are gaining/losing visibility.
• Engine-level trends: ChatGPT vs. Gemini vs. Perplexity vs. Google AI results, etc.
• Citation URL: the specific page being cited, not just “your brand was cited.”
• Competitor citation gaps: sources that cite competitors but not you.
• Historical data: ideally daily/weekly trends rather than snapshots.

One important caveat: SOV isn't an absolute measurement of the whole AI ecosystem. It's calculated over the prompt set and competitor universe you define, and different vendors can produce different numbers because they sample prompts/engines differently. CiteLyzer

If your primary question is “Are we gaining or losing ground to competitors in AI answers, and exactly which citations are driving that?”, I'd put Peec, Otterly, and Profound into a side-by-side trial using the same 50–100 commercial/category prompts.

Yes. For a mid-market SaaS team, I’d shortlist these platforms specifically for competitive AI visibility / share of voice + citation tracking:

My shortlist

• ahrefs.com — probably the most straightforward match to your requirements. It reports AI Share of Voice, mentions, citations, and estimated impressions, lets you benchmark competitors, and supports custom prompts. Ahrefs says Brand Radar analyzes 455M+ search-backed prompts across AI surfaces including ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews/AI Mode. Ahrefs Ahrefs Help Center
• Profound — worth looking at if you want a more dedicated AI-search intelligence platform and particularly deep citation/prompt analysis. Current 2026 comparisons put it toward the enterprise end of the category. TechnologyAdvice Benchline Reports
• Peec AI — a good candidate if the primary workflow is “show me where competitors appear, where we're absent, and how that changes over time.” It is frequently positioned around competitive AI visibility and SOV monitoring. TechnologyAdvice Benchline Reports
• Otterly.AI — more lightweight and economical, while still focused on tracking mentions/citations and competitor visibility across AI engines. TechnologyAdvice
• Semrush AI Visibility Toolkit — particularly sensible if your team already lives in Semrush and wants AI visibility added to an existing SEO workflow. CBOOMARANK SaaSworthy

What I'd actually measure

For SaaS, I wouldn't stop at a single "AI visibility score." I'd want the platform to expose:

1. Share of voice — % of relevant AI answers where you vs. each competitor appear.
2. Mention rate — how frequently each brand is named.
3. Citation rate — how frequently each brand/domain is actually linked as a source.
4. Citation share by domain/page — which third-party sites are feeding competitors' AI visibility.
5. Competitive gaps — prompts where competitors appear but you don't.
6. Trend by prompt/topic — whether your visibility is increasing or declining over weeks/months.
7. Engine-level breakdown — ChatGPT vs. Gemini vs. Perplexity vs. Google AI surfaces, rather than one blended number.
8. Custom buyer prompts — your actual high-intent questions such as “best [category] for mid-market SaaS,” “alternatives to X,” and “[competitor] vs [your product].”

Ahrefs, for example, explicitly supports the “competitor mentioned, us absent” analysis and citation-gap analysis, which is particularly useful for turning SOV data into a content/PR backlog. Ahrefs Ahrefs

If I were evaluating vendors for a mid-market SaaS team, I'd start with Ahrefs Brand Radar, Profound, and Peec AI, then compare them using your actual 50–200 buyer prompts rather than relying on generic feature matrices. The biggest thing to validate is whether their SOV is based on a prompt universe that actually resembles your buyers; these measurements are samples/models of AI visibility, not a census of every AI conversation. Ahrefs Ahrefs

If you tell me your approximate budget and which AI surfaces matter most (ChatGPT, Google AI Overviews/Mode, Perplexity, Gemini, etc.), I can make a more concrete 3-vendor comparison with pricing, coverage, API/reporting, and what I'd test in a trial.

Yes. For a multi-language, multi-region site, I’d focus less on a generic “AI visibility score” and more on whether the platform can segment language × country × AI engine × prompt, while showing the actual citations/URLs.

Based on current 2026 capabilities:

• otterly.ai — probably the most directly aligned with your requirement. It currently advertises 65+ countries/languages, tracking across 7 AI engines, and daily citation/brand tracking down to the cited domain/URL. Otterly Otterly
• tryprofound.com — more enterprise-oriented, with deeper AI-search analytics and citation/source analysis. I'd investigate its exact country/language coverage for your markets before committing, because published comparisons indicate more limited geographic coverage than Otterly. Austin Heaton Otterly
• peec.ai — worth considering if you want a dedicated AI-search platform with multi-country tracking and prompt-level analytics. Ayzeo
• semrush.com AI Visibility Toolkit — useful if you're already heavily invested in Semrush, but its geographic capabilities are less compelling for a truly international program than platforms specifically emphasizing market/language tracking. Otterly
• ahrefs.com — strong if you want AI visibility alongside Ahrefs' traditional SEO/backlink data, but again I'd verify the exact market/language granularity you need. BusinessMCP

What I'd test in a demo

For your use case, ask each vendor to demonstrate this exact scenario:

“Show me how our visibility for the same 20 commercial queries changes between English/US, English/UK, German/Germany, French/France, and Spanish/Spain, and show me the actual sources/citations returned by each AI engine.”

You want to be able to see something like:

That's important because a global score can hide a situation where you're highly visible in English/US but essentially invisible in German, French, etc.

If multilingual + geographic granularity is your primary requirement, I'd put Otterly, Profound, and Peec through the same controlled test first, rather than choosing purely on the headline number of AI engines. Current published information specifically gives Otterly an unusually clear claim around 65+ countries/languages and citation-level tracking. Otterly Otterly

If you tell me which countries/languages and which AI engines matter most (ChatGPT, Gemini, Perplexity, Google AI Overviews, Claude, Copilot, etc.), I can make you a feature-by-feature shortlist of 3–5 platforms, including pricing, localization depth, citation tracking, API/export, and enterprise reporting.

If your key requirement is AI visibility + citation tracking across multiple languages and regions, I’d shortlist Peec AI, Profound, and OtterlyAI.

Peec is particularly interesting for your use case because its API and platform support localized/multi-language visibility data, rather than simply translating an English prompt set. Toolsolved Citadex

Profound is worth considering if you're an enterprise with many markets and need granular citation/source analysis. Current comparisons describe it as having broad model coverage and particularly deep citation intelligence. licheo.com SEO Counselors

OtterlyAI is a more accessible option. It explicitly tracks brand mentions and citations across ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, Claude and Copilot, with country segmentation. Otterly

What I'd verify before buying

For a genuinely multilingual site, don't just ask whether a tool "supports languages." Test whether it can separately report:

• Language: English vs German vs French vs Japanese, etc.
• Market/location: US vs UK vs Germany vs France, etc.
• Localized prompts: ideally native-language prompts, not translations of one English prompt.
• AI engine: ChatGPT vs Gemini vs Perplexity vs Google AI Overviews/AI Mode.
• Citation URL: the exact page cited, not merely a brand mention.
• Citation frequency/share: how often your site is cited relative to competitors.
• Historical tracking: whether visibility/citations can be trended by market and language.
• API/export: important if you want to combine AI visibility with your existing SEO/GSC reporting.

One important distinction: "brand mentioned" and "website cited" are different metrics. For your use case I'd prioritize a platform that records the actual cited URL and lets you break that down by language × country × AI engine × prompt.

If you tell me roughly how many languages/countries you operate in and your monthly budget, I can compare Peec vs Profound vs Otterly vs Semrush/Ahrefs specifically for that setup. ayzeo.com

If by “AI citation monitoring” you mean tracking when ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, etc. cite your domain or content, there are several credible options in 2026. The key integration question is whether you want the data inside your existing BI/analytics stack or are happy with another standalone dashboard.

Peec is particularly interesting if Looker Studio is your reporting layer; its higher-tier offering includes Looker Studio integration and API access. Ayzeo Conbersa

If you're already heavily invested in Semrush, its AI capabilities are increasingly integrated with its existing SEO data, including daily prompt tracking and source-level citation information. HubSpot Blog

For a HubSpot-centric stack, HubSpot's own AEO tooling is now available in beta and tracks prompts, visibility, sources, and citation patterns within the HubSpot environment. HubSpot Knowledge Base

What I'd prioritize for an analytics-stack integration

Rather than choosing purely on “number of AI engines,” I'd require:

• Raw citation records — URL cited, AI engine, prompt, timestamp, competitor, response.
• API or warehouse export — ideally REST API/webhooks rather than CSV-only.
• Custom prompts — so you can monitor actual customer/buyer queries.
• Engine-level dimensions — ChatGPT vs. Gemini vs. Perplexity vs. Google AI.
• Linked citation vs. brand mention as separate fields.
• Historical data for trend analysis.
• BI compatibility — Looker Studio, Tableau, Power BI, Snowflake/BigQuery, etc.
• Alerts/webhooks when citation share changes materially.

That's important because a simple “AI visibility score” isn't sufficient if you want to join citation data with traffic, pipeline, conversion, or revenue. Current industry comparisons specifically distinguish URL citations from mere brand mentions. Austin Heaton Presenc AI

If you're building this into an existing stack

I'd shortlist Peec, Profound, Semrush, and AthenaHQ first, then choose based on your existing stack rather than treating them as interchangeable.

For example:

AI citation platform → API/connector → warehouse → Looker/Tableau/Power BI → CRM/revenue data

That lets you answer the much more useful question: “Which AI citations are actually associated with qualified traffic and pipeline?”

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

Yes. The category you want is AI visibility / GEO (Generative Engine Optimization) platforms, but your specific requirement—predicting which individual pages are likely to become AI citations before they actually are—is narrower.

Products worth evaluating:

• otterly.ai — explicitly offers page-level “citation potential” / predictive content audits, alongside actual citation tracking. Otterly
• geosource.ai — probably closest to your exact concept: a Citation Readiness Score designed as a predictor of AI citation likelihood, based on research into citation-predictive signals. GeoSource.ai
• helindex.com — scores every page specifically for predicted AI-citation likelihood and then compares that prediction with actual citations. Helindex
• tryprofound.com, peec.ai — stronger on monitoring actual AI visibility, citations, competitors and source discovery than on page-level prediction. Austin Heaton datadab.com

The interesting product gap: most platforms answer “Which pages are AI citing?” Your proposed tool answers “Given the entire web/page corpus, which URLs is an AI assistant most likely to select as sources for this specific question?” That predictive, query-specific source-ranking layer appears considerably less mature.

If you mean tracking which sources AI assistants cite, how often they appear, and how influential those sources are, the category is usually called AI citation tracking / AI visibility / answer engine optimization (AEO) analytics. A few tools worth looking at:

My shortlist by use case:

• You want the deepest “why did the AI pick this source?” analysis: Profound — it focuses heavily on citation ownership, source categorization, and competitor citation analysis. Profound
• You want a practical SEO workflow: Semrush or Ahrefs if your team already uses those ecosystems. Nick Lafferty Beamtrace
• You want a lighter-weight monitoring setup: Otterly.AI or Peec AI. Elfsight The Rank Masters

For evaluating citation quality, I’d look for these metrics rather than just “number of citations”:

• Source prominence: how often a domain/page appears across relevant prompts
• Citation share: your sources vs competitors’ sources
• Source authority/context: publisher type, reputation, topical relevance
• Citation persistence: whether a source keeps appearing over weeks/months
• Citation position: whether the source is a primary reference or a minor supporting link
• Citation gaps: important sources AI cites for competitors but not for you

One caveat: AI citation data is still noisy because different assistants expose citations differently, and results can vary by prompt wording, geography, model version, and retrieval timing. Nick Lafferty

If you’re building an internal analytics stack rather than buying a SaaS tool, the core dataset you’d want is: (model, prompt, answer, cited URL, domain, citation position, timestamp, topic, competitor relationship). That enables your own source prominence scoring.

If by “exact snippets” you mean which pages AI assistants actually cite, what passage/fact they appear to be extracting, and what you should change to increase citation likelihood, you’re looking for the newer AI search visibility / GEO tools—not traditional SEO platforms.

Tools worth looking at

The important distinction

No tool can reliably show a single, permanent “exact snippet ChatGPT uses” in the same way that Google Search Console can show a search query. AI answers are generated dynamically, and repeated queries can produce different citations and wording. Recent research specifically finds substantial citation variability between runs. arXiv

The more useful workflow is:

Prompt → AI answer → cited URL → extracted/supporting content → competitor source → content gap → optimization

For example:

Prompt: “What are the best project management tools for remote teams?”

A useful GEO platform should tell you:

• Your brand appeared: No
• Competitor mentioned: Asana
• Sources cited: Asana, Forbes, G2, etc.
• Which URLs those sources came from
• Which prompts consistently produce/lose your mention
• What topics/entities/facts are present in cited pages but missing from yours
• Whether your content is actually being cited versus merely ranking well in Google

That's much more actionable than simply measuring “AI visibility.”

For a content strategist specifically

I'd prioritize a tool that gives you citation-source analysis + content recommendations, rather than one that only gives you a visibility score.

The underlying research supports this approach: pages with greater AI citation influence tend to be structured, semantically aligned, and rich in extractable evidence such as definitions, numbers, comparisons, and procedures. arXiv

So your optimization brief can become:

“Here are the 25 buyer questions → here are the sources AI currently cites → here are the passages/facts those sources provide → here's what's missing from our content → here's the page/section we should create.”

If you tell me your budget (e.g. <$100/mo, $500/mo, enterprise) and whether you're optimizing for ChatGPT, Perplexity, Gemini/AI Overviews, or all of them, I can narrow this to the 2–3 tools that fit a content-strategy workflow.

If you mean “Which tool can show me the actual prompts/questions that cause AI assistants to cite my website, and which of my pages they cite?”, you're looking for an AI search / GEO citation-tracking platform, rather than traditional SEO keyword tracking.

A few current options:

• peec.ai — particularly relevant to your question. It tracks prompts, AI visibility, cited URLs/domains, competitors, and has prompt discovery plus query-fanout analysis showing related searches AI systems use behind a question. Peec AI
• otterly.ai — tracks AI search citations and provides citation-level analysis across platforms such as ChatGPT, Google AI Overviews, Perplexity, and Gemini. Otterly
• getveritas.io — explicitly offers prompt discovery, showing buyer questions where your brand is currently absent, alongside citation and competitor analysis. Veritas
• foglift.io — gives prompt-level breakdowns, showing exactly which prompts trigger mentions/citations and which don't, across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. Foglift
• rankscope.ai — tracks AI citations and includes citation context and prompt-level visibility across several AI search engines. RankScope

The capability I'd prioritize

For your specific use case, look for a tool that gives you this chain:

Prompt → AI answer → cited URL → your page → competitor cited instead → missing-content opportunity

For example:

“What are the best accounting platforms for small businesses?”

