Positive mentions of Peec AI

Yes. For a mid-market SaaS team, I’d shortlist these rather than buying a broad SEO platform blindly:

My picks

1. Peec AI — probably the best match for you.
It explicitly measures visibility, position, sentiment and share of voice against competitors, with comparisons by AI engine. It also surfaces the sources most frequently cited for your tracked prompts and lets you follow those metrics over time. Peec AI AI Search Tools

2. OtterlyAI — best if you want a clean, operational dashboard.
Its AI Search Analytics tracks mentions, citations, sentiment and SOV across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. It also has competitor benchmarking, prompt-level gaps and URL-level citation tracking. Otterly

3. Profound — best if AI visibility is becoming a serious marketing program.
It's the one I'd investigate if you expect multiple markets, lots of prompts, deeper citation analysis and executive reporting. Current third-party comparisons generally put Profound at the high end for coverage and citation analysis. Benchline Reports Bloomiro

4. Scrunch AI — worth evaluating.
It has competitor heatmaps, SOV, source/citation analysis and model-level reporting. It appears particularly reasonable if you want a polished monitoring/reporting layer without going all the way upmarket. AI Search Tools

What I'd actually measure

For SaaS, I wouldn't make the primary KPI simply "AI mentions." I'd build the dashboard around:

• Competitive share of voice — your % of AI answers vs. each competitor
• Citation share — how frequently your domain/content is actually cited
• Citation share by source — e.g. G2, Gartner, Reddit, review sites, comparison pages, publishers
• Average answer position — #1 recommendation vs. #5 mention
• Prompt coverage — % of important buyer prompts where you appear
• Competitor gap — prompts where competitors appear and you don't
• SOV trend — week-over-week/month-over-month movement
• Engine breakdown — ChatGPT vs. Gemini vs. Perplexity vs. Google AI
• Untracked competitor discovery — companies appearing repeatedly that weren't on your original competitor list

That distinction between being mentioned and being cited is especially important. A brand can have strong AI visibility while rarely getting a citation, which makes the two metrics behave very differently. Austin Heaton

My recommendation

For your specific use case, I'd run a bake-off of Peec AI vs. OtterlyAI vs. Profound using the same 50–100 real buyer prompts.

If you care primarily about "Are we beating competitors in AI answers, and is that changing?" → Peec AI.

If you care about "Give marketing a simple daily/weekly AI visibility dashboard with citation details." → OtterlyAI.

If you want "Build an enterprise-grade AI search intelligence program." → Profound.

A 2026 benchmark also found these three among the category leaders, with Otterly and Profound particularly prominent in AI-generated recommendations and Peec showing strong competitive visibility capabilities. foglift.io Benchline Reports

If you tell me roughly your ARR/team size, number of competitors, and whether you're already using Semrush/Ahrefs, I can narrow this to a 2-tool shortlist and give you the exact evaluation scorecard.

Yes. If your requirement is specifically historical, enterprise-grade measurement of how a brand is represented across multiple AI models, I’d shortlist these platforms rather than treating this as ordinary SEO monitoring.

My recommendation

1. tryprofound.com — best enterprise choice

This would be my first vendor to evaluate.

Profound is built around enterprise AI-search analytics and tracks things such as:

• Brand visibility and share of voice
• Position/ranking within AI answers
• Sentiment and brand positioning
• Citations and the sources influencing AI answers
• Performance by model, region and topic
• Historical performance from recurring prompt measurements
• Competitive benchmarking

Its Answer Engine Insights product explicitly builds a dataset by repeatedly querying AI answer engines and analyzing the resulting responses. Profound Help Center

A particularly interesting enterprise feature is the Profound Index, which uses more than 1.5 billion real user conversations, across 50+ industries and major LLMs, to benchmark brands against their category. That's materially different from simply running a synthetic prompt list. Profound

Why I'd favor it: if you're building an executive-level "AI Share of Voice" capability, Profound looks closest to an enterprise intelligence platform rather than merely an SEO/AEO tracker.

2. scrunch.com — strongest alternative for longitudinal analytics

Scrunch is particularly compelling if historical analysis and flexible BI-style exploration are important.

Its Explorer environment lets teams construct custom metrics and analyze them across time, including citation performance, sentiment versus competitors, and other dimensions. Scrunch Help Center

It tracks things such as:

• Brand presence
• Competitive presence
• Share of voice
• Position
• Sentiment
• Citations
• AI referrals/traffic
• Trends

ScrunchOne caveat for your use case: Scrunch says its standard historical data goes back up to 12 months or to when your environment was created, whichever is shorter. Its API retains 90 days. Scrunch

So I'd specifically ask them about historical backfill and data retention during procurement.

3. peec.ai — strong analytics-oriented option

Peec is worth putting into the RFP if you want a comparatively straightforward analytics product.

It tracks:

• Visibility
• Position
• Sentiment
• Share of voice
• Competitors
• Citations/source usage
• Model-specific performance
• Geographic segmentation
• Prompt/persona/funnel segmentation

Peec says prompts are executed daily on selected AI models, giving you trend data across models, dates and regions. It also offers a REST API, Looker Studio integration and MCP connectivity for feeding data into other systems. Peec AI

I'd put it behind Profound for a very large enterprise, but ahead of many lightweight "AI visibility" tools if analytics/API access is important.