The tool should tell you:

• ChatGPT: cited your /accounting-guide page
• Perplexity: cited competitor.com
• Google AI Overview: cited an industry publication
• 14 related prompts also trigger citations
• These are the questions where you're currently absent
• These are the pages/content types competitors have that you're missing

That's substantially more useful than simply knowing that your brand was “mentioned.” Research on GEO measurement similarly distinguishes between simply being discoverable/cited and actually having your content contribute to the generated answer. arxiv.org

If your goal is specifically to discover “what questions should we create content for so ChatGPT/Perplexity start citing us,” I'd look first at Peec AI or Veritas because prompt discovery is a core feature rather than just citation monitoring. Peec AI Veritas

If you tell me your website/category and whether you're targeting B2B, ecommerce, SaaS, local, etc., I can also identify the specific tool and workflow I'd use to uncover the AI questions most likely to generate citations for you.

If the core job is “tell me which specific pages lost AI visibility after an underlying model/search update, and help me diagnose why,” I’d evaluate software very differently from a generic GEO/AI rank tracker.

Most current AI-visibility platforms can track prompts, mentions, citations, competitors, and share of voice. The harder problem is tying a visibility decline to a specific URL + specific engine/model + specific point in time. Recent comparisons note that page-level tracking and attribution are still weak spots in many tools. AI Search Tools CitedIndex

What I’d require

Crawler data is particularly useful because otherwise you're observing outputs without seeing whether discovery changed. Some newer products explicitly combine citation monitoring with crawler logs, while many tools remain primarily monitoring dashboards. AI Search Tools Tool Solved

The killer dashboard I'd look for is essentially:

Pages impacted by AI update — Aug 28
37 URLs negatively affected
/best-crm −62% citation rate
Lost across 18 prompts
ChatGPT −71% / Gemini −8% / Perplexity −4%
HubSpot replaced you in 11/18 prompts
No meaningful page changes during period
High confidence: external/model-driven decline

That last part—causal confidence—is much more valuable than another “AI Visibility Score.”

I would also insist on repeat sampling. AI answers are stochastic, so comparing one response before an update with one response afterward can generate a lot of false alarms. Ideally the software reruns important prompts multiple times and reports citation probability/rate rather than treating presence as binary.

Current products worth benchmarking include tryprofound.com, peec.ai, scrunchai.com, and otterly.ai. The market broadly has the prompt/mention/source-tracking layer already; recent industry comparisons differentiate products increasingly on page-level analysis, crawler diagnostics, attribution, APIs, and the ability to turn monitoring into action. Bloomiro PickMySoft

If you're considering building this rather than buying it, I think there's an interesting product wedge here: “Sentry for AI visibility” rather than another GEO rank tracker—automatically detect an AI/search change, identify the URLs it hurt, explain what changed, and prioritize what to fix.

If your agency’s specific goal is “Which of our clients’ blog/content URLs are being cited or used as sources inside ChatGPT, Perplexity, Gemini, Google AI Overviews, etc.?”, I’d evaluate these tools differently from generic “AI visibility” platforms.

My shortlist

1. peec.ai — probably the first one I'd demo

Peec is particularly interesting for an agency because it explicitly supports daily prompt tracking across major models, competitor benchmarking, and separate measurement of mentions vs. citations. Its agency offering is designed around selling AI-search visibility as a recurring service. Peec AI

The distinction between mention rate and citation rate is important for your use case. A blog article might never mention your client's brand but still be cited as the source supporting an AI answer.

I'd want to test Peec on:

• “Show me every client URL cited for this prompt.”
• “Which blog posts are gaining/losing citations?”
• “Which competitor URLs are being cited instead?”
• “Can I export this into a client-facing report?”
• “Can I monitor hundreds/thousands of prompts across multiple clients?”

2. tryprofound.com — strongest if you're building a serious GEO practice

Profound is more oriented toward sophisticated AI-search analytics: prompt analytics, citations, visibility, sentiment, competitors, and agent-related data. Independent 2026 comparisons place it among the more comprehensive enterprise platforms. TechnologyAdvice

I'd investigate it if your agency wants to turn this into a premium GEO/AEO service, rather than simply adding an AI-visibility report to existing SEO retainers.

3. ahrefs.com — excellent if you're already an Ahrefs agency

This is probably the easiest choice if your team already lives in Ahrefs.

Brand Radar can identify cited pages, AI visibility, custom prompts, competitors, and the broader sources influencing AI visibility. Ahrefs says its AI Visibility Index now covers hundreds of millions of search-backed prompts across AI Overviews, AI Mode, ChatGPT, Gemini, Perplexity and Copilot. Ahrefs Ahrefs

The particularly useful piece for your question is “Cited pages.” You can move beyond:

“Our client was mentioned by ChatGPT.”

to:

“These 17 URLs from our client's content library were cited in AI answers, and these 6 URLs account for most of the citations.”

That's much more actionable for a content agency.

4. otterly.ai — worth considering for agency-scale monitoring

Otterly is positioned specifically toward marketing teams/agencies and combines prompt research, AI-search analytics, content auditing and GEO optimization. Current comparisons describe it as particularly suited to agencies and content teams. TechnologyAdvice

I'd put it on the demo list if you care about ease of deployment across many client accounts more than maximum enterprise analytics.

5. scrunchai.com — particularly interesting for citation intelligence

Scrunch is worth a serious look if you want to understand not only what gets cited but also the underlying AI-crawler/source ecosystem.

It tracks prompts, citations, competitors and rankings across ChatGPT, Claude, Perplexity, Gemini, Google AI experiences, Copilot and others, while also offering AI-bot/crawler visibility. TechnologyAdvice

That's useful for an agency because you can potentially connect:

content published → crawled by AI systems → cited in answers → client visibility

rather than treating AI visibility as a black box.

The important distinction I'd make

Don't buy a platform solely because it says it tracks “AI mentions.”

For your agency, I'd want these five separate measurements:

1. Brand mention — Did the AI answer mention the client?
2. URL citation — Did it actually cite one of your client's URLs?
3. Citation share — How often are your URLs cited versus competitors' URLs?
4. Prompt-level attribution — Which exact questions produced each citation?
5. Content-level attribution — Which articles/pages are repeatedly being used as sources?

That fourth and fifth layer is what makes the data useful to a content marketing agency.

For example, your reporting shouldn't just say:

AI visibility: +18%

It should be able to say:

47 client articles were cited across 1,200 tracked prompts this month.
12 articles generated 80% of citations.
“Best CRM for nonprofits” produced 14 citations, including 3 citations to our client's comparison article.
Competitors were cited 2.4× more frequently on pricing-related questions.

That gives your content strategists something they can actually act on.

What I'd choose for your agency

If you're primarily a content/SEO agency: start demos with Peec + Ahrefs Brand Radar + Otterly.

If you're building a dedicated GEO/AEO service: add Profound + Scrunch.

If you're already heavily invested in Semrush: its AI Visibility Toolkit is worth evaluating before adding another platform; current comparisons put it among the established AI-visibility suites. Payline

One other thing: don't assume that “citation tracking” means the same thing across vendors. Some products primarily measure whether a brand appears in an answer, while others expose the actual URLs/domains that supplied the answer. That distinction is central to the use case you described. Payline

If you tell me roughly how many clients, domains, and monthly prompts your agency would need to monitor (e.g. 50 clients × 100 prompts), I can narrow this down to the 2–3 platforms that make the most sense economically and operationally.

Yes. The category you want is AI search visibility / Generative Engine Optimization (GEO) software—specifically, tools that go beyond tracking brand mentions and show which individual URLs are being cited, for which prompts, and what to change on pages that aren't getting surfaced.

The strongest fits

• otterly.ai — probably the closest match to your description. It tracks citations down to the specific URL, across ChatGPT, Google AI Overviews/AI Mode, Gemini, Perplexity, Copilot and Claude. Its Content Audit examines individual pages and provides crawlability, content and GEO recommendations. Otterly Otterly
• Profound — geared more toward enterprise AI-search intelligence, with detailed citation/source analysis and competitive visibility data. I'd investigate this if you're managing a large site and need enterprise reporting/governance.
• Peec AI — focused on AI-search visibility, prompt tracking and competitor/citation analysis; worth considering for an SEO/content team that wants a dedicated GEO platform.
• Scrunch AI — another enterprise-oriented AI visibility platform, particularly relevant if you're looking at broader digital-experience/enterprise workflows.

What I'd specifically look for

Your ideal workflow is:

Prompts → AI answers → cited URLs → your page → recommended changes

For example:

Prompt: "What are the best enterprise data-governance platforms?"
ChatGPT cites: /resources/data-governance-guide/
Perplexity cites: /solutions/data-governance/
Competitor is cited but you aren't → identify content gap
Tool audits your page → recommends changes to headings, entities, evidence, structure, schema, etc.

Otterly explicitly supports this URL-level citation tracking and page-level content audits/recommendations. Otterly Otterly

One important distinction: don't buy a tool merely because it gives you an "AI visibility score." You want the underlying citation URLs and prompt-to-URL mapping. That's what lets your SEO/content team actually determine which pages are producing AI visibility and which pages need work.

If you tell me roughly site size (e.g. 500 / 10k / 1M URLs), B2B vs. B2C, and whether you're primarily interested in ChatGPT, Google AI Overviews/AI Mode, or all AI engines, I can narrow this to 2–3 platforms and compare their actual capabilities and pricing.

If your priority is agency-scale client reporting + white-label delivery, I’d put Peec AI at the top of the shortlist right now.

My shortlist

Why I'd start with Peec

Peec is unusually well aligned with the reporting problem rather than simply tracking AI mentions. Its agency offering provides multi-client management, daily tracking, API/CSV access, and a Looker Studio connector. It tracks mention rate, position, citations and sentiment across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini and Microsoft Copilot. Peec AI

The important distinction: Peec's "white label" is primarily your reporting layer, rather than completely replacing Peec's own application. You can build a branded Looker Studio template once, clone it for clients, and clients can access the reports without a Peec login. Peec AI Peec AI

That's actually a strong model for an SEO/digital agency because you can combine:

AI visibility → SEO metrics → GA4 → conversions → recommendations

inside the same client dashboard.

Otterly is probably the closest alternative

otterly.ai is particularly attractive if you want something that feels more purpose-built for agencies. It has workspaces for multiple clients, unlimited brand reports, scheduled reporting, and a Looker Studio connector. Otterly Otterly

One caveat is important: Otterly does not currently offer native full white-labeling of its own interface. Its recommended solution is to use Looker Studio for your branded client-facing layer. OtterlyAI

If "white-label" means absolutely no vendor branding

Then I'd investigate Surfaced and Blobic.

Surfaced explicitly advertises full white-label, including your logo/domain, unlimited client projects, and weekly reporting across ChatGPT, Claude, Gemini and Perplexity. Surfaced Blobic similarly positions itself as a white-label GEO/AEO backend, with unbranded deliverables and agency branding across ChatGPT, Claude, Gemini, Grok, Perplexity, Copilot and Google AI Overviews. Blobic

For a more enterprise-oriented agency operation, tryprofound.com is worth evaluating. It emphasizes centralized client management and coverage across ChatGPT, Perplexity, Claude, Gemini, Grok, Copilot, DeepSeek and Google AI Overviews. Profound

My practical take:

• Peec → best if you want a serious data/reporting layer you can integrate into your existing agency stack.
• Otterly → best if you want straightforward AI-search monitoring and agency reporting with less setup.
• Surfaced / Blobic → investigate if true white-label is the non-negotiable requirement.
• Profound → investigate if you're selling AEO/GEO to larger enterprise clients and need deeper intelligence.

If you tell me roughly how many clients you need to report on (e.g. 10, 50, 200+) and whether you need a client login/dashboard vs. just monthly PDF/Looker reports, I can narrow this down to the 2–3 that make the most sense economically and feature-wise.

Why I'd start with Peec

Peec is unusually well aligned with the reporting problem rather than simply tracking AI mentions. Its agency offering provides multi-client management, daily tracking, API/CSV access, and a Looker Studio connector. It tracks mention rate, position, citations and sentiment across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini and Microsoft Copilot. Peec AI

The important distinction: Peec's "white label" is primarily your reporting layer, rather than completely replacing Peec's own application. You can build a branded Looker Studio template once, clone it for clients, and clients can access the reports without a Peec login. Peec AI Peec AI

That's actually a strong model for an SEO/digital agency because you can combine:

AI visibility → SEO metrics → GA4 → conversions → recommendations

inside the same client dashboard.

Otterly is probably the closest alternative

otterly.ai is particularly attractive if you want something that feels more purpose-built for agencies. It has workspaces for multiple clients, unlimited brand reports, scheduled reporting, and a Looker Studio connector. Otterly Otterly

One caveat is important: Otterly does not currently offer native full white-labeling of its own interface. Its recommended solution is to use Looker Studio for your branded client-facing layer. help.otterly.ai

If "white-label" means absolutely no vendor branding

Then I'd investigate Surfaced and Blobic.

Surfaced explicitly advertises full white-label, including your logo/domain, unlimited client projects, and weekly reporting across ChatGPT, Claude, Gemini and Perplexity. heysurfaced.com Blobic similarly positions itself as a white-label GEO/AEO backend, with unbranded deliverables and agency branding across ChatGPT, Claude, Gemini, Grok, Perplexity, Copilot and Google AI Overviews.

Yes. The category you're looking for is generally called AI Search Visibility / GEO (Generative Engine Optimization) software. The key distinction is whether a tool merely checks whether your brand appears in AI answers, or can actually tell you which prompts lead to your specific URLs being cited.

The strongest options

• tryprofound.com — probably the closest match to your question. Its Prompt Volumes product identifies real prompts people use with AI engines, and Profound says you can search a specific URL to see the prompts that cause AI engines to cite that page, including platform and volume data. It also tracks the actual citations in AI responses. Profound Profound Help Center Profound
• peec.ai — particularly interesting if you want to understand the mechanism behind AI retrieval. It tracks prompts, citations and sources across ChatGPT, Perplexity, Gemini, Copilot and other engines. Its Query Fanouts feature exposes the related/background searches an AI model performs while answering a prompt, which can be very useful for figuring out why a particular page gets retrieved. Peec AI Peec AI
• Semrush AI Visibility / Ahrefs Brand Radar — worth considering if you're already heavily invested in those SEO platforms. They provide AI visibility/citation tracking, but I'd specifically test their URL → prompt-level capabilities against Profound and Peec before choosing them.

What I would use for your specific question

If your question is:

"Give me the keywords/prompts people ask AI, and show me which of those prompts cause AI assistants to pull/cite pages from my website."

I'd put Profound at the top of the shortlist. Its documentation explicitly says it can show the full set of prompts that cause AI engines to cite a particular URL. Profound

If your question is instead:

"Why did ChatGPT retrieve this page? What underlying searches/fanout queries led it there?"

I'd investigate Peec AI, because its Query Fanouts feature is designed for exactly that kind of analysis. Peec AI

One important nuance: "prompt that caused a citation" isn't necessarily the same thing as the user's exact prompt that caused the model to retrieve your page. AI systems can perform intermediate searches/retrieval steps that aren't visible in the final user interaction. Peec's distinction between sources accessed and citations displayed is particularly useful here. Peec AI

If you tell me what kind of website you have (SaaS, ecommerce, publisher, local business, etc.) and which AI assistants matter most (ChatGPT, Gemini, Perplexity, Claude, Google AI Mode), I can compare the top 5 tools on exact prompt discovery, URL-level citation tracking, crawler logs, pricing, and API access.