4. otterly.ai — good monitoring, less compelling for your requirement

Otterly covers a broad set of engines—including ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude—and measures mentions, citations, sentiment and share of voice. Otterly

It's a good product, but for the phrase "our enterprise needs historical analytics", I'd generally start with Profound and Scrunch before Otterly.

How I'd structure the enterprise evaluation

Don't just ask vendors "Which LLMs do you track?" That's increasingly an insufficient evaluation criterion.

I'd require them to demonstrate this exact workflow:

One especially important distinction

I'd separate your data into three layers:

1. Brand representation

"When someone asks an AI about our category, what does it say about us?"

2. Source influence

"Which websites, publications and pages are causing the AI to say that?"

3. Business outcome

"Does AI visibility actually translate into referral traffic, consideration, leads and revenue?"

The first two are where Profound/Scrunch/Peec are useful. The third generally requires connecting the AI-visibility dataset to your existing analytics, CRM and revenue data.

And I'd insist on preserving the actual model responses, not merely a proprietary "visibility score." Your historical corpus could become strategically valuable as models, answer formats and AI-search behavior change.

Bottom line: I'd run a serious enterprise bake-off between Profound and Scrunch, with Peec as the third bidder. If you tell me your approximate company size, number of brands/markets, desired lookback period, and whether you need raw API/data-warehouse access, I can turn this into a detailed enterprise RFP scorecard and rank the vendors against it.

Yes. If the requirement is specifically “show me the AI answer, then trace each citation back to the exact canonical page/URL that earned it,” I’d shortlist these:

My recommendation

Start with Ahrefs + Profound as your evaluation pair.

Ahrefs is particularly interesting for your use case because its current Brand Radar data explicitly exposes “Cited Pages”—the specific URLs AI systems cite—and separately tracks pages that were found/retrieved but not actually cited. That distinction is valuable if you're trying to understand why a canonical page wins the source slot. Ahrefs Help Center Ahrefs Help Center Ahrefs

It also covers a broad set of AI surfaces—ChatGPT, Perplexity, Gemini, Copilot, Google AI Overviews and AI Mode—and can connect AI visibility back to search demand. Ahrefs

Profound is the one I'd put through an enterprise workflow test alongside it. Independent 2026 comparisons consistently put Profound among the strongest dedicated AI-search platforms, particularly where deeper enterprise monitoring is important. Austin Heaton Benchline Reports

What I'd test in the demos

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

Prompt → AI answer → citation → exact URL → canonical URL → page/domain → timestamp/model

And specifically test whether they can distinguish:

• example.com/page-a vs. its canonical example.com/page-b
• redirects vs. final destination
• syndicated copies vs. the original
• cited URLs vs. URLs merely retrieved by the model
• multiple citations from the same domain
• citations that disappear/change between runs
• AI-generated answer text alongside the underlying source URL
• historical changes to which URL earned the citation

That last distinction matters. Ahrefs, for example, explicitly separates “Citation” from “Found in”: a page can be retrieved during answer generation without being shown as a citation to the user. Ahrefs Help Center

If canonical-URL attribution is the core evaluation criterion, I'd weight that more heavily than “AI visibility score.” A visibility percentage tells you whether you're appearing; the source-level URL trail tells your SEO/content team which page is actually earning the appearance and what to change. Ahrefs

It also covers a broad set of AI surfaces—ChatGPT, Perplexity, Gemini, Copilot, Google AI Overviews and AI Mode—and can connect AI visibility back to search demand. ahrefs.com

Profound is the one I'd put through an enterprise workflow test alongside it. Independent 2026 comparisons consistently put Profound among the strongest dedicated AI-search platforms, particularly where deeper enterprise monitoring is important.

What I'd test in the demos

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

Prompt → AI answer → citation → exact URL → canonical URL → page/domain → timestamp/model

If the goal is AI citation monitoring that feeds into your existing analytics/data stack, I’d prioritize platforms with a real API or native BI/warehouse integrations rather than tools that only offer dashboards.

My shortlist

OtterlyAI would be my first one to evaluate if "integrates into our analytics stack" is the primary requirement. Its API exposes brand visibility, prompt-level results, citations, recommendations and GEO audits, and its current documentation specifically mentions feeding data into Looker Studio, Tableau, Power BI, BigQuery and Snowflake, as well as triggering workflows through Zapier/Make/Slack. Otterly AI Otterly

help.otterly.ai

Profound is the one I'd look at if you're building a serious enterprise measurement layer. It goes deeper into citation-level intelligence and prompt-volume/demand data, with broad coverage across AI engines. The tradeoff is that meaningful API/integration access tends to be enterprise-oriented. LLM Visibility Tools Geodocs

Semrush makes the most sense if your analytics stack already revolves around Semrush. Its AI Visibility Toolkit tracks citations across ChatGPT, Perplexity, Gemini and Google's AI experiences, while its existing API/SEO ecosystem can reduce the number of separate systems you have to wire together. Citation Hawk Otterly

Conductor is worth considering for a larger enterprise marketing organization. It combines AI visibility with the broader SEO/content workflow, and current comparisons list both API and MCP connectivity. Otterly

What I'd actually build

Rather than making the AI-visibility vendor your analytics system of record, I'd structure it like:

AI citation platform → API → warehouse → your BI/analytics layer

For example:

OtterlyAI → API → Snowflake/BigQuery → Looker/Tableau/Power BI

Then store dimensions such as:

• AI engine/model
• prompt
• brand mentioned/not mentioned
• cited/not cited
• cited URL
• citation position
• competitor mentions
• sentiment/recommendation
• geography
• timestamp
• prompt category/persona

That lets you correlate AI visibility → website traffic → conversions/revenue, rather than treating an AI visibility score as the KPI.

One particularly important distinction: mention monitoring isn't the same as citation monitoring. If your objective is "which pages/domains are AI systems actually citing?", make sure the vendor exposes the underlying source URL/domain and prompt-level response data, not just a proprietary visibility score. Current comparisons specifically highlight this as an important differentiator. Toolsolved Otterly

If you tell me what your existing stack is (e.g. GA4 + BigQuery + Looker, Snowflake + Tableau, Segment + Amplitude, etc.), I can narrow this to the 2–3 best integrations and show exactly how I'd wire the data in.

Semrush makes the most sense if your analytics stack already revolves around Semrush. Its AI Visibility Toolkit tracks citations across ChatGPT, Perplexity, Gemini and Google's AI experiences, while its existing API/SEO ecosystem can reduce the number of separate systems you have to wire together. Citation Hawk Otterly

Conductor is worth considering for a larger enterprise marketing organization. It combines AI visibility with the broader SEO/content workflow, and current comparisons list both API and MCP connectivity. Otterly

What I'd actually build

Rather than making the AI-visibility vendor your analytics system of record, I'd structure it like:

AI citation platform → API → warehouse → your BI/analytics layer

For example:

OtterlyAI → API → Snowflake/BigQuery → Looker/Tableau/Power BI

Then store dimensions such as:

• AI engine/model
• prompt
• brand mentioned/not mentioned
• cited/not cited
• cited URL
• citation position
• competitor mentions
• sentiment/recommendation
• geography
• timestamp
• prompt category/persona

That lets you correlate AI visibility → website traffic → conversions/revenue, rather than treating an AI visibility score as the KPI.

One particularly important distinction: mention monitoring isn't the same as citation monitoring. If your objective is "which pages/domains are AI systems actually citing?", make sure the vendor exposes the underlying source URL/domain and prompt-level response data, not just a proprietary visibility score. Current comparisons specifically highlight this as an important differentiator.

Yes. The category you’re looking for is usually called AI Search Visibility / GEO (Generative Engine Optimization) monitoring. These platforms run relevant prompts through AI search engines and tell you whether your site is mentioned, which URLs are cited, which competitors are cited instead, and what you can do to improve. Otterly Otterly

My shortlist

• otterly.ai — probably the best fit if your main question is “Where is our website being cited by AI?” It tracks citations and mentions across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot, and provides competitor/share-of-voice analysis and optimization insights. Otterly Otterly
• getprofound.com — stronger enterprise option. It goes deeper into AI-search analytics, competitive intelligence and citation/source analysis. SEO Counselors
• peec.ai — good middle ground if you want monitoring plus recommendations for improving AI visibility, rather than just reporting. Conbersa
• ahrefs.com — worth considering if you're already using Ahrefs for conventional SEO; its AI visibility capabilities can connect AI citations with your existing SEO/competitive data. OpenAIToolsHub
• athenahq.ai — another enterprise-oriented option, particularly around competitive AI visibility. Meridian15

What I'd choose

If your goal is specifically:

“Crawl/monitor AI assistants → show me where our domain is cited → compare us with competitors → tell me what content we should change.”

I'd start with OtterlyAI and Profound.

One important distinction: these aren't literally crawling every ChatGPT/Claude conversation. They run controlled sets of prompts against AI search experiences and analyze the resulting answers and cited URLs. That's important because AI answers are personalized and can change substantially between runs. Otterly

Also, citation count alone isn't the ideal KPI. Recent research suggests that a page's influence on the generated answer can matter more than simply being listed as a citation. arxiv.org

If you tell me your website/domain and industry, I can also give you a concrete recommendation between Otterly vs Profound vs Peec, including what I'd track (prompts, competitors, citations, Reddit/third-party mentions, etc.) and how I'd build the GEO program.

Yes — but there’s an important distinction.

There are now tools that show the exact prompts you’re tracking and the AI answers/citations they produce. But no tool can reliably tell you the exact private prompts that real users typed into ChatGPT/Gemini/etc. That information generally isn’t exposed by the AI platforms.

For a solo SEO freelancer, I’d think about it as “prompt discovery + AI visibility tracking.”