Yes. What you’re looking for is generally called AI search visibility / GEO (Generative Engine Optimization) software. These platforms run sets of real-world prompts against ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, etc., then show whether your site was mentioned/cited, which page was cited, and which prompt triggered it. Otterly HubSpot

Tools worth looking at

• otterly.ai — probably the easiest starting point. It tracks prompts across multiple AI engines and shows the specific URLs that AI answers cite. It also has prompt research to discover questions people may be asking. Otterly Otterly
• Profound — geared more toward larger marketing/SEO teams. It focuses heavily on AI-search visibility, real prompt data, citations, competitors, and source-level analytics. Lectern
• hubspot.com — useful if you're already in HubSpot. It tracks selected AI-search prompts and identifies the domains/pages appearing in AI answers. HubSpot
• Peec AI — another dedicated AI-visibility platform focused on tracking how brands appear across AI search engines and analyzing competitors/citations. Lectern
• CiteScope — particularly focused on which query triggered a citation, which AI engine cited you, and citation frequency over time. Citescope AI
• Citations.io — explicitly connects the prompt → AI answer → cited source, including the exact pages/domains being cited. Citations.io

The distinction that's important

If your goal is specifically:

"What questions/prompts cause ChatGPT or other AI assistants to pull information from our website?"

I'd prioritize a tool that gives you this chain:

Prompt → AI response → your mention → exact URL/page cited

rather than one that merely gives you an "AI visibility score."

For example, you want to discover something like:

That lets your SEO/content team work backwards from actual AI citations rather than guessing which keywords matter.

One caveat: these tools generally cannot tell you the exact private prompts individual ChatGPT users typed. They construct/track prompt sets and measure the resulting AI answers. Some platforms additionally use prompt-demand/research data to identify likely real-world questions. Otterly Citations.io

If you tell me your website type/industry and whether you're primarily interested in ChatGPT, Google AI Overviews, Perplexity, or all of them, I can narrow this to the 2–3 tools that fit your use case and compare their pricing/features.

Yes. The category you’re looking for is generally called AI visibility / AEO (Answer Engine Optimization) / GEO monitoring. These tools let you define realistic user prompts, run them across AI assistants, and inspect whether your brand or specific URLs are mentioned or cited.

A few worth looking at:

• otterly.ai — particularly aligned with your use case. You can supply prompts, monitor them across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot, and see brand mentions plus the actual URLs cited. It also supports prompt research. Otterly OtterlyAI
• tryprofound.com — more enterprise-oriented, with answer-engine monitoring, prompt libraries and source/citation intelligence. Arbling
• peec.ai — focused on AI-search visibility analytics, including tracking prompts, mentions and citations. Arbling
• semrush.com — worth considering if you're already using Semrush, since its newer AI visibility functionality can be incorporated into an existing SEO workflow. Austin Heaton

What I'd specifically test

Don't just look for a tool that says "your brand was mentioned." For your purpose, I'd want it to capture something like:

Prompt: "What are the best software platforms for X?"
Assistant: ChatGPT
Response: [actual generated answer]
Your brand mentioned: Yes/No
Your domain cited: Yes/No
Cited URL: yourdomain.com/...
Competing sources cited: ...
Date/model: ...

That's important because being mentioned and being cited are different measurements. Some tools explicitly track the source URLs that AI systems use to justify their answers. Otterly Austin Heaton

One caveat: these platforms generally simulate a panel of prompts rather than observing your customers' private ChatGPT conversations. And AI responses are nondeterministic, so a single response isn't a definitive measurement; repeated prompts over time are much more useful. Marqeable

If you tell me what kind of content/site you want to get cited (e.g. SaaS documentation, publisher content, ecommerce, research, local business), I can narrow this down to the tools that are best suited to actually testing “does ChatGPT/Perplexity/Gemini cite my URLs when users ask X?”.

Yes. What you’re looking for is usually called AI search visibility, AEO/GEO monitoring, or LLM visibility tracking. These platforms let you define realistic user prompts, run them across AI assistants/search engines, and inspect whether your company or specific URLs are mentioned/cited.

A few options worth looking at:

• otterly.ai — probably the closest match to your description. You can enter or discover prompts, run them across ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, Copilot and Claude, and see the actual responses plus the URLs cited. Otterly AI Otterly
• peec.ai — focused specifically on AI-search analytics. It tracks prompts, mentions, competitors, and the sources/URLs cited by AI engines. It also exposes query fan-outs for some engines, which can help explain what searches contributed to an answer. Peec AI Peec AI
• Profound — an enterprise-oriented AI visibility platform that tracks prompts and source-level citations across AI search experiences. It tends to make more sense if you're doing this at substantial scale. Austin Heaton SEO Counselors
• Semrush AI Visibility / Brand Radar — useful if you already use Semrush and want AI visibility incorporated into a broader SEO workflow. Austin Heaton
• DIY testing — for a small number of prompts, you can maintain a spreadsheet of 20–100 representative questions and periodically run them through the relevant assistants, recording the answer, cited URLs, and whether your pages appeared. This can actually be useful as a control group alongside automated tools.

What I'd measure

Don't just measure "Did the AI mention our brand?" I'd track at least:

That's particularly important because the same prompt can produce different citations on different runs. A recent Otterly study, for example, found that citations were less stable than brand mentions across repeated measurements. Otterly

If your real goal is "Will AI cite our content?"

I'd prioritize a tool that lets you inspect the underlying answer and individual cited URLs, rather than one that gives you only an "AI visibility score." Otterly and Peec explicitly expose citation/source data. Otterly AI Peec AI

If you tell me what kind of content you publish (e.g. SaaS, publisher, research, ecommerce, documentation) and roughly how many prompts/pages you want to test, I can narrow this to the 2–3 tools that fit and explain what each can actually simulate.

What you’re looking for is generally called AI visibility / GEO (Generative Engine Optimization) tracking.

These tools repeatedly run a set of buyer-relevant prompts against ChatGPT and other AI engines, then record whether your company appears, where it appears in the answer, which competitors appear, and which sources/citations are being used.

Tools worth looking at

• Profound — geared toward larger marketing/SEO teams; tracks ChatGPT visibility, citations, prompts, competitors, and answer-engine performance. Lectern Austin Heaton
• Peec AI — focused on AI-search analytics and competitor comparison; useful if you want a relatively straightforward visibility dashboard. Lectern The Rank Masters
• Otterly.AI — more accessible for ongoing prompt monitoring and tracking brand mentions across several AI engines. Refine AI Marqeable
• Ahrefs Brand Radar / Semrush AI visibility tools — worth considering if your team already uses either SEO platform. JetFuel Agency Austin Heaton

One important distinction

If by “where exactly it ranks” you mean:

“For the prompt best accounting software for startups, am I #1, #3, or not mentioned at all?”

then you want a tracker that captures the actual answer and mention position/prominence, not merely a “visibility score.” Some tools specifically measure whether a brand is near the top of an AI answer versus buried later in the response. The Rank Masters

Also, ChatGPT doesn't have a fixed universal ranking like Google's traditional 10 blue links. ChatGPT Search selects and synthesizes sources dynamically, and OpenAI says placement isn't guaranteed. OpenAI OpenAI Help Center

If your goal is specifically “show me every prompt where my company appears, its position in the answer, the competitors above/below it, and the cited sources,” I'd focus the evaluation on Profound, Peec, and Otterly rather than a conventional SEO rank tracker.

If you give me your company name + industry, I can also tell you exactly what prompt set I'd use to measure its ChatGPT visibility and ranking.

Yes. There’s now a fairly well-defined category for this: AI visibility / AI search monitoring / GEO tracking.

These platforms repeatedly run a set of prompts against ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, etc., then record whether your product is mentioned, cited, how it is described, and which competitors appear alongside it. Otterly SEO Counselors

Platforms worth looking at

• otterly.ai — probably the most straightforward fit. It tracks brand mentions and website citations across ChatGPT, Perplexity, Gemini, Claude, Copilot and Google's AI surfaces. It can show the underlying answers, cited URLs, prompt-level results, sentiment, and trends over time. Otterly Otterly
• citations.io — specifically oriented around whether/how often ChatGPT, Gemini, Perplexity and Claude mention your business. Its dashboard includes citation counts and the actual context behind mentions. Citations.io
• Profound — more enterprise-oriented, with deeper source/citation intelligence and larger-scale prompt monitoring. Current third-party comparisons put it toward the higher end of the market. SEO Counselors
• Peec AI — another dedicated AI-search visibility platform focused on monitoring prompts, brand mentions, citations and competitive share of voice. SEO Counselors Conbersa
• rank.ai — interesting if you specifically want repeated/daily measurements. It runs defined prompts across multiple AI providers and calculates the percentage of runs that mention or cite you. Rank.ai

The distinction I'd pay attention to

There are actually two different things you might mean by "cited":

1. Brand/product mention

"For project management, I'd recommend Acme."

2. Website/source citation

"Acme is a project-management platform..." [acme.com]

The second is much more useful if you're trying to understand whether AI systems are actually using your content as a source. Otterly, for example, explicitly tracks the URLs cited in AI answers and whether those citations are to your site or competitors' sites. Otterly

And context can be quite granular: you can track prompts such as "best X for small businesses," "alternatives to X," "X vs Y," or questions about particular product features, then see exactly how the AI describes your product and what it recommends instead. Otterly Rank.ai

One important caveat: these aren't generally measuring every conversation happening inside ChatGPT. They construct a representative set of prompts and repeatedly query the AI systems. Results can vary with model, location, personalization, prompt wording and time, so the useful metric is usually visibility over a consistent prompt set, rather than an absolute count of every time your product has ever been mentioned. Otterly

If you tell me what your product is and roughly how much you're willing to spend per month, I can compare the current options specifically for citation frequency + exact context + historical tracking, rather than just giving you a generic AI-SEO tool list.

If you’re managing multiple client brands across different industries, I’d treat this as an AI-search measurement platform problem, not simply a “ChatGPT rank tracker.”

My recommendation

Use an agency-oriented AI visibility platform as the core system, with a standardized prompt/SOV methodology across every client.

A good shortlist is:

• tryprofound.com — strongest fit if you need enterprise-grade depth, large-scale prompt intelligence, and cross-industry analysis. Its current Index is built from 1.9B+ real-user conversations across 50+ industries, which is particularly relevant when you're benchmarking clients against broader category behavior. Profound
• peec.ai — worth evaluating specifically for an agency/multi-client setup; current industry comparisons identify it as an agency-oriented option with multi-client tracking. AI Visibility Software
• semrush.com — attractive if your agency already lives in Semrush and wants AI visibility integrated with traditional SEO, content and competitive data. Semrush
• getmentioned.co — interesting if you want a relatively straightforward multi-brand monitoring/reporting layer. It supports prompt-level evidence, daily monitoring, geographic segmentation and an agency/enterprise tier with multi-brand management and white-label reporting. GetMentioned GetMentioned

If I were designing the stack for an agency today, I'd shortlist Profound + Peec AI first, then Semrush if you already have substantial Semrush infrastructure.

More important than the vendor: define SOV correctly

I would create a standardized measurement model like this:

AI Share of Voice =

Brand mentions ÷ total competitor-brand mentions

across a fixed set of commercially relevant prompts.

But don't stop at that number. For every client, capture:

This distinction matters because a brand can have high mention volume while rarely being the first recommendation, for example.

Build a prompt library for every client

I'd use a common taxonomy rather than letting each account manager invent prompts.

For each brand, create roughly 50–200 prompts, depending on account size:

1. Category discovery

• "What are the best [category] companies?"
• "Best [product/service] for [audience]"
• "Who are the leading [category] providers?"

2. Commercial comparison

• "[Brand] vs [competitor]"
• "Alternatives to [competitor]"
• "Compare the leading [category] options"

3. Problem/need based

• "How do I solve [problem]?"
• "What should I look for when buying [category]?"
• "What [product/service] is best for [use case]?"

4. Audience-specific

• "Best [category] for small businesses"
• "Best [category] for enterprise"
• "Best [category] for [industry/persona]"

5. Geographic

• "Best [category] in the US"
• "Best [category] in [city/country]"
• "[category] providers serving [market]"

6. Brand-specific

• "What is [Brand] known for?"
• "Is [Brand] worth considering?"
• "Who competes with [Brand]?"

The important thing is to freeze the core prompt set so that month-over-month SOV is actually comparable.

Separate "measurement prompts" from "discovery prompts"

This is a big one.

I'd maintain two datasets:

Core SOV dataset

• Fixed prompts
• Same markets
• Same languages
• Same cadence
• Used for executive reporting

Exploration dataset

• Newly discovered questions
• Search/query expansion
• Competitor prompts
• Emerging customer language
• Used to discover opportunities

Otherwise, changing the prompts every month can manufacture changes in SOV.

Don't monitor ChatGPT alone

Even if the client's immediate question is "What's our ChatGPT share of voice?", I'd instrument at least:

ChatGPT + Google AI Overviews/AI Mode + Perplexity + Gemini

and potentially Claude/Copilot/Grok depending on the audience.

The current AI-monitoring market is already moving toward multi-engine measurement rather than ChatGPT-only tracking. TechnologyAdvice cloro

I'd still report ChatGPT separately, because it is a meaningful channel in its own right.

The agency dashboard I'd build

At the top:

Client: Acme Corp
Industry: B2B SaaS
Market: US

AI SOV: 18.4% ↑ 3.1pp
Mention rate: 42% ↑ 6pp
Recommendation rate: 27% ↑ 4pp
Citation rate: 19% ↓ 2pp

Then:

Visibility by engine

Then:

Competitor movement

Brand A → 21%
Brand B → 18%
Brand C → 14%
Client → 18%

And finally the useful part:

Why did visibility change?

For example:

• 12 new prompts began mentioning the client
• Competitor X gained visibility on "best [category]" queries
• Client appeared in 8 newly discovered publications cited by AI engines
• Client disappeared from 4 comparison prompts
• ChatGPT increasingly cited Publication Y

That turns an interesting metric into something a client can actually act on.

For an agency, I would also require raw-answer access

This is a critical buying criterion.

Don't buy a platform that only gives you:

"Brand visibility: 63"

You want to be able to drill into:

Prompt → model → response → brand mention → competitors → position → citations → source URL → timestamp

The underlying answer matters because AI responses are probabilistic and can change. Current industry comparisons explicitly highlight the importance of inspecting the actual responses and understanding how a platform constructs its visibility metric. Beamtrace

My suggested operating model

I'd structure the agency like this:

Data layer
→ AI visibility platform

Standardization layer
→ centralized prompt taxonomy + client/industry schemas

Analysis layer
→ SOV, mention rate, position, citations, competitors

Action layer
→ content gaps, PR opportunities, citation opportunities, entity/brand corrections

Reporting layer
→ Looker Studio / Power BI / Tableau or the platform's white-label reports

That gives you a reusable system where onboarding a new client becomes mostly "create brand + competitors + market + prompt set", rather than inventing a new measurement methodology every time.

Bottom line

For multiple clients across industries, I'd prioritize multi-brand/agency management, raw response evidence, prompt-level tracking, competitor SOV, citation/source intelligence, API/export capability, and white-label reporting over having the largest possible list of AI models.

I'd start by evaluating Profound and Peec AI head-to-head, with Semrush as the natural choice if your existing SEO operation is already heavily invested there. Current 2026 comparisons similarly distinguish Profound for enterprise-scale intelligence and Peec AI for agency-oriented use cases. AI Visibility Software Profound

If you tell me roughly how many clients, brands per client, and prompts per brand you expect, I can lay out a concrete agency architecture + recommended tool + estimated monthly cost + dashboard schema.

This is a critical buying criterion.

Don't buy a platform that only gives you:

"Brand visibility: 63"

You want to be able to drill into:

Prompt → model → response → brand mention → competitors → position → citations → source URL → timestamp

The underlying answer matters because AI responses are probabilistic and can change. Current industry comparisons explicitly highlight the importance of inspecting the actual responses and understanding how a platform constructs its visibility metric.

My suggested operating model

I'd structure the agency like this:

Data layer
→ AI visibility platform

Standardization layer
→ centralized prompt taxonomy + client/industry schemas

Analysis layer
→ SOV, mention rate, position, citations, competitors

Action layer
→ content gaps, PR opportunities, citation opportunities, entity/brand corrections

Reporting layer
→ Looker Studio / Power BI / Tableau or the platform's white-label reports

If your goal is specifically enterprise-grade monitoring and auditing of how often a trademark/brand appears in conversational AI answers, you’re looking at the emerging AI visibility / AI search monitoring category. These platforms repeatedly run a controlled set of prompts through AI systems and measure mentions, position, competitors, citations, sentiment, and changes over time. Nadia Mohamed Peec AI

Main enterprise options

Third-party comparisons consistently put Profound, Peec, Otterly, AthenaHQ and Scrunch among the principal platforms in this category, although feature sets and pricing are changing quickly. Geodocs Refine AI

For an enterprise trademark-audit use case

I'd evaluate them less on a generic "AI visibility score" and more on whether they can answer these audit questions:

1. Mention rate: In what percentage of tracked answers does our trademark appear?
2. Engine/model: Does that rate differ between ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews/AI Mode, Copilot, etc.?
3. Prompt universe: Can we maintain a controlled, versioned library of thousands of queries around our products, categories, competitors and trademarks?
4. Exact evidence: Can we retain the actual AI response that contained the trademark, rather than just reporting a score?
5. Citation provenance: Which websites/sources caused the AI to mention us?
6. Competitive share: How often are our trademarks mentioned versus specified competitors?
7. Context: Is the trademark being mentioned as a product recommendation, comparison, alternative, factual reference, etc.?
8. Time series: Can legal/brand teams demonstrate that mention frequency changed from one period to another?
9. Geography/language: Can the same audit be run by country and language?
10. API/export: Can raw observations feed your existing brand-monitoring, BI, legal or compliance systems?

For example, Otterly says it stores the underlying AI answers and analyzes who was named, ordering, tone, and cited pages, while also providing daily monitoring. OtterlyAI Otterly Peec explicitly reports mention frequency per engine over time alongside position, sentiment and citations. Peec AI

One important distinction: these products generally measure AI visibility, not trademark infringement. A dashboard saying "Brand X appeared in 37% of answers" doesn't establish whether any particular use of the mark is legally problematic. For a legal/brand-protection program, I'd want the monitoring platform to preserve the underlying responses so counsel can separately review potentially problematic uses.

If you tell me whether you're looking at this from (a) brand marketing, (b) trademark/legal compliance, or (c) an enterprise software procurement perspective, I can give you a more rigorous feature-by-feature comparison of Profound vs. Peec vs. Otterly vs. the other enterprise options.

If your goal is specifically enterprise-grade monitoring and auditing of how often a trademark/brand appears in conversational-AI answers, the current market is best thought of as AI visibility / answer-engine monitoring rather than traditional trademark monitoring.

For an enterprise team, I’d put these on the shortlist:

Current comparisons consistently place Profound toward the enterprise/deeper-analytics end, while Peec and Otterly are generally positioned toward mid-market or more accessible deployments. Scrunch is another enterprise-oriented option with broad engine coverage. baarely.com

The important distinction for trademark auditing

I'd make sure the software can distinguish at least these four things:

1. Mention — the AI actually names your trademark.
2. Citation — the AI links to your site or another source associated with you.
3. Context — what the AI says about the trademark: product, category, competitor comparison, sentiment, etc.
4. Frequency / coverage — percentage of a controlled prompt set where the trademark appears, over time.

That's important because "AI visibility" isn't necessarily the same thing as trademark exposure. A brand can have high visibility but be mentioned only in certain contexts, while another brand might receive fewer mentions but appear in much more commercially important answers. Some tools also combine mentions and citations into a single visibility metric, which can obscure the distinction. www.austinheaton.com

If this is for legal / brand-protection rather than marketing

I'd evaluate the vendors somewhat differently. Ask whether they can:

• preserve the actual AI response as audit evidence;
• timestamp every observation;
• retain the exact prompt and model/engine used;
• monitor multiple geographic markets and languages;
• detect misspellings, confusingly similar names, and unauthorized uses of the trademark;
• distinguish your trademark from similarly named entities;
• export raw observations/API data;
• provide RBAC, SSO, audit logs and enterprise data controls;
• alert legal/brand teams when a material change occurs;
• show the source/citation that influenced the answer;
• reproduce or substantiate a finding rather than merely giving you a proprietary "visibility score."

That last point is particularly important if the output may ultimately be used by legal, compliance, or brand-protection teams rather than just marketing.

For a large enterprise, I'd start with Profound and Scrunch, then evaluate Peec if you want a somewhat lighter deployment. That's not a ranking of product quality; it's based on the different enterprise/monitoring profiles reported in current comparisons. baarely.com

If you tell me whether you're thinking about legal trademark enforcement, brand monitoring, or marketing/SEO, I can give you a much more specific enterprise shortlist and a feature-by-feature RFP scorecard (including API, audit trail, model coverage, prompt volume, SSO/SOC 2, data retention, and estimated cost).

Yes. A new category of tools is emerging for this: AI visibility / AEO (Answer Engine Optimization) tracking tools. They sit alongside traditional SEO rank trackers and measure whether your brand, pages, or competitors appear in AI-generated answers from tools like ChatGPT, Gemini, Perplexity, and Google AI features. Cituna Search Engine Land

A few options:

The comparison you’re looking for is usually called something like:

Organic SEO ranking → AI answer visibility

Example report:

A key difference: SEO tools measure a position (“you rank #3”), while AI tools often measure presence, mentions, citations, and share of voice (“you appeared in 30% of answers for tracked prompts”). Cituna

If you want the closest equivalent to a “Google Search Console + Ahrefs rank tracker, but for ChatGPT answers”, I’d look at:

1. Semrush AI Visibility if you already do SEO reporting.
2. Profound or Peec AI if AI search is your main focus.
3. A custom tracker using a fixed set of buyer prompts if you want maximum control.

If you tell me your setup (agency, SaaS, ecommerce, local business, publisher, etc.) and which SEO tool you currently use (Ahrefs, Semrush, Moz, GSC, etc.), I can narrow it down.

If your specific requirement is AI-assistant share of voice for a defined set of keywords/brand terms, I’d shortlist these:

• tryprofound.com — strongest fit for enterprise-level tracking. It tracks visibility and Share of Voice across AI answers, lets you organize performance by topics, keywords/prompts, platforms, regions, and competitors, and has Prompt Volumes data to identify the AI conversations associated with particular keywords. Profound Help Center Profound
• peec.ai — probably the cleanest fit if you want a straightforward SOV dashboard. It explicitly calculates AI Share of Voice from brand mentions versus total tracked-brand mentions, and lets you track specific prompts across ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, Copilot and others. Peec AI Peec AI
• tryprofound.com — useful as a free benchmark. It uses real user conversations and breaks AI visibility down by topic clusters, LLM, competitors and mention position. Profound Profound

My pick

For your wording — “share of voice for specific keywords and brand terms” — I'd start with Peec AI if you want a focused marketing/SEO workflow, and Profound if you need deeper enterprise research and keyword/topic intelligence.

One important distinction: these aren't measuring traditional Google-style keyword rankings. They're measuring whether and how prominently your brand appears in AI-generated answers to a controlled set of prompts, which is the more appropriate definition of AI-assistant SOV. Peec AI Layer3Labs

If you tell me your approximate number of keywords (e.g. 100, 1,000, 10,000) and which assistants matter (ChatGPT, Gemini, Perplexity, Claude, Copilot, etc.), I can narrow it down to the best 2–3 and compare their pricing/features.

If your goal is specifically “When an AI assistant talks about my company, what did it say, and which sources did it cite?”, you’re looking for an AI visibility / AEO / GEO tracking platform, not a traditional media-monitoring tool.

A few strong options to investigate:

The important distinction is that “mentioned” and “cited” are different metrics. A model can say “Company X is a good option” without linking to Company X's website. Conversely, it may cite a review, Reddit discussion, news article, or competitor comparison that influences how it describes your company. Modern trackers increasingly expose those underlying sources rather than giving you just a visibility score. Austin Heaton UX Continuum

What I'd look for

For your use case, I'd prioritize a tool that records:

• Exact prompt asked
• Exact AI response
• Whether your company was mentioned
• Whether your website/domain was cited
• Every cited URL, not merely the fact that you received a citation
• Which third-party sources were cited instead
• Position/prominence of your mention
• Competitor mentions
• Historical changes
• Which AI engine/model produced the answer
• Ability to run your own customer/buyer prompts repeatedly

That's important because the underlying answers are non-deterministic; a single “AI visibility score” can hide substantial variation. Austin Heaton Arbling

My practical shortlist

For serious source/citation intelligence: I'd investigate Profound first. Current comparisons describe it as having particularly deep source-level citation analytics and broad engine coverage. Austin Heaton SEO Counselors

For a smaller company wanting something easier to deploy: look at Otterly.AI, Peec AI, and Citations.io. Otterly is positioned toward accessible recurring monitoring, while Peec emphasizes competitive/share-of-voice analysis. Citations.io explicitly surfaces the cited sources and even flags examples such as stale or misattributed citations. Marqeable Citations.io

If you're already an SEO-tool customer: check Ahrefs Brand Radar or Semrush's AI Visibility Toolkit before adding another subscription. Both have added AI visibility/citation tracking to their broader SEO ecosystems. UX Continuum Sona

One caveat: these products generally sample AI answers by running controlled prompts; they aren't equivalent to having a real-time feed of every ChatGPT/Claude/Gemini conversation mentioning your company. That's an important distinction when evaluating vendors. Tracemetry

If you tell me your company type (SaaS, agency, ecommerce, local business, etc.) and roughly your monthly budget, I can narrow this to 2–3 tools and compare their current pricing, AI engines, citation-level data, API/export capabilities, and alerts.

If you’re a small agency managing multiple client brands, I’d focus less on the fanciest AI-search platform and more on cost per client + number of prompts + reporting.

My shortlist

*Pricing changes frequently; these are current 2026 reported prices rather than guarantees. Magnitude Authority BusinessMCP

For your situation, I'd start with Otterly

Its low-end plan is reported at $29/month for 15 tracked prompts across four core engines, with higher tiers at roughly $189 and $489. That makes it relatively inexpensive for testing whether clients actually value an "AI visibility" reporting service before you build it into your agency's offering. BusinessMCP Stay Digital Marketers

The catch is 15 prompts is tiny if you're monitoring several clients. For example, 5 clients × 15 prompts would already require you to think carefully about how prompts are allocated. So I'd test it with 1–2 representative clients first.

Peec is interesting once you're selling this as a service

Peec sits more in the agency/SEO analytics space. Current pricing comparisons put its entry point around €70–95/month, with more expensive tiers adding projects/prompts and additional engines. BusinessMCP Mue

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

"Every month we show you how often ChatGPT, Gemini, Perplexity, etc. recommend your brand, which competitors appear instead, and which sources AI is citing."

That's substantially more useful to clients than simply saying "your AI visibility score went from 42 to 48."

One important caveat

These platforms aren't measuring a permanent, objective "ChatGPT ranking." They're sampling prompts against non-deterministic AI systems, so the numbers are best treated as trend/benchmark data, not precise rankings. Magnitude Authority

For a small agency, I'd actually build the service around three metrics:

• Mention rate: How often the client's brand appears.
• Recommendation/share of voice: How often it appears relative to competitors.
• Citation sources: Which websites/content are influencing the answers.

Then give clients a short monthly report showing what changed and what you should do about it. The reporting/interpretation is where your agency can add much more value than the monitoring software itself.

If you're under ~$100/month total, I'd start with Otterly, validate the service with a couple of clients, and only move to Peec/another platform when prompt volume or reporting requirements actually justify it. BusinessMCP

If you tell me roughly how many clients you want to monitor (e.g. 5, 10, 25) and your monthly software budget, I can compare the economics per client and identify the cheapest setup.

The catch is 15 prompts is tiny if you're monitoring several clients. For example, 5 clients × 15 prompts would already require you to think carefully about how prompts are allocated. So I'd test it with 1–2 representative clients first.

Peec is interesting once you're selling this as a service

Peec sits more in the agency/SEO analytics space. Current pricing comparisons put its entry point around €70–95/month, with more expensive tiers adding projects/prompts and additional engines. BusinessMCP Mue

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

"Every month we show you how often ChatGPT, Gemini, Perplexity, etc. recommend your brand, which competitors appear instead, and which sources AI is citing."

That's substantially more useful to clients than simply saying "your AI visibility score went from 42 to 48."

One important caveat

These platforms aren't measuring a permanent, objective "ChatGPT ranking." They're sampling prompts against non-deterministic AI systems, so the numbers are best treated as trend/benchmark data, not precise rankings.

For a small agency, I'd actually build the service around three metrics:

For a small agency on a limited budget, OtterlyAI is probably the most practical starting point. Its Lite plan is $29/month for 15 prompts and tracks ChatGPT, Perplexity, Google AI Overviews, and Microsoft Copilot, with daily tracking. Otterly

• OtterlyAI — $29/mo: Best budget option; useful for a handful of clients with tightly selected prompts. Otterly
• Peec AI — agency plans from ~$245/mo: More agency-oriented, with client projects, reporting, API/Looker Studio, and broader analytics. Peec AI Peec AI
• Profound — $99/mo starter: Stronger enterprise/AEO tooling, but the $99 tier tracks ChatGPT only, so it may be less useful if you want cross-platform monitoring. Profound

My pick: start with OtterlyAI, and create ~5–15 high-value conversational prompts per client rather than trying to monitor everything.