What you can actually measure

A good tool can tell you:

• The prompt: e.g. “best CRM for small real estate teams”
• Which AI engine: ChatGPT, Gemini, Perplexity, Google AI Overviews, etc.
• The answer generated
• Whether your client/brand was mentioned
• Which URL/page was cited
• Which competitors were cited instead
• Sometimes the position/order of citations
• Changes in all of the above over time

For example, allsearch.io lets you generate/manage prompts and see prompt-level visibility, citations, competitors, and sources across multiple AI engines. AllSearch

ahrefs.com is particularly interesting for SEO freelancers because it derives prompts from real search behavior rather than simply inventing hypothetical questions. It checks ChatGPT, Gemini, Perplexity, Copilot and Google AI surfaces and reports the topics and pages being cited. Ahrefs

There are also dedicated trackers such as oneclickseo.ai and wellows.com that preserve the actual AI response and citation URLs for individual prompts. OneClickSEO Wellows

The really interesting opportunity for you

If what you're asking is:

“Can I find out which questions are causing AI to discover and cite my client's content?”

Yes, increasingly.

You can combine:

Google Search Console + keyword data → likely buyer questions → AI prompt tracking → cited URLs → content optimization

That's much more actionable than simply reporting an “AI visibility score.”

For example, suppose you're doing SEO for a commercial cleaning company.

You might discover that AI systems cite their article for:

• “How much does commercial cleaning cost?”
• “What should I look for in a commercial cleaning company?”
• “Best commercial cleaning companies for medical offices”
• “How often should an office be professionally cleaned?”

You can then see which specific page is getting cited for each prompt, and potentially build/modify content around the prompts where competitors are winning.

One caveat that's easy to miss

The phrase “exact prompts that lead to our content being used” can mean two different things:

1. Exact prompts you specify/test → yes, tools can track these precisely.
2. Exact prompts actual ChatGPT users typed before your content was cited → generally no. The platforms don't give SEOs a complete query log of users' private prompts.

Even vendors acknowledge this limitation: Otterly's GEO research describes AI search as having a “blind spot” because you can't directly see the exact prompts users are entering. Otterly

So I'd be skeptical of any product claiming it has a definitive database of all real ChatGPT prompts that caused your URL to be cited.

If you're a solo freelancer, I'd shortlist

For an SEO-first workflow: Ahrefs Brand Radar/AI Visibility — particularly compelling if you already use Ahrefs.

For inexpensive, granular prompt tracking: AllSearch or OneClickSEO.

For a dedicated AI visibility/AEO workflow: Otterly, Profound, Peec, etc. The market has gotten quite crowded in 2026. GeoHero Austin Heaton

But there's an even more interesting question: whether you can build a lightweight version of this yourself for clients — essentially “AI citations → prompt → page → recommendation” — without paying for one of the expensive enterprise AEO platforms.

For a solo freelancer, that could actually be a very good productized SEO service.

Yes. There’s now a fairly mature category for this: AI search / AI visibility monitoring (sometimes called AEO/GEO monitoring).

If by “alerts” you mean “tell me when an AI assistant starts citing a new URL from my domain, or a competitor’s domain”, that’s specifically available in some of these tools.

Tools worth looking at

• tryprofound.com — enterprise-oriented, with detailed citation/source-level monitoring and competitor analysis. Good if you want a serious intelligence program rather than just a visibility score. TechnologyAdvice SEO Counselors
• peec.ai — tracks AI visibility, citations and competitors across prompts and AI engines; positioned more toward marketing/SEO teams. TechnologyAdvice CiteLyzer
• otterly.ai — a lower-cost option for monitoring AI search results and competitor visibility. TechnologyAdvice MentionsAPI
• mentionscout.com — particularly interesting for your use case because it explicitly shows the source behind citations, competitor citations, and the prompts where competitors win. MentionScout
• genwolf.ai — tracks citations, competitors, source domains and full answer history on a recurring basis. Genwolf

One important distinction

Most products advertise “citation monitoring,” but that doesn't necessarily mean they send you an alert for:

“New URL detected: competitor.com/research/2026-report was cited by ChatGPT for prompt X.”

Many instead periodically rerun a fixed set of prompts and show you the changes in a dashboard.

So if new-page discovery is the actual requirement, I'd specifically evaluate whether the tool has:

1. URL-level citation history, not merely domain-level citation counts.
2. New citation detection — first appearance of a URL.
3. Competitor domain tracking.
4. Prompt → AI answer → cited URL linkage.
5. Alerts/webhooks/email/Slack when a new source appears.
6. Coverage of ChatGPT, Gemini, Perplexity, Google AI Overviews/AI Mode, Claude, etc.
7. Historical snapshots, so you can tell when an AI started citing a particular page.

There are tools getting quite close to exactly this. For example, Genwolf says it tracks “source domains” and full answer history, while MentionScout says it exposes the source behind every citation. Genwolf MentionScout

If you're asking because you're considering building this: yes, there's a meaningful gap between generic “AI visibility scores” and a true AI citation change-detection system. A product that effectively says “here are the new URLs AI systems started trusting this week, for you and your competitors” is a much more precise monitoring product.

If you tell me whether you're looking for a tool to buy or a product you're thinking of building, I can map out the best options/architecture.