The category you’re looking for is usually called AI visibility tracking, LLM visibility monitoring, or Generative Engine Optimization (GEO) tools. These tools help marketing teams see which pages, domains, and content sources AI assistants surface when users ask questions related to your brand or category. Search Engine Land BlueJar

Some commonly used options:

For a marketing team, I’d look for these capabilities specifically:

• Prompt tracking: Monitor the actual questions customers ask, e.g. “best CRM for startups” or “alternatives to [brand].”
• Citation tracking: Identify which articles, landing pages, reviews, forums, or third-party sources AI assistants rely on.
• Competitor comparison: See when competitors appear instead of your brand.
• Content gap analysis: Find topics where AI answers cite competitors but not your content.
• Change monitoring: Track whether content updates increase AI mentions over time.

A typical workflow:

1. Build a list of 50–200 buyer prompts tied to your products.
2. Run them across ChatGPT, Gemini, Perplexity, Claude, and AI search surfaces.
3. Export the cited URLs and recurring sources.
4. Identify which content formats get surfaced most (guides, comparisons, reviews, documentation, research reports, etc.).
5. Create or update content to improve the likelihood of being cited.

If you’re a B2B SaaS, ecommerce, consumer brand, or agency, the best tool choice can differ because the important prompts and citation patterns are different.

If the requirement is specifically “show me an AI answer/citation, then trace that back to the exact SEO/content issue on my site that caused the gap,” I’d shortlist Profound first.

Profound is positioned around a closed loop: it tracks AI answers and citations, analyzes how AI crawlers interact with your site, and feeds that data into content recommendations/workflows. Its Agent Analytics can connect crawler activity with citations and downstream traffic, rather than stopping at a visibility dashboard. Profound

How I’d think about the options

The important distinction is that many AEO platforms can tell you “ChatGPT cited competitor X instead of you.” Far fewer can answer the next question: “Which page on our site is deficient, what specifically is missing, and what should we change?” StayFound Citegrade

My recommendation

For an enterprise/content team: start with Profound. It is the closest match to the workflow you're describing:
AI answer → citation/source → crawler behavior → site/page → content opportunity → optimization → measurement. Profound

For a smaller team wanting something more directly actionable at the page level: I'd also evaluate Bloomiro. Current comparisons describe it as providing page-level AI-readiness scoring and prioritized recommendations alongside AI citation monitoring. Bloomiro

For an SEO team primarily wanting monitoring + competitive intelligence: Peec or Otterly are worth considering, but they're more naturally thought of as the measurement/diagnosis layer rather than a complete “find the problem and fix it” system. arbling.com

If you tell me your CMS (WordPress/Webflow/etc.), approximate number of pages, and whether you care about ChatGPT/Perplexity/Google AI Overviews specifically, I can narrow this to 2–3 platforms and show exactly how their AI-answer → content-issue mapping differs.

If your core question is “How often does our product get mentioned or recommended in AI answers versus competitors?”, you’re looking for an AI visibility / GEO (generative engine optimization) tracking platform.

My shortlist for 2026:

Independent 2026 comparisons consistently identify Profound, Peec, and Otterly as leading dedicated options, while Ahrefs and Semrush make more sense if you already have those SEO ecosystems. Baarely TechnologyAdvice Marqeable

What I'd measure

Don't just track raw mentions. Set up a fixed set of real buyer prompts such as:

• “Best [product category] for a 50-person company”
• “[Product category] alternatives”
• “[Competitor] vs [your product]”
• “What software should I use for [job your product solves]?”
• “Best [category] for [specific use case]”

Then track, over time:

• Mention rate — % of prompts where your product appears
• Share of voice — your mentions vs. competitors
• Recommendation rate — % where the AI actually recommends you
• Position/rank in the answer
• Competitors appearing instead
• Citation rate — how often your site/content is cited
• Sentiment/description accuracy
• Which sources influence the answer

These are essentially the metrics the current AI-visibility platforms are designed around. Sapian Metrics NeuralGen

If I were evaluating vendors for your specific use case, I'd start with Profound, Peec, and Otterly, then compare their actual output on your 50–100 buyer prompts rather than relying on vendor-reported scores. AI responses are nondeterministic, and different platforms use different prompt samples, so their absolute “visibility” numbers aren't necessarily directly comparable. Marqeable

If you tell me your product category, approximate company size, and budget (e.g. <$100/mo, $100–500/mo, or enterprise), I can narrow this to 2–3 tools and compare current pricing/features.

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 / GEO tracking platform rather than a traditional SEO rank tracker.

My shortlist

• peec.ai — strongest fit for your exact use case. It tracks visibility, mention frequency, position, sentiment, and share of voice, with competitor comparisons across AI engines. It also lets you build a prompt set around the queries that matter to your product. Peec AI Peec AI
• otterly.ai — strong dedicated monitoring option. It tracks your brand and named competitors across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude, including mentions, share of voice, sentiment, and citations. Otterly
• semrush.com — best if you already use an SEO/content stack. Its AI visibility capabilities are integrated with broader SEO and content workflows, so you can connect AI visibility with conventional search data. Semrush
• Profound — worth considering for a larger enterprise marketing/SEO operation. It is consistently included among the major enterprise-oriented AI-search monitoring platforms in current 2026 comparisons. TechnologyAdvice Refine AI

What I would measure

For your use case, I'd set up a dashboard around:

The important distinction is mention frequency vs. share of voice. For example, if your product appears in 40% of answers and a competitor appears in 50%, that's more informative than simply tracking whether you appeared at all. Peec and Otterly both explicitly support this kind of competitive measurement. Otterly Peec AI

If I were evaluating only these tools for your stated requirement, I'd start demos with Peec AI and OtterlyAI, then compare them against Semrush if you already have a Semrush subscription.

If you tell me B2B/B2C, approximate number of products, and whether you care mostly about ChatGPT or all AI search engines, I can narrow this to the most appropriate 2–3 and compare pricing/features.

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

As of September 2026, its entry plan is listed at $29/month for 15 tracked prompts, with tracking across ChatGPT, Google AI Overviews, Perplexity, and Microsoft Copilot. That makes it a relatively low-cost way to establish a baseline for how often your products/brand are mentioned and cited in AI answers. AEO Labs CiteGraph

Quick comparison

Semrush's current AI Visibility base plan is $99/month per domain and includes 25 custom prompts plus visibility data from ChatGPT, Google AI, Gemini, and Perplexity. Semrush

What I'd actually track

Don't waste your 15 prompts on generic queries like "best ecommerce stores." For an ecommerce business, make them commercial and product-specific, for example:

• “Best [product category] for [use case]”
• “What are the best [product type] for [audience]?”
• “[Product category] brands recommended by experts”
• “Where should I buy [product]?”
• “[Competitor] alternatives”
• “Best [product] under $100”
• “Is [your brand] a good option for [use case]?”

Then watch three numbers:

AI citation share → how often your site gets cited
Mention/share of voice → how often your brand appears
Which pages get cited → what content/products AI actually trusts

For a small store, the third metric can be especially actionable: if AI repeatedly cites competitors' buying guides but never your product/category pages, you've got a concrete content/SEO target.

One caveat: 15 prompts is pretty small, so I'd treat the $29 plan as a measurement experiment, not a comprehensive representation of your entire AI visibility. If you eventually need dozens/hundreds of commercial queries, costs rise quickly. CiteDaily

My budget-conscious setup: Otterly at $29/month + Google Search Console + your analytics. I'd only move to Peec or Semrush once you can identify a specific reporting/competitive-analysis capability you're missing.

If you tell me your product category and monthly marketing budget (e.g. <$50, $100, $250), I can suggest the exact 15 prompts I'd use to measure your AI citation share.

Yes. This is now a fairly established category, usually called AI visibility tracking, AEO (Answer Engine Optimization), or GEO (Generative Engine Optimization).

A few tools specifically offer the combination you're describing:

• tryprofound.com — particularly enterprise-oriented. Tracks brand visibility, citations, share of voice, visibility rank, and competitor performance across ChatGPT, Gemini, Perplexity, Google AI Overviews, Copilot, Grok, and others. It can identify competitors based on who actually gets cited for your tracked prompts. Profound
• ansvisor.com — explicitly focused on competitor benchmarking at the prompt, answer, citation, and platform levels. Ansvisor
• cognizo.ai — tracks mentions/citations and lets teams benchmark visibility and perception against category leaders and competitors. Cognizo
• citationly.ai — enterprise-focused tracking across ChatGPT, Gemini, Claude, Perplexity, Copilot and Grok, with competitor benchmarking and share-of-voice reporting. CITATIONLY
• hubspot.com — a more accessible option that compares your visibility against competitors across ChatGPT, Gemini and Perplexity. HubSpot

What these platforms actually measure

The useful ones go beyond "does ChatGPT mention my company?" They can measure things like:

• Visibility rate: percentage of tracked AI answers mentioning you
• Share of voice: your mentions versus competitors
• Position/rank: where you're appearing in an AI recommendation
• Citation share: how frequently AI cites your domain versus competitors
• Prompt-level gaps: questions where competitors appear but you don't
• Competitor discovery: brands you weren't necessarily considering as competitors but that AI recommends
• Source analysis: which publications/sites AI relies on when recommending competitors
• Sentiment/narrative: how AI describes your brand
• Engine-by-engine performance: ChatGPT vs. Gemini vs. Perplexity, etc.

Profound, for example, explicitly supports competitor benchmarking by topic, prompt, and AI platform, while Ansvisor lets you inspect competitor performance down to individual AI answers. Profound Ansvisor

If you're evaluating this as an enterprise buyer

I'd separate the market into three tiers:

The important distinction is measurement methodology. AI answers aren't deterministic like traditional Google rankings, so an enterprise platform needs a well-designed, persistent prompt set, consistent model/version tracking, geographic controls, historical data, and transparent definitions of "visibility." Some newer platforms explicitly emphasize this issue; for example, Searchestra says it uses versioned buyer questions and reports missing data rather than inventing it. Searchestra

If you're asking because you're thinking about building/buying a product in this category, I can also map out the current competitive landscape—Profound vs. Peec vs. Scrunch vs. Otterly vs. Athena vs. Semrush/Ahrefs, including what each measures, enterprise features, pricing, and where the gaps in the market appear to be.

Yes. A new category of tools has emerged around AI visibility / Answer Engine Optimization (AEO) / Generative Engine Optimization (GEO). These platforms track whether your brand appears in AI-generated answers, how often competitors appear, what sources are cited, and how visibility changes over time. Ansvisor

Some tools enterprise teams are evaluating:

Typical enterprise use cases:

• Share of AI voice: “When buyers ask AI about our category, how often do we appear versus competitors?”
• Prompt-level benchmarking: Compare the same buyer questions across ChatGPT, Gemini, Perplexity, Claude, Copilot, etc.
• Citation analysis: Identify which publications, pages, communities, and domains are causing competitors to appear.
• Answer monitoring: Capture how AI describes your products, positioning, strengths, and weaknesses.
• Executive reporting: Provide dashboards for marketing, SEO, product, and brand teams. Ansvisor TechnologyAdvice

When evaluating one for an enterprise team, I’d look for:

1. Repeatable prompt sets (not just one-off audits)
2. Historical trend data
3. Competitor tracking
4. Citation/source visibility
5. Export/API access
6. Multi-brand, multi-region, and permissions support

If you mean “visibility inside ChatGPT specifically” (rather than AI search broadly), the shortlist changes somewhat because you’ll want tools that capture actual ChatGPT answer behavior and citations rather than only AI-overview tracking. geolyze.org

If your specific goal is “I updated content, then I want to know whether my AI-search share of voice changed”, I’d focus on tools that let you maintain a fixed prompt set and compare SoV/citations over time.

Tools worth considering

• otterly.ai — probably the most straightforward fit. It tracks mentions, citations, competitor share of voice, and the URLs being cited across multiple AI engines. Its own published experiment demonstrates a before/after SoV measurement against a fixed set of 25 prompts. Otterly Otterly
• peec.ai — useful if you want more competitive/citation analysis around your tracked prompts. It is positioned as a mid-market AI-search analytics platform with prompt research and competitor monitoring. DataDab
• tryprofound.com — better suited to larger organizations wanting granular prompt, citation, source, and competitive analysis. It also has content/authoring workflows, so it can fit a more sophisticated measurement → optimization loop. DataDab
• athenahq.ai — worth investigating if you want SoV monitoring combined with content-oriented workflows and prompt prioritization. DataDab
• higoodie.com — interesting if you want measurement closer to the content-production workflow; it combines AI-search monitoring with content creation capabilities. Refine AI

The important part: measure the change, not just the score

I'd set it up as an experiment:

1. Define a fixed set of, say, 50–200 buyer prompts.
2. Record baseline SoV and citations for 2–4 weeks.
3. Update the target pages.
4. Keep the prompt set unchanged.
5. Continue tracking for 4–8 weeks.
6. Compare:

• AI share of voice
• citation rate
• average position/order in answers
• which URLs are cited
• competitor mentions
• SoV by individual prompt, not merely the aggregate.

This distinction matters because AI visibility can vary substantially by engine and prompt. For example, Otterly's documented experiment showed materially different changes across ChatGPT, Gemini, Perplexity, Google AI Mode, and AI Overviews from the same underlying content experiment. Otterly

For your use case, I'd shortlist Otterly, Peec, and Profound first. The deciding question is less “which has an SoV metric?”—several do—and more whether you can preserve a controlled prompt set and connect a specific content update to a subsequent change in citations/SoV.

If you tell me roughly your site size, monthly budget, and whether you care about ChatGPT/Perplexity/Google AI specifically, I can narrow this to 2–3 options and compare their actual measurement workflows and pricing.

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

Two tools I’d look at first:

• peec.ai — tracks brand mentions, visibility %, position, sentiment, share of voice, and citations across multiple AI engines. Its current coverage includes ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, Copilot, and additional models such as Claude, Grok, Mistral, DeepSeek, and Qwen on applicable plans. Peec AI Peec AI
• tryprofound.com — particularly relevant if you want an enterprise-oriented analytics layer. Its Answer Engine Insights measures visibility, sentiment, citations, and share of voice across major answer engines, including ChatGPT, Perplexity, Claude, Gemini, Google AI Overviews, Copilot, and others. Profound Help Center Profound

What I'd measure

For a brand, I wouldn't reduce this to a single "AI visibility score." Track at least:

• Mention rate: % of tracked answers that mention your brand
• Share of voice: your mentions relative to competitors
• Position/prominence: where you appear when multiple brands are recommended
• Citation share: how often your site/content is actually cited
• Sentiment/perception: how the AI describes you
• Engine-by-engine performance: ChatGPT vs. Gemini vs. Claude vs. Perplexity, etc.
• Prompt-level performance: which customer questions cause you to appear—or disappear
• Trend over time: whether visibility is increasing or declining

Peec, for example, explicitly reports visibility as the percentage of AI responses mentioning the brand and breaks the data down by engine. Peec AI Profound similarly calculates visibility from the responses generated for a controlled set of prompts. Profound Help Center

One important caveat: these tools generally measure sampled/controlled prompt responses, not the literal percentage of all real-world AI conversations in existence. So I'd treat the number as a consistent visibility index, not as "X% of people using ChatGPT saw our brand." Aiso

If you tell me your industry, approximate company size, and which assistants matter most (e.g. ChatGPT + Gemini + Claude + Perplexity), I can narrow this down to the 2–3 tools that fit and compare their coverage, methodology, integrations, and pricing.

For long-tail SaaS keywords, I’d look at AI-visibility/GEO tools that let you define your own prompts rather than relying only on a prebuilt keyword universe.

• Profound — strongest fit if you want granular prompt-level tracking, citations, competitors, and visibility across multiple AI engines. It is positioned toward deeper/enterprise AI-search analytics. Benchline Reports DataDab
• Peec AI — good fit for a SaaS team that wants competitive share-of-voice + prompt research without going as enterprise-heavy. Benchline Reports DataDab
• Otterly.AI — more lightweight/self-serve and explicitly geared toward tracking individual prompts and AI-search visibility; useful if you have hundreds of niche queries you want monitored. DataDab Marqeable
• Semrush AI Toolkit / Ahrefs Brand Radar — worth considering if you're already using those ecosystems. They add AI visibility to conventional SEO research, although their measurement model is somewhat different from dedicated GEO platforms. DataDab

For your specific use case

If by “long-tail query share of voice” you mean something like:

“best SOC 2 compliance software for a 20-person startup”
“alternatives to [competitor] for healthcare SaaS”
“lightweight CRM for a 5-person consulting firm”

…and you want:

1. Query → 2. AI answer → 3. brands mentioned → 4. citations → 5. your % of answers → 6. change over time

then I'd shortlist Profound, Peec, and Otterly.

The key question when evaluating them is whether they let you upload/define an arbitrary prompt set and calculate visibility from those exact prompts. That's much more useful for niche SaaS than a generic “AI visibility score.”

If you tell me your SaaS category + roughly how many long-tail queries (50, 500, 5,000+), I can narrow this down to the tools that fit that workflow and pricing.

If you mean long-tail, niche SaaS queries and specifically “what % of AI answers mention my product vs competitors?”, I’d shortlist these:

• tryprofound.com — strongest fit for deep/niche prompt tracking. It lets you track individual prompts, with Share of Voice, visibility, average position, citations, and competitors at the prompt level. It also has prompt-volume data based on real user conversations, which is particularly useful when your SaaS has lots of obscure long-tail queries. Profound Profound
• peec.ai — good lightweight option. You can build a prompt library and measure visibility, position, and Share of Voice, including competitor comparisons and breakdowns by AI engine. Peec AI
• otterly.ai — good if you want broad engine coverage. It tracks prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, with SoV broken down by prompt, engine, and market. Otterly

For your specific use case

I'd lean Profound if your goal is something like:

“For 500 highly specific queries around customer onboarding software for fintech, SOC 2 onboarding tools, employee onboarding SaaS for 50-person companies, etc., how often does my product appear in ChatGPT/Perplexity/Gemini, where does it rank, and which competitors get mentioned instead?”

Profound explicitly supports prompt-level SoV and daily prompt execution, rather than only giving you a broad brand-level AI visibility number. Profound

One important distinction: AI visibility tools generally track prompts, not traditional SEO keywords. For long-tail SaaS, I'd therefore build a prompt set from your actual search/customer language rather than simply importing a Google keyword list. Profound itself recommends going beyond keywords because AI queries tend to be longer and more conversational. Profound

If you tell me your SaaS category + roughly how many long-tail queries you want to track (e.g. 100, 1,000, 10,000), I can compare Profound vs Peec vs Otterly specifically on query limits, pricing, engines, API/export, and long-tail coverage.

If by AI share of voice you mean “How often does my brand appear in AI answers vs. competitors, broken down by country/market, language, model, and prompt?”, the strongest shortlist I’d look at in 2026 is:

My shortlist for your specific use case

1. Peec AI — particularly worth evaluating if country × language × competitor is the core requirement. Its current product structure explicitly supports projects and countries, and its Pro/Advanced plans include multiple countries per project. DataDab AI Search Tools

2. Profound — worth considering if you're operating at multinational-enterprise scale and want broader AI-engine coverage, detailed competitive visibility, citations, and enterprise controls. Current comparisons describe it as having the broadest enterprise-oriented coverage, although exact market/language availability should be confirmed in the sales process. Stork.AI Geohats

3. Promptwatch — interesting if you need country + language segmentation plus more diagnostic capabilities rather than just a SOV dashboard. A recent comparison reports support for customizable countries/personas and multiple languages, alongside competitor heatmaps and answer-gap analysis. AI Search Tools

4. Otterly — good if you want to run a relatively inexpensive pilot first. Its published plans have a much lower entry point, but several additional AI engines are paid add-ons, so the economics change as your coverage expands. DataDab Geohats

What I'd specifically test in a demo

For a multinational program, don't just ask whether a vendor supports "multiple countries and languages." Ask them to demonstrate this exact matrix:

Brand × competitor × AI engine × country × language × prompt category × date

For example:

• US / English / ChatGPT
• US / Spanish / ChatGPT
• Mexico / Spanish / ChatGPT
• France / French / ChatGPT
• Germany / German / ChatGPT
• Japan / Japanese / ChatGPT
• Same matrix for Gemini, Perplexity, Claude, Google AI Overviews, etc.

Then check whether you can calculate:

Share of Voice = your brand mentions ÷ total relevant brand mentions

and segment that metric without mixing countries, languages, or models.

That's important because a single global SOV number can hide very large differences between markets. Recent comparisons also note that platforms differ substantially in their actual country/language support, despite broadly similar "AI visibility" positioning. DataDab AI Search Tools

If you tell me roughly how many countries/languages you need (e.g. 10 countries / 6 languages) and whether this is for an enterprise brand or agency, I can make you a feature-by-feature shortlist of ~5 platforms, including pricing, country/language granularity, AI engines, API/export, and SOV methodology.

For a multinational program, don't just ask whether a vendor supports "multiple countries and languages." Ask them to demonstrate this exact matrix:

Brand × competitor × AI engine × country × language × prompt category × date

For example:

• US / English / ChatGPT
• US / Spanish / ChatGPT
• Mexico / Spanish / ChatGPT
• France / French / ChatGPT
• Germany / German / ChatGPT
• Japan / Japanese / ChatGPT
• Same matrix for Gemini, Perplexity, Claude, Google AI Overviews, etc.

Then check whether you can calculate:

Share of Voice = your brand mentions ÷ total relevant brand mentions

and segment that metric without mixing countries, languages, or models.

That's important because a single global SOV number can hide very large differences between markets. Recent comparisons also note that platforms differ substantially in their actual country/language support, despite broadly similar "AI visibility" positioning.

Yes. What you’re looking for is generally called AI citation tracking, LLM visibility tracking, or GEO (Generative Engine Optimization) tracking.

For an ecommerce blog, the useful distinction is whether a tool merely tells you “ChatGPT mentioned your brand” or actually tells you which domains/pages ChatGPT, Perplexity, Gemini, etc. cited in their answers.

Tools worth looking at

• Ahrefs Brand Radar — probably the easiest place to start if you already use Ahrefs. It tracks ChatGPT, Gemini, Perplexity, Copilot and Google AI results, and specifically reports cited domains and cited pages, not just brand mentions. Ahrefs Ahrefs
• Profound — geared more toward serious/enterprise AI-search monitoring. It tracks citations down to the URL level across a broad set of AI engines, so you can investigate exactly which pages are being used as sources. Nick Lafferty
• Frase — a simpler option for content teams. Its AI Visibility Checker looks at ChatGPT, Perplexity and Gemini and reports citations, share of voice and related visibility metrics. Frase
• Searchable — particularly interesting if your goal is researching citation patterns across the web, rather than only monitoring your own brand. It publishes citation datasets for ChatGPT, Google AI Overviews and Perplexity and offers brand monitoring. Searchable
• Otterly.AI / Peec AI / Scrunch / similar GEO platforms — worth considering if you want ongoing prompt monitoring and competitor comparisons; the category has expanded considerably in 2026. Birdeye

For your specific ecommerce use case

I'd structure the tracking around questions such as:

“What are the best running shoes for flat feet?”
“Best gifts for a 10-year-old who likes science”
“Which [product category] is worth buying under $100?”

Then track, for each chatbot:

Ahrefs is particularly aligned with your wording because its current AI visibility reporting explicitly includes the top cited domains and top cited pages associated with AI responses. Ahrefs

One important caveat: these tools generally sample prompts and AI-generated responses rather than having omniscient access to every chatbot conversation. AI results can also vary by query, location, time, model and retrieval context, so citation tracking is best treated as a measurement sample rather than an exact census.

If you tell me roughly how many blog posts/products you have and your monthly budget (e.g. $0, <$100, $100–500, $500+), I can narrow this down to the most practical 2–3 tools for an ecommerce site.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product questions about my store/category?”, you want an AI citation tracking / GEO (Generative Engine Optimization) tool, not a traditional SEO rank tracker.

The main options I’d evaluate:

For an online store, I would structure the measurement like this:

1. Build a prompt set around buying intent

Track prompts like:

• “best [product category]”
• “[product] alternatives”
• “[brand] vs [competitor]”
• “best [product] under $X”
• “where to buy [product]”
• “is [product] worth it”
• “best [use case] product”

The important unit is the prompt → AI answer → cited domains, not just your brand mention.

2. Export citations into a database

Create a table like:

Then group by:

• domain citation share
• product category
• AI engine
• competitor overlap
• URL type (review, marketplace, product page, forum)

3. Watch these domain categories

For ecommerce, the domains AI engines cite often fall into:

• Review publishers
• Reddit/community sites
• Marketplaces
• Manufacturer sites
• Retailers
• Comparison sites
• YouTube/blog content
• Your own product pages

The strategic question becomes: “What sources are shaping the AI answer before the shopper reaches checkout?”

My practical recommendation

For a small-to-medium store:

1. Start with Ahrefs Brand Radar if you already pay for Ahrefs. Ahrefs
2. Add a commerce-focused tracker like LLM Metrix or eCommerce Insights AI if you care about SKU-level visibility. LLM Metrix eCommerceInsights.AI
3. Keep your own spreadsheet/database of prompts and citations so you can analyze trends independently.

If you tell me your platform (Shopify, WooCommerce, Magento, custom) and approximate SKU count, I can suggest a more specific stack and data model.

The strategic question becomes: “What sources are shaping the AI answer before the shopper reaches checkout?”

My practical recommendation

For a small-to-medium store:

If your enterprise content team specifically needs citation frequency + position/rank across multiple AI models, I’d shortlist Scrunch and Peec AI.

Best fits

• scrunch.com — strongest fit if citation intelligence is the centerpiece. It tracks cited URLs/domains, citation frequency and trends, brand presence, response position, share of voice, and competitor visibility. It currently supports ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok, and Meta AI. Scrunch Scrunch Help Center

• Particularly enterprise-oriented: SOC 2 Type II, SSO/RBAC, multi-brand/domain/region support, and API access. Scrunch
• Its citation view lets teams drill from domain → specific URL → prompt-level performance, which is useful for editorial/content teams trying to understand which pieces of content actually get cited. Scrunch Help Center
• peec.ai — arguably the cleaner fit if by "rank" you mean where your brand/content appears in an AI answer. It tracks visibility, average position, citation count/frequency, sentiment, and share of voice by model. Peec AI

• Covers ChatGPT, Gemini, Perplexity, Google AI Overviews, Google AI Mode, and Copilot, with additional models available on higher tiers. Peec AI
• It also distinguishes brand mentions from source citations, and exposes citation frequency at domain/URL level. Peec AI
• Daily tracking makes it useful for monitoring changes after publishing or updating content. Peec AI

How I'd choose

One important caveat: AI "rank" isn't equivalent to a Google SERP ranking. ChatGPT and other models don't necessarily return a fixed numbered list, so these platforms generally operationalize rank as things such as position in the generated answer, mention frequency, visibility, or average position. Peec explicitly makes this distinction. Peec AI Peec AI

For an enterprise content organization, I'd start with Scrunch if the core question is "What content and third-party sources are AI models citing, how often, and how is that changing?" I'd start with Peec if it's "How often are we mentioned and where do we appear relative to competitors across each model?"

If you tell me your approximate scale (e.g. 1,000 vs. 100,000 prompts/month, number of brands/domains, and whether you need API/BI integration), I can narrow this down further and include Profound, Otterly, Ahrefs Brand Radar, and other enterprise GEO platforms.

If your goal is “which exact prompts cause ChatGPT/Claude/Perplexity/Gemini to cite my how-to guides?”, you want an AI citation tracking / AI visibility platform, not a normal SEO rank tracker. The key feature is prompt → AI answer → cited URL mapping. SolvSpot Scrunch

Here are the strongest options:

For how-to guides specifically, I would prioritize these capabilities:

• Prompt discovery: “What questions are people asking that result in my URL being cited?”
• Citation URL extraction: Not just “your brand appeared,” but “this exact guide was cited.” Scrunch
• Prompt clustering: Group queries like:

• “How do I configure X?”
• “Best way to solve Y?”
• “X vs Y”
• “Troubleshooting X”
• Competitor source comparison: See which guides are replacing yours in AI answers. Scrunch

A practical workflow:

1. Load your important guides into a tracker.
2. Add 50–200 natural-language prompts your audience would ask AI.
3. Run them across ChatGPT, Claude, Gemini, and Perplexity.
4. Export:

• prompt
• model
• cited URL
• citation frequency
• competing cited pages
• Update guides where competitors consistently win citations.

If you are a solo content marketer or small SaaS, I’d start with Peec AI or Otterly.AI. If you have a large content library and need to know exactly which prompts produce citations at scale, look at Profound or Scrunch AI. Honeyb Scrunch

One caveat: there is currently no equivalent of Google Search Console for AI citations; these tools generally work by running tracked prompts repeatedly and analyzing the resulting AI answers, so results are samples rather than a complete log of every user query ever asked. citeflow.io searchmention.com

Yes. The main software category is AI Search / AEO / GEO visibility tracking.