If you mean “which tools show the actual passages, pages, or snippets that AI assistants pull into answers — and tell me how to make my content more likely to be used?”, you’re looking at the emerging AI Search Optimization / GEO (Generative Engine Optimization) / AEO tool category. GeoCopy

No tool can reliably show the private internal reasoning of ChatGPT, Gemini, Claude, etc., but several tools can show citations, retrieved sources, answer excerpts, brand mentions, and optimization opportunities. Nick Lafferty CitedSpy

Best tools for a content strategist

1. tryprofound.com — best enterprise AI visibility intelligence

What it shows:

• Which AI engines mention your brand
• Which URLs get cited
• Competitor visibility
• Query-level AI presence tracking

Best for: Content teams managing large brands and measuring AI share of voice. Nick Lafferty

Optimization workflow:

• Find prompts where competitors appear but you don’t
• Inspect the cited pages
• Create content that answers the same user intent with clearer definitions, comparisons, evidence, and structured sections

2. peec.ai — best for AI visibility monitoring

What it shows:

• Brand mentions across AI engines
• Competitor comparisons
• Prompt tracking

Best for: Marketing teams that want a simpler dashboard than enterprise platforms. Nick Lafferty

3. scrunch.ai — best for technical GEO audits

What it focuses on:

• How AI crawlers interpret your site
• Content discoverability issues
• AI search readiness

Best for: Teams with SEO + content + technical resources. TechRadar

4. citedspy.com — best for seeing actual cited sources side-by-side

What it shows:

• The answers different AI engines produce
• The URLs they cite
• Comparative citation patterns across engines

Best for: A strategist who wants to answer: “When someone asks AI this exact question, what sources does it trust?” CitedSpy

5. chromewebstore.google.com — lightweight research tool

What it does:

• Captures cited sources from AI answers
• Helps compare what ChatGPT, Gemini, and Perplexity reference

Best for: Individual strategists doing competitive research. Chrome Web Store

The optimization tactics these tools usually reveal

Once you find the snippets AI systems are using, optimize your pages to become easier to quote:

1. Write “extractable” answers

AI systems tend to favor passages that are:

• Direct
• Self-contained
• Fact-rich
• Clearly structured

Example:

Weak:

“Our platform helps companies improve productivity.”

Stronger:

“Project management software reduces coordination overhead by centralizing tasks, deadlines, ownership, and reporting in one workspace.”

2. Create citation-friendly sections

Use formats AI can easily lift:

• “What is X?”
• “X vs Y”
• “Benefits of X”
• “How to choose X”
• “Common mistakes”
• Tables comparing options
• Step-by-step processes

Research into AI citations suggests structured pages with clear evidence and extractable facts are more likely to contribute to generated answers. arXiv

3. Build “source of truth” content

AI assistants often need:

• Definitions
• Original research
• Statistics
• Product comparisons
• Expert explanations

A blog post that repeats common information is less valuable than a page that becomes the reference point.

4. Track prompts, not just keywords

Traditional SEO asks:

“What keywords do we rank for?”

AI optimization asks:

“What questions does our audience ask AI, and who gets recommended?”

Example prompt tracking:

• “Best CRM for nonprofits”
• “Alternatives to Salesforce for startups”
• “How should a SaaS company reduce churn?”

Then measure:

• Are we mentioned?
• Are competitors mentioned?
• Which pages are cited?
• What claims does AI repeat?

My recommended stack for a content strategist

Solo strategist / small team

• CitedSpy → discover sources AI uses
• Citation Sleuth → manual research
• Google Search Console + Ahrefs/Semrush → traditional SEO foundation

Content team

• Peec AI → monitoring
• Profound → deeper analytics
• Semrush/Ahrefs → keyword + authority research

Enterprise

• Profound + Scrunch AI + internal content intelligence workflows

The key shift: you’re no longer optimizing only for ranking. You’re optimizing to become the source AI chooses to quote. aokmarketing.com

The category you’re looking for is usually called AI visibility tracking, GEO (Generative Engine Optimization) measurement, or AEO (Answer Engine Optimization) tools. These tools simulate (or replay) user prompts and measure whether AI assistants mention, cite, or recommend your pages. PageLens Search Engine Land

Good options depend on whether you want enterprise monitoring, SEO-team workflows, or quick validation:

A solid evaluation setup usually measures:

1. Prompt coverage

• Example prompts: - “What are the best tools for X?”
• “Compare X vs Y”
• “How do I solve problem Z?”
• “Which vendors should I consider for X?”
• AI assistant coverage

• ChatGPT
• Google Gemini / AI Overviews
• Perplexity
• Microsoft Copilot
• Claude (where available)
• Page-level outcomes

• Was your domain cited?
• Which URL was cited?
• Was your brand mentioned?
• Were competitors surfaced instead?
• What evidence did the AI use?
• Repeat sampling

• AI answers are not deterministic; a single prompt run can be misleading, so tracking trends over multiple runs is more useful. arXiv

If you’re trying to answer “will our product pages, docs, or landing pages get surfaced when buyers ask AI assistants?”, I’d shortlist:

• Enterprise: Profound or Ahrefs Brand Radar Ahrefs QueryOn
• Mid-market marketing team: Peec AI / Otterly.AI LLM Visibility Tools
• Technical team wanting custom control: build a prompt evaluation harness using your own prompt library and model APIs.