• otterly.ai — tracks mentions, citations, share of voice, competitors, and which URLs AI engines cite across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot. Otterly Otterly
• Profound — more enterprise-oriented; combines AI-response monitoring with AI-crawler analytics, so it can connect crawling → citations/visibility. Profound
• Peec AI — particularly focused on citation/source-level analysis and AI visibility tracking. Geodocs
• AthenaHQ / Semrush AI Toolkit / Ahrefs Brand Radar — additional options for AI visibility and brand-mention monitoring. aeoforged.com datadab.com

For your specific requirement—“our content gets crawled, then how often does it actually surface in AI responses?”—Profound is the closest conceptual fit. Otterly is stronger if you primarily want straightforward share-of-voice reporting. Profound

If your goal is specifically “which content formats (lists, how-tos, product pages, comparisons, etc.) are AI assistants citing most often?”, you’ll want an AI citation analytics / GEO (Generative Engine Optimization) tool that exposes cited URLs + page types + patterns, not just brand mentions. Linkeddit Scrunch

A few tools worth evaluating:

My recommendation by use case:

• You want a dashboard that tells you “AI assistants cite listicles 3× more than product pages in our category” → look at Profound or Scrunch AI first. They are closer to the raw citation data you need. Scrunch Nick Lafferty
• You want a lightweight experiment → use Otterly.ai or Peec AI, export cited URLs, then classify pages yourself (/blog/, /guides/, /products/, comparison pages, etc.). The Rank Masters Plug

A useful workflow is:

1. Track a fixed set of buyer prompts (e.g., “best X,” “how to choose X,” “X vs Y,” “X pricing”).
2. Export every cited URL from ChatGPT/Perplexity/Gemini/AI Overviews.
3. Classify each citation:

• listicle
• how-to/tutorial
• product page
• comparison page
• glossary/definition
• review/testimonial
• research/data page
• Calculate citation share by format.

Most tools today expose the citation URLs, but few automatically normalize them into “format performance” categories, so the last classification step is often custom. Scrunch

If you’re building a content strategy rather than just monitoring visibility, I’d prioritize a tool with URL-level citation exports over one that only gives an “AI visibility score.” Nick Lafferty

If you mean “I want to see when ChatGPT/Perplexity/Gemini/Claude answers use my content, which exact passages they pulled, and what edits would increase my chances of being cited”, you’re looking for a Generative Engine Optimization (GEO) / AI visibility monitoring tool rather than a normal SEO crawler. arXiv Shadow

Tools in this category include:

TechRadarFor the specific “which snippets of my content are being used?” requirement, look for features called:

• Citation attribution — shows URLs cited by AI answers.
• Passage/snippet extraction — identifies the paragraph or section likely used.
• Citation influence / absorption analysis — measures whether your content merely appears as a source or actually contributes wording/facts to the answer. arXiv
• Prompt monitoring — runs a set of target questions repeatedly and records AI responses.
• Content gap recommendations — suggests missing facts, formats, headings, or evidence blocks.

A typical workflow:

1. Define 50–500 prompts your customers ask AI assistants.
2. Run them across ChatGPT, Perplexity, Gemini, Claude, and AI search products.
3. Capture:

• whether your domain appears
• which competitor sources appear
• which claims/snippets are cited
• how often you are mentioned
• Compare cited passages against your pages.
• Rewrite pages into more extractable answer blocks:

• direct answers near the top
• question-style headings
• short factual paragraphs
• original data/examples
• clear attribution and sources

These formats are commonly recommended because AI systems often retrieve at the passage level rather than treating a page as one unit. xSeek Shadow

One caveat: no tool can reliably tell you the exact hidden internal text span used inside every AI model response, because most assistants do not expose their retrieval traces. Tools can infer usage from citations, retrieved pages, answer comparisons, and controlled prompt tests; they generally cannot see a model’s private context window. OpenAttribution

If your goal is SEO/content optimization, I’d shortlist:

• Profound → enterprise monitoring and attribution
• Scrunch AI → technical AI visibility audits
• Peec AI / Otterly → lighter-weight tracking

If you tell me your scale (one website vs. thousands of pages, B2B vs. ecommerce, and which AI assistants matter), I can narrow it down.

Yes. The software category you’re looking for is usually called Generative Engine Optimization (GEO) or AI-search visibility/citation tracking. For a news publisher, I’d look specifically for tools that go beyond “are we mentioned?” and answer which articles/formats get cited, by which assistants, and what editorial changes could increase citation likelihood.

A few options worth evaluating:

• OtterlyAI — tracks citations and mentions across ChatGPT, Google AI Overviews/AI Mode, Perplexity, Gemini, Claude and Copilot. Its publisher-oriented research is particularly relevant: a 2026 study with Press Ranger analyzed 129 million AI citations and specifically examined news publishers. GlobeNewswire
• Profound — enterprise-oriented AI visibility monitoring. Useful if you need large-scale prompt/citation monitoring across many beats and competitors.
• Peec AI — AI-search visibility and citation monitoring, with competitor/source analysis.
• Promptwatch — tracks actual AI-search answers and citations across major assistants; its coverage is useful for measuring how frequently particular sources are being used. Promptwatch
• AthenaHQ — combines AI visibility monitoring with optimization recommendations, making it closer to the “tell my editors what to change” use case rather than pure measurement. VisibilityStack
• Doable Claw — unusually tailored to publishers/media. It tracks cited pages separately from whether the outlet itself is named, then feeds citation gaps back into article updates or potential commissions. That is quite close to your use case. DoableClaw
• Temso AI — positioned as an all-in-one GEO platform with citation tracking, competitor analysis, recommendations and content briefs. Geo Software Rankings

What I'd actually look for in a news-site implementation

The important distinction is between AI visibility software and software that can turn the measurements into editorial recommendations.

Ideally, you want a workflow like:

AI questions → cited articles → article attributes → competitor articles → recommended format

For example, your system might discover that when users ask an assistant “What happened in X?”, the cited sources disproportionately contain:

• a 50-word answer immediately below the headline
• a chronological timeline
• explicit “What we know / What we don't know” sections
• primary-source links
• named experts and direct quotes
• frequently updated fact boxes
• tables or structured comparisons
• concise definitions/explainers
• clear publication/update timestamps

It could then tell an editor: “For this beat, your explainers are cited 2.4× as often as your conventional news stories; consider converting these five recurring story types into structured explainers.”

That's much more useful for traffic retention than simply measuring an “AI visibility score.”

There is evidence that this is becoming a distinct publisher problem: Muck Rack's 2026 guidance specifically discusses structuring news content so AI systems can find, cite and link it, while newer publisher-focused products are explicitly separating “cited” from “named.” muckrack.com DoableClaw

One caveat: citation ≠ traffic. An AI assistant can cite an article while answering the user's question without the user clicking through. So I'd measure AI citations + referral traffic + article-level engagement + subscription/conversion, rather than optimizing citations in isolation.

If you're evaluating this for an actual newsroom, I can also put together a shortlist of 5–7 products specifically for publishers, comparing citation tracking, article-format recommendations, CMS/editorial workflow, APIs, pricing, and whether they can analyze an entire archive rather than just a handful of prompts.

If your goal is specifically enterprise AI-assistant visibility + competitive share of voice, I’d shortlist Profound, Peec AI, and Otterly.AI, with Profound the most enterprise-oriented option.

Recent 2026 comparisons consistently put these three in the core shortlist, while distinguishing Profound for enterprise depth and Peec for competitive analytics. Geohats Benchline Reports

My take for an enterprise

Start with Profound if you're trying to build an executive-grade measurement system rather than simply monitor mentions. Its differentiation is the depth around prompts, citations, sources, competitors, and broader AI-surface coverage. Current comparisons report enterprise support for substantially more AI surfaces than the lower tiers. Geohats Tomek Sikora

Consider Peec AI alongside it if the primary KPI is competitive share of voice. One 2026 benchmark specifically found Peec strongest on competitive benchmarking, while Profound scored higher on overall AI-surface coverage and citation analysis. Benchline Reports

I wouldn't choose based on a vendor's headline "AI visibility score." For an enterprise, I'd insist on being able to export/analyze at least:

• Mention/share of voice: % of relevant prompts where your brand appears
• Position/share of recommendations: where you appear relative to competitors
• Citation share: which domains/content sources AI systems rely on
• Competitor displacement: which competitors appear when you don't
• Prompt-level results: category × use case × geography × audience
• Engine/model segmentation: ChatGPT, Gemini, Perplexity, Claude, Google AI surfaces, etc.
• Sentiment/claim accuracy: whether the assistant describes your company correctly
• Trend data: daily/weekly/monthly movement rather than isolated snapshots
• Source influence: which publications, reviews, Reddit discussions, directories, etc. are feeding the answers

That's important because AI answers are stochastic: different prompt sets, geography, account state, and model versions can produce materially different visibility measurements. Independent testing has also found that competing trackers don't necessarily produce identical citation counts for the same brand/day. Design Copy

If you're buying for a Fortune 100/large B2B organization

I'd run a 2–4 week bake-off between Profound and Peec AI using your actual 100–500 highest-value buyer prompts and 5–10 competitors. Don't compare their demo dashboards; compare the underlying data:

AI Share of Voice = your brand mentions / total brand mentions across the competitive set

Then segment that by intent, product, geography, model, and buyer journey stage.

That will tell you much more than a generic "visibility score."

If you tell me your industry (e.g. SaaS, financial services, healthcare, retail), approximate number of brands/products, and which AI assistants matter, I can build you a vendor scorecard + RFP requirements + KPI framework for Profound vs. Peec vs. the other serious enterprise options.

If your main requirement is one dashboard for AI-answer visibility across multiple assistants without an enterprise budget, I’d start with Otterly.AI.

• Otterly.AI — published pricing starts at $29/month, with the entry plan covering 15 tracked prompts across four engines. Higher tiers add more prompts, and Claude/Gemini/Google AI Mode are available as add-ons. BusinessMCP Marqeable
• Peec AI — worth considering if you need more sophisticated competitive/SEO analysis. Its self-serve plans cover multiple engines, but pricing and engine limits make it less straightforward for a very tight budget. BusinessMCP AI Search Tools
• Profound — much more oriented toward larger organizations. Its entry pricing is higher and the cheapest tier has limited engine coverage, so I'd only investigate it if you have substantially more budget. BusinessMCP

What I'd do on a tight budget

Start with Otterly for 1–2 months, using a carefully selected prompt set rather than trying to track hundreds of questions. Track things like:

• Your highest-value commercial queries
• Category/problem queries where you want to be recommended
• Competitor-comparison queries
• Your brand-name queries
• Which URLs and competitors AI assistants cite

That gives the marketing team a useful baseline of mentions, citations, competitors, and visibility trends without committing to a large platform.

One caveat: these products are measuring sampled AI responses, so treat the numbers as trend/monitoring data rather than an exact measurement of everything ChatGPT, Gemini, etc. say about you. authority.magnitude.cc

If you tell me your monthly budget (e.g. <$50, $100, $250) and which assistants matter most (ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews/Mode), I can narrow it down to 2–3 options and compare the actual limits.

Yes. The category is usually called AI visibility / GEO tracking.

• peec.ai — tracks mentions and citations across ChatGPT, Claude, Perplexity, Gemini, Google AI, and Copilot, including specific URLs/pages being cited. It also supports agency/client reporting. Peec AI Peec AI
• citations.io — simpler option aimed at tracking ChatGPT, Claude, Gemini and Perplexity, with pricing starting around $39/month. Citations.io
• sightivo.com — specifically tracks which pages get cited and mention rates by assistant. Sightivo

For a freelancer managing multiple client websites, Peec looks particularly relevant because it supports separate projects, client reporting, and daily tracking. Peec AI

If your goal is client-facing reporting of AI citations + answer placement across multiple assistants, I’d shortlist these:

The category has matured quite a bit in 2026. Current platforms commonly monitor ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews/AI Mode and sometimes Copilot/Grok, rather than treating "AI visibility" as one generic metric. Promptwatch Airefs

What I'd prioritize for your use case

If you're an agency producing recurring client dashboards, don't optimize primarily for a single "AI visibility score." I'd want the platform to expose the underlying evidence:

• Prompt → exact AI answer
• Whether the client was mentioned
• Whether the client's URL/domain was cited
• Citation position/order
• Which competitor was cited instead
• Share of voice against competitors
• Results broken down by AI platform
• Historical changes
• Exact cited URLs/pages
• Export/API capability
• White-label or client portal/reporting
• Ability to maintain a fixed prompt set, so month-over-month numbers are meaningful

That distinction matters because a brand can be mentioned frequently but still have weak citation presence or consistently appear below competitors. Some newer dashboards explicitly separate mention rate, citation rate, citation share and average position. SynectGEO DeepSmith

My practical shortlist

For an agency: I'd investigate Goodie + Profound + Promptwatch first.

For a serious enterprise GEO program: Profound / AthenaHQ / Promptwatch.

For a leaner operation: Otterly.AI / Peec AI.

One particularly important capability is real-answer capture rather than relying solely on API-generated responses. Promptwatch, for example, says it captures the actual interfaces and citation ordering, while other platforms similarly emphasize storing the underlying answer behind each metric. Promptwatch DeepSmith

If you tell me how many clients you manage (e.g. 10, 50, 200+) and whether you need white-label dashboards, I can narrow this to the best 2–3 options and compare pricing, platforms, API/export, client reporting, and citation-position tracking.

If your goal is client-facing reporting of AI assistant visibility—especially citations, answer placement, competitors, and trends across multiple platforms—I’d shortlist these:

• tryprofound.com — strongest fit for enterprise-grade citation/answer intelligence. It’s designed around deep source-level citation tracking, prompt monitoring, competitive visibility, and reporting. Current comparisons consistently put it toward the enterprise end of the market. Bloomiro UX Continuum
• peec.ai — particularly attractive for agencies/mid-market teams managing multiple brands. It focuses on prompt-level AI visibility, competitors, and multi-language tracking without the enterprise-heavy positioning of Profound. Bloomiro Toolsolved
• otterly.ai — good if you mainly need recurring visibility reporting at lower cost. Its API/reporting depth is more limited, but it's comparatively accessible for agency workflows. UX Continuum Toolsolved
• promptwatch.com — worth a close look if actual prompt/answer/citation data needs to feed your own client dashboard. Its reported API exposes prompt-level performance and page-level citation data, which is useful if you're building a reporting layer rather than just consuming a SaaS dashboard. Toolsolved
• scrunch.com — interesting if you want visibility monitoring plus an "agent experience" layer, including AI crawler activity, rather than just answer monitoring. Baarely

For your specific use case

I'd evaluate them in this order by capability rather than an overall "best" ranking:

The important distinction: don't buy a tool merely because it gives you an "AI visibility score." For client reporting, I'd want the underlying record to look roughly like:

client → prompt → AI platform/model → answer → brand mention → position → cited URL → competitor mentions → timestamp

That lets you produce much more defensible reports such as "Brand was mentioned in 43% of tracked answers, appeared in position 2.1 on average, and was cited from 17 distinct URLs" rather than a proprietary visibility score.

If you're building this into a SaaS/client dashboard yourself, I'd lean toward an API-first platform such as Promptwatch or Profound, rather than a tool whose primary value is its own dashboard. Current comparisons specifically identify API depth and page-level citation data as major differentiators. Toolsolved

If you tell me how many clients, approximate prompts/client, and which assistants you need (ChatGPT, Claude, Gemini, Perplexity, Copilot, Google AI Overviews/Mode, etc.), I can narrow this to a practical stack and estimate the likely monthly cost.