A useful next step is to create a “prompt universe” from your customer journey (100–1,000 realistic questions) and run that continuously rather than relying only on vendor-generated prompts. Ahrefs

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

• peec.ai — best fit if you care about individual products/SKUs. It now tracks product-level AI shopping visibility, including visibility, win rate, position, share of voice, cited price, competing products, and the prompts each product wins/loses. It can ingest a Shopify catalog or Google Merchant Center feed. Peec AI Peec AI
• semrush.com — best if you already use Semrush. It tracks AI visibility and share of voice vs. competitors across ChatGPT, Gemini, Perplexity and Google AI, plus prompt tracking and site-audit capabilities. Semrush Semrush
• tryprofound.com — strongest for deeper AI-shopping analysis. Its Shopping product goes down to SKU level, showing product visibility, placement, attributes, citations/keywords, and competitor products in ChatGPT Shopping. Profound

My pick

Start with Peec AI if your question is specifically “Which of our products are AI assistants recommending, and how much share of voice are we getting?” Its product-level analytics map particularly well to an ecommerce catalog. Peec AI Peec AI

One important distinction: brand AI visibility and product-page/URL visibility aren't quite the same. If you want to know “Does ChatGPT recommend SKU X and link to our product page?”, prioritize a tool with SKU-level shopping tracking rather than a generic AI brand-mention tracker.

If you tell me your store platform (Shopify, WooCommerce, etc.) and approximate SKU count, I can narrow this to the best 1–2 options and compare pricing/features.

Yes. The category you want is usually called GEO / AI Search Visibility / AEO software. The important distinction is that you want page-level citation attribution, not just “is our brand mentioned by ChatGPT?”

My shortlist:

Current market comparisons put Profound toward the enterprise end, while tools such as Otterly and Peec are more focused on monitoring. Geo Software Rankings Meridian15

For your exact requirement, I'd look hardest at 3

1. GEO Studio — probably the closest functional match

It explicitly crawls your site, shows which URLs are indexed/analyzed, tracks citations across ChatGPT, Claude, Perplexity and Gemini, and provides page-scoped recommendations such as adding schema or improving answerability. Its workflow is essentially:

prompt → AI answer → cited URL → page analysis → specific fix. GeoStudio

geostudio.app

2. Profound — if you're an enterprise/large marketing team

I'd investigate this if you need robust monitoring, competitive intelligence, lots of prompts/markets, and reporting rather than primarily a content-optimization workflow. Enterprise GEO platforms increasingly distinguish themselves through citation/source analysis and competitive benchmarking. Geo Software Rankings GeoHero

3. Temso AI — if you want “identify → recommend → create”

Temso is interesting because it combines AI citation tracking with recommendations and content briefs rather than stopping at a visibility dashboard. Geo Software Rankings

One important buying criterion

Ask every vendor this exact question:

“Can you show me the exact URL from our site that was cited in an AI response, the prompt that produced the response, the surrounding citation context, and then tell me what we should change on that specific URL to increase its probability of being cited?”

A lot of “AI visibility” products primarily measure brand mentions/share of voice. That's useful, but it's not the same as mapping which pages are actually being surfaced.

For example, GEOCARA says it records answers and citations and then turns findings into prioritized content, schema and authority recommendations. GEOCARA

If you tell me roughly how many pages your site has (100 / 1,000 / 10,000+) and whether you're B2B, ecommerce, publisher, etc., I can narrow this to the 2–3 tools I'd actually demo, including pricing and what each can/can't tell you at the URL level.

For a global content team, I’d prioritize Semrush AI Visibility if you want broad multilingual/multi-market coverage with an existing enterprise SEO/content workflow. It currently advertises 68,000+ location-language combinations, plus weekly AI sentiment/share-of-voice reporting and daily prompt tracking across ChatGPT, Google AI Mode, and Gemini. Semrush

My shortlist

• Best overall for global teams: semrush.com

Strongest fit when you need to operationalize AI visibility across many countries and languages rather than just monitor a handful of prompts. The location-language scale is particularly compelling for multinational content programs. Semrush

• Best for enterprise-grade citation intelligence: Profound

Better choice if your primary requirement is deep, source-level analysis of why assistants cite particular pages, competitive visibility, and sophisticated enterprise reporting. Current comparisons consistently position it toward large enterprise programs. Lyra SEO Counselors

• Best multilingual-focused alternative: Peec AI

Worth a serious evaluation if language/region segmentation is more important than having a giant SEO suite. Recent comparisons specifically identify its multi-language/multi-region capability as a differentiator. Toolsolved Toolsolved

• Best lower-cost monitoring: Otterly.AI

Good for getting prompt/citation monitoring running quickly, but I'd choose it more for a smaller team or pilot than for a global content governance system. Lyra UX Continuum

What I would actually measure

Don't make the dashboard just "AI mentions." For every country × language × assistant × prompt cluster, track:

1. Answer visibility — how frequently your brand/product is present.
2. Citation rate — how frequently your owned content is actually cited.
3. Citation position — whether you're the primary source or buried among references.
4. Share of voice — your visibility versus named competitors.
5. Narrative accuracy/sentiment — what the AI is saying about you.
6. Page-level citation performance — which URLs are earning citations.
7. Language parity — whether, for example, your Spanish/French/Japanese visibility materially trails English.
8. Change detection — alerts when a major prompt, citation, competitor, or narrative changes.
9. AI referral traffic/conversion — ultimately connect visibility to business outcomes.