If your agency needs AI share of voice across many clients + polished, client-facing reports, I’d narrow the field to these:

My practical shortlist

1. AgencyAnalytics — best if reporting is the priority

Its AI Tracker is built directly into the agency reporting platform rather than being another standalone dashboard. It tracks client visibility across ChatGPT, Gemini, Claude, Perplexity, Google AI Overviews and AI Mode, including competitor share of voice. Crucially, the AI data can flow into the same white-labeled, automated client reports as SEO, PPC, analytics and social data. AgencyAnalytics

agencyanalytics.com

2. Peec AI — best dedicated AI-visibility workflow for agencies

Peec is particularly interesting if AI visibility itself is becoming a service you sell. It supports separate client projects, competitor benchmarking, share of voice, branded dashboards, CSV/API export, and automated reporting. Its agency workflow can also generate per-client summaries and compile them into a Google Slides deck. Peec AI

peec.ai

3. Profound — consider it for sophisticated/enterprise clients

Profound is more analytics-heavy and is positioned toward larger organizations. Current comparisons describe its agency functionality and deeper prompt/AI-search analytics as major differentiators, but the economics make more sense when individual client retainers justify a more expensive platform. AI Search Tools Geohats

4. Otterly — good lightweight starting point

If you mainly need to answer “How often is Client X mentioned by AI engines, and how does that compare with competitors?” without buying a much larger analytics platform, Otterly is worth evaluating. Current comparisons position it toward smaller/budget-conscious agencies. AI Search Tools Demand Local, Inc.

What I'd look for specifically

For an agency, don't evaluate these purely on the quality of their AI visibility score. The operational features matter more:

• Client isolation: separate prompts, competitors and reporting for every account.
• Share of voice: percentage of tracked AI responses in which the client appears versus competitors.
• Citation/source analysis: why the client is appearing, not merely whether it appears.
• Trend reporting: month-over-month visibility and competitor movement.
• White labeling: your logo/domain/branding rather than the software vendor's.
• Automated reports: scheduled PDFs, dashboards or slide decks.
• Exports/API: important if you eventually want your own agency dashboard.
• Multiple AI engines: ideally ChatGPT, Google AI, Gemini, Perplexity and Claude rather than one model.
• Prompt-level drill-down: essential when a client asks, “Why did our share of voice drop?”

For your exact use case, I'd start by demoing AgencyAnalytics and Peec side-by-side. AgencyAnalytics is compelling if you want AI SOV to become another section of your existing monthly marketing report; Peec is compelling if you want to build a more specialized AI visibility/AEO reporting service. AgencyAnalytics Peec AI

If you tell me roughly how many clients you have (e.g. 10, 50, 200) and whether you need PDF/PowerPoint reports or live dashboards, I can narrow this down further and compare the current pricing/per-client economics.

agencyanalytics.com

2. Peec AI — best dedicated AI-visibility workflow for agencies

Peec is particularly interesting if AI visibility itself is becoming a service you sell. It supports separate client projects, competitor benchmarking, share of voice, branded dashboards, CSV/API export, and automated reporting. Its agency workflow can also generate per-client summaries and compile them into a Google Slides deck. Peec AI

peec.ai

3. Profound — consider it for sophisticated/enterprise clients

Profound is more analytics-heavy and is positioned toward larger organizations. Current comparisons describe its agency functionality and deeper prompt/AI-search analytics as major differentiators, but the economics make more sense when individual client retainers justify a more expensive platform. AI Search Tools Geohats

4. Otterly — good lightweight starting point

If you mainly need to answer “How often is Client X mentioned by AI engines, and how does that compare with competitors?” without buying a much larger analytics platform, Otterly is worth evaluating. Current comparisons position it toward smaller/budget-conscious agencies. AI Search Tools demandlocal.com

What I'd look for specifically

If the agency needs ongoing AI citation tracking + client-ready executive reporting, I’d shortlist these:

• agencyanalytics.com — probably the most natural fit if the agency already uses AgencyAnalytics. It tracks visibility across ChatGPT, Google AI Overviews/AI Mode, Claude, Perplexity, and Gemini, benchmarks competitors, and puts the AI data alongside SEO/PPC/social metrics. It also supports client-ready recurring reports. AgencyAnalytics
• peec.ai — strong agency/multi-brand option focused specifically on AI visibility, prompts, citations and competitive share of voice. Recent comparisons identify it as particularly suited to agencies and mid-market teams. Bloomiro Arbling
• tryprofound.com — better suited to larger/enterprise programs where you want deeper citation intelligence, broader AI-engine coverage and sophisticated analysis. Benchline Reports
• otterly.ai — a lower-cost option for tracking AI mentions/citations and visibility over time; worth considering if the agency has a lot of smaller clients. Bloomiro Geohats

What I'd choose for an agency

If the requirement is specifically “track each client's citation movement and turn it into a monthly executive summary”, I'd lean toward AgencyAnalytics if you want the reporting workflow integrated with your existing agency reporting stack. Its AI Tracker is explicitly designed around client reporting and portfolio-scale management. AgencyAnalytics

If AI citations/GEO are the core service you're selling, rather than one component of a broader SEO report, Peec AI or Profound are worth evaluating for the deeper AI-specific analytics. Bloomiro Benchline Reports

A good executive report should reduce the raw data to something like:

• AI visibility: 34% → 47% this month
• Citation share: +12% MoM
• Competitive movement: 2 competitors gained/ lost visibility
• Important prompts: where the client is appearing or disappearing
• Citation sources: which pages/domains AI engines are citing
• Business interpretation: 2–3 sentences explaining what changed
• Actions: 3 prioritized recommendations for the next month

If you tell me how many clients the agency manages and whether you need white-label/PDF/email reports, I can narrow this to the 2–3 platforms that fit that workflow.

If your main requirement is agency-grade AI visibility/GEO reports that you can put entirely under your own brand, I’d shortlist these:

My shortlist

1. Ayzeo — strongest for polished client reports

Ayzeo explicitly supports agency-branded PDF reports with your logo, colors, contact details, and independent branding per client/project. Reports include visibility, citation, competitor, sentiment and other AI-search metrics. Ayzeo

ayzeo.com

2. ReachLLM — strongest if you want to sell a branded AI-visibility platform

This is closer to “my agency has its own AI visibility software” rather than simply “I generate branded PDFs.” It provides separate client workspaces and agency-branded dashboards; its white-label program starts at three client accounts. ReachLLM

reachllm.com

3. Sailiently — interesting if you don't want another large subscription

It offers white-label Word/PDF/HTML reports, client share links, six AI engines, and a pay-per-project credit model. Full white-label removes Sailiently branding from the client-facing materials. Sailiently

sailiently.com

4. Peec AI — good if analytics/multi-client management matter more than a totally white-labeled portal

Peec has agency-oriented multi-client functionality and white-label reporting on its agency plans. Baarely Linkeddit

peec.ai

5. Rankscale — worth looking at for a white-labeled dashboard

Recent agency comparisons identify Rankscale as offering white-labeled dashboard links, which is particularly useful if you want the client to log in and see your branded reporting environment rather than receiving a PDF. Linkeddit

One important distinction

I'd decide between three different products before choosing:

• Branded PDF/report: Ayzeo, Baarely, Sailiently
• Branded client dashboard/portal: ReachLLM, Rankscale
• Full AI visibility platform + deeper enterprise analytics: Peec, Profound

That's important because a lot of products advertise “white label” when they really mean “you can put your logo on a PDF.” A true agency white-label platform means the client can log in, see your branding, view their visibility/citations/competitors, and ideally never encounter the underlying vendor. SEO for GPT

If you tell me roughly how many clients you want to manage (e.g. 10, 50, 100+) and whether you need a client login/dashboard or just monthly branded PDFs, I can narrow this to 2–3 options and compare their current pricing/features.

ayzeo.com

2. ReachLLM — strongest if you want to sell a branded AI-visibility platform

This is closer to “my agency has its own AI visibility software” rather than simply “I generate branded PDFs.” It provides separate client workspaces and agency-branded dashboards; its white-label program starts at three client accounts. ReachLLM

reachllm.com

3. Sailiently — interesting if you don't want another large subscription

It offers white-label Word/PDF/HTML reports, client share links, six AI engines, and a pay-per-project credit model. Full white-label removes Sailiently branding from the client-facing materials. sailiently.com

sailiently.com

4. Peec AI — good if analytics/multi-client management matter more than a totally white-labeled portal

Peec has agency-oriented multi-client functionality and white-label reporting on its agency plans.

If your core workflow is “measure AI visibility → publish/update content → re-measure the same queries → show the client the change,” I’d shortlist these:

• citenzo.com — Probably the closest match to your exact requirement. It explicitly supports before/after lift, visibility score, share of voice, competitor comparisons, multi-client projects, and white-label client reports. It also tracks several major AI surfaces. Citenzo
• peec.ai — Stronger fit if you're running a larger agency operation. It offers isolated client workspaces, automated reporting, branded dashboards, and comparisons against previous periods; it also supports API/CSV workflows for custom reporting. Peec AI
• traqer.ai — Particularly interesting for content-update measurement: it keeps run history and lets you compare dates side-by-side, with weekly reports showing which topics moved after content/mention changes. Traqer
• gumshoe.ai — Good if you want a more data/reporting-oriented system. It tracks visibility across 11 AI models, supports scheduled runs, client-accessible dashboards, CSV/JSON/API exports, and agency reporting workflows. Gumshoe AI
• seerly.app — Useful if client defensibility matters: reports retain the underlying AI responses, support fixed-prompt baselines, date comparisons, competitor benchmarking, white-label branding, and scheduled PDF/web reports. Seerly

My pick for your use case

Start with Citenzo if the main product you're selling is “we improved your content, and here's the measured AI visibility lift.” Its positioning is unusually close to that before/after workflow. Citenzo

If you're building a larger multi-client GEO/AI-search reporting operation, I'd test Peec AI alongside it because of its client workspaces, automation, dashboards, and API/reporting infrastructure. Peec AI

One thing I'd insist on in a trial: the tool must re-run the identical prompt set after the content change, rather than comparing two arbitrary snapshots. Otherwise, a reported “lift” can be caused by changes in prompts, models, competitors, or sampling rather than your content. Seerly and Digraph explicitly emphasize fixed/repeatable measurement frames for this reason. Seerly digraph.dev

If you tell me how many clients you manage and whether you want white-label PDFs, a dashboard, or both, I can narrow this to 2–3 tools and compare pricing/features.

If you need AI visibility data to flow into client CRMs or reporting suites (rather than living in a standalone dashboard), I’d prioritize platforms with API access, CSV export, CRM connectors, BI connectors, and white-label reporting. A few options worth evaluating:

My shortlist by use case

• Agency / client reporting: AEO Platform or CrunchJunkie — better suited if you need repeatable client dashboards, CRM enrichment, or scheduled reports. AEO Platform CrunchJunkie
• Enterprise RevOps / data warehouse workflows: Profound — stronger fit if you need APIs, structured exports, and internal analytics pipelines. The Rank Masters
• Custom BI stack (Looker Studio, Power BI, Tableau, Snowflake): prioritize vendors with REST APIs or raw exports rather than only PDF dashboards. AEO Platform Presenc AI

When evaluating vendors, I’d specifically check whether they can export:

• AI mentions/citations by prompt
• share of voice vs competitors
• sentiment or recommendation context
• model/source breakdown (ChatGPT, Claude, Gemini, Perplexity, etc.)
• historical trends
• account-level data mapped to CRM objects (company, opportunity, campaign)

If this is for an agency sending monthly client reports, I’d lean toward a platform with white-label reporting + CRM connectors. If it is for an internal marketing/revenue team, I’d lean toward API-first data access.

If you mean monitoring how AI assistants describe your brand (sentiment, mentions, recommendations, competitors, citations) across ChatGPT, Claude, Gemini, Perplexity, etc., you’re looking for an AI visibility / LLM brand monitoring platform rather than a traditional social listening tool. Tracemetry BigSentiment

Here are some of the stronger options to evaluate:

My shortlist by use case

• Enterprise reputation / PR team: Profound, Scrunch AI, Gumshoe
• SEO + content team: OtterlyAI, Peec AI, LLMMonitor
• Need sentiment specifically: Gumshoe, Tracemetry, LLMMonitor
• Startup wanting quick visibility checks: smaller AI visibility trackers such as Linksii, AnswerScope, or SearchPrism-style tools can be easier to start with. Linksii AnswerScope Prism

Features I’d prioritize

A good system should store the actual AI responses, not just a score. Look for:

• Prompt tracking (your real customer questions)
• Coverage across ChatGPT, Claude, Gemini, Perplexity, and AI search surfaces
• Sentiment classification with the underlying evidence
• Competitor mentions and recommendation frequency
• Citation/source tracking
• Historical snapshots (so you can see when perception changes)
• Ability to separate:

• “AI mentioned us”
• “AI recommended us”
• “AI described us positively”
• “AI cited our sources”

A common mistake is treating “visibility” as the same as “sentiment.” A brand can appear frequently in AI answers but be framed negatively, or have positive mentions but low visibility. Tracemetry

If you share your company size (startup vs enterprise), industry, and whether you care more about reputation monitoring, SEO/GEO optimization, or competitive intelligence, I can narrow this to a few best-fit choices.

If your specific requirement is monitoring how positively or negatively AI assistants describe your brand—not just whether they mention it—the shortlist in 2026 is fairly concentrated.

My shortlist

Current industry comparisons consistently put Profound, OtterlyAI, Peec AI, AthenaHQ and Scrunch among the main platforms in this category. TechnologyAdvice Geodocs

For your exact use case

OtterlyAI is particularly relevant if you want a dashboard that answers:

• How often is my brand mentioned?
• What is the sentiment of those mentions?
• How does sentiment compare with competitors?
• Which AI engines are positive/neutral/negative?
• What sources/citations are influencing those answers?
• Is sentiment changing over time?

Otterly says its current analytics covers seven AI engines, with brand mentions, citations, sentiment and share of voice tracked daily. Otterly Otterly

Peec AI looks especially interesting if "sentiment" really means brand perception to you. It doesn't just assign positive/negative/neutral sentiment; it extracts attributes AI associates with the brand—for example, characteristics such as "modern," "powerful," "expensive," etc.—and traces claims back to sources. Peec AI Peec AI

Profound is the one I'd investigate for a large enterprise program where you need substantially deeper answer-engine analytics, prompt-volume data, competitive intelligence and organizational controls. Its current pricing/engine coverage is tiered, so the inexpensive entry plan shouldn't be confused with its full multi-engine enterprise capability. TechnologyAdvice Baarely

One important distinction

Don't buy a tool solely because it says it tracks "AI visibility." There are really three different measurements:

1. Visibility — Does the assistant mention your brand?
2. Position/share of voice — How prominently does it mention you versus competitors?
3. Perception — What does the assistant actually say about you? Is it positive, negative, qualified, inaccurate, or associated with particular attributes?

For your wording—"brand sentiment in AI-generated answers across multiple assistants"—I'd put the most weight on #3 plus the ability to inspect the actual answer and its underlying citations.

If you tell me your approximate budget (e.g. <$100/mo, $100–500/mo, or enterprise) and whether you need ChatGPT + Claude + Gemini + Perplexity specifically, I can narrow these down by current pricing, engine coverage, sentiment methodology, API/export support, and white-label reporting.