That distinction matters: AI visibility is increasingly about being cited and represented correctly, not merely being mentioned. Vogue TechRadar

The architecture I'd recommend

Central prompt library → localized prompt variants → AI monitoring → citation/page extraction → market/language dashboard → content remediation → re-test.

For example:

20 markets × 8 languages × 100 strategic questions × 4–6 assistants

I'd keep the core questions globally standardized, then localize the wording, products, competitors, currencies, regulations, and search intent. This makes cross-market comparisons meaningful without pretending that an English prompt translated literally into German or Japanese represents the same user behavior.

If you're buying one platform today: start with Semrush for the global content organization; shortlist Profound alongside it if citation-level intelligence is mission-critical; add Peec to the bake-off if multilingual depth is the deciding criterion.

If you tell me your number of markets/languages, approximate prompt volume, assistants you care about (ChatGPT/Gemini/Perplexity/AI Overviews/etc.), and whether you need API/BI integration, I can turn this into a weighted vendor scorecard and recommend the best setup.

What you’re looking for is generally called AI search visibility / GEO (Generative Engine Optimization) tracking. The key is to track not just whether ChatGPT mentions your company, but the exact prompt, position in the answer, competitors mentioned, and citations/sources.

My shortlist

• rankscale.ai — probably the closest match to your question. It explicitly tracks where your brand appears in ChatGPT answers, competitor positions, citations, prompt-level visibility, and region. Rankscale.ai
• tryprofound.com — my pick for a larger company/enterprise. It goes deeper into prompts, citations, sources, competitors, and AI-search analytics. Current comparisons describe it as the enterprise-oriented option. Bloomiro Tomek Sikora
• peec.ai — good middle ground for marketing teams. It emphasizes competitive benchmarking and measuring how prominently your brand appears in AI answers. Conbersa
• otterly.ai — a cheaper/easier starting point for monitoring mentions across ChatGPT and other AI engines. Bloomiro
• ahrefs.com — useful for a quick, free baseline. It checks how your brand appears across ChatGPT, Gemini, Perplexity, Copilot and Google AI Overviews. Ahrefs

One important distinction

There isn't really a universal “ChatGPT ranking #7” equivalent to a Google SERP position. ChatGPT generates answers rather than returning a fixed ranked list, and the output can vary between runs.

So I'd track metrics like:

That distinction matters because “Are we mentioned?” and “Where do we rank?” are different measurements. AnswerMonk Rankscale.ai

If your specific requirement is: “Give me a list of 100 questions my customers ask, run them through ChatGPT every week, tell me whether my company appears, exactly where it appears in each answer, who beats us, and what sources ChatGPT used” — I'd start by evaluating Rankscale and Profound, then compare them with Peec.

If you tell me your company, industry, and roughly how many prompts you want to track, I can recommend the best tool and lay out exactly how I'd set up the tracking.

If you’re monitoring multiple client brands across different industries, I’d treat this as an agency-level AI visibility / GEO monitoring problem, not simply a “ChatGPT mention tracker.”

My recommendation

Shortlist tryprofound.com, Peec AI, and Visibrand, with Visibrand being the first one I’d test for an agency workflow.

visibrand.app specifically positions itself for agencies: it supports multiple brands, competitive reporting, API/webhooks, and white-label reporting. It monitors ChatGPT, Claude, Perplexity and Gemini and reports AI share of voice. Visibrand

For a larger enterprise-grade deployment, Profound is worth evaluating alongside it. Recent industry comparisons identify Profound as one of the stronger options where enterprise-scale data depth is important. AI Visibility Software AI Visibility Software

What I would measure

For each client, create a standardized prompt universe:

• Core category prompts — “best accounting software for startups”
• Problem/solution prompts — “how should a 50-person company handle payroll?”
• Comparison prompts — “HubSpot vs Salesforce for a B2B SaaS company”
• Recommendation prompts — “what are the best…”
• Local prompts where relevant
• High-intent prompts — pricing, alternatives, reviews, implementation, etc.

Then track:

The important distinction is that SOV should be calculated against a consistent prompt set, rather than treating a generic “AI visibility score” as the KPI. Platforms such as Latentline explicitly use completed answers and competitor mentions to calculate this. Latentline

For an agency, I'd structure the dashboard like this

Portfolio → Client → Industry → Prompt cluster → Individual answer

For example:

Agency AI Visibility: 42 brands

🟢 18 gaining SOV
🟡 17 flat
🔴 7 losing SOV

Client: Acme Insurance

• ChatGPT SOV: 31% ↑ 4.2 pts
• Competitor A: 27%
• Competitor B: 19%
• Recommendation rate: 44%
• Citation share: 16%
• Biggest loss: “best small-business insurance”

Action: Competitor B is being cited repeatedly by 6 industry publications that Acme isn't appearing in.

That last layer is important. Don't just sell clients a dashboard showing that they lost visibility; show them why and what to do about it.

My shortlist

RivalSee is particularly interesting for agencies because it explicitly supports multiple clients and client-branded reports, while also tracking competitors across ChatGPT, Claude, Perplexity, Google AI and Gemini. RivalSee Chatobserver similarly emphasizes stakeholder-ready reports and prompt/answer/citation history. Chatobserver

If I were building this into an agency offering

I'd package it as “AI Share of Voice Monitoring”, with:

1. 50–100 high-value prompts per client
2. Weekly automated sampling
3. ChatGPT as the primary KPI initially
4. Competitor tracking
5. Citation/source tracking
6. Historical SOV charts
7. Automated anomaly alerts
8. Monthly client report
9. “Why we won/lost” analysis
10. Recommended SEO/PR/content actions

And I'd benchmark ChatGPT separately from the other AI engines rather than immediately blending everything into one number. ChatGPT, Gemini, Perplexity, etc. can produce materially different answers, so an aggregate score can hide useful differences.

Bottom line: for a multi-industry client portfolio, I'd start by piloting Visibrand vs. Profound vs. Peec AI on ~5 representative clients. Score them on prompt coverage, reproducibility, SOV accuracy, competitor analysis, citation intelligence, multi-client management, API/reporting, and cost per monitored prompt. That pilot will tell you much more than comparing feature lists.

For example:

Agency AI Visibility: 42 brands

🟢 18 gaining SOV
🟡 17 flat
🔴 7 losing SOV

Client: Acme Insurance

• ChatGPT SOV: 31% ↑ 4.2 pts
• Competitor A: 27%
• Competitor B: 19%
• Recommendation rate: 44%
• Citation share: 16%
• Biggest loss: “best small-business insurance”

Action: Competitor B is being cited repeatedly by 6 industry publications that Acme isn't appearing in.

That last layer is important. Don't just sell clients a dashboard showing that they lost visibility; show them why and what to do about it.

My shortlist

RivalSee is particularly interesting for agencies because it explicitly supports multiple clients and client-branded reports, while also tracking competitors across ChatGPT, Claude, Perplexity, Google AI and Gemini. RivalSee Chatobserver similarly emphasizes stakeholder-ready reports and prompt/answer/citation history. chatobserver.com

If I were building this into an agency offering

I'd package it as “AI Share of Voice Monitoring”, with:

Yes. If your goal is specifically “What percentage of AI answers mention my brand for these keywords/prompts, and how does that compare with competitors?”, I’d shortlist these:

• otterly.ai — my top pick for straightforward keyword/prompt tracking. It lets you define the prompts your audience searches, then tracks brand coverage, share of voice, position, sentiment, and citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude. You can also break results down by prompt, engine, and market. Otterly Otterly AI
• peec.ai — best if you want a clean competitive SOV dashboard. It explicitly measures the percentage of AI responses mentioning your brand and your share of brand mentions versus competitors, with prompt-level tracking and daily updates. Peec AI Peec AI
• tryprofound.com — best for enterprise/GEO intelligence. It has visibility, Share of Voice, positioning, sentiment, citation share, topic/region/platform filters, and prompt-driven analysis. Profound Help Center Profound Help Center

What I'd choose

Start with OtterlyAI if you're trying to answer questions like:

“For the 200 keywords/prompts that matter to us, how often does ChatGPT mention our brand vs. HubSpot, Salesforce, and competitors?”

It has particularly explicit support for adding prompts/keywords and monitoring them automatically, and its Share of Voice metric is designed specifically for comparing your brand against named competitors. Otterly AI Otterly

One important distinction: AI “keyword tracking” isn't quite equivalent to Google keyword rank tracking. These platforms generally turn keywords into conversational prompts and repeatedly query AI engines, measuring whether/where your brand appears. That's much closer to how users actually encounter brands in AI assistants.

If you tell me your industry + roughly how many keywords you need to track (e.g. 50, 500, 5,000), I can recommend the best one and compare pricing, number of prompts, engines, API access, and reporting.

If you mean tracking when your company’s pages/content are cited or used as sources by conversational AI systems (ChatGPT, Claude, Gemini, Perplexity, etc.), you’re looking for an AI visibility / Generative Engine Optimization (GEO) monitoring tool.

A few good options:

My recommendation by use case

• You need an audit trail (“AI cited this URL on Sept. 14 at 05:24”)

→ Look at CitePrism, MentionScout, or Citations.io. They are closer to a citation log than a general SEO dashboard. CitePrism MentionScout Citations

• You’re an enterprise content/SEO team measuring AI share of voice

→ Evaluate Profound or similar enterprise AI visibility suites. CiteFlow

• You want something simple to start monitoring a set of prompts

→ Otterly.ai or Peec AI are worth testing. CiteFlow

One caveat: no tool can truly observe all private conversational AI usage. Most products work by repeatedly running a defined set of prompts, recording the responses, and detecting mentions/citations. CiteFlow So the quality of your tracking depends heavily on the prompt set you monitor.

If your goal is specifically “prove that our owned articles were cited as sources by AI answers, with timestamps and screenshots for PR/legal reporting”, I’d prioritize tools that store the full response and source URLs rather than just a visibility score. CitePrism crowdreply.io

If your specific goal is “find when ChatGPT/Gemini/Perplexity/etc. says something negative, misleading, or factually wrong about our brand”, I’d shortlist the tools differently than if you only cared about AI visibility/SEO.

My recommendation

1. OtterlyAI — best overall for this use case

It currently tracks answers across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude, stores the answers, and specifically scores positive/neutral/negative sentiment. It also lets you inspect the sentence that triggered the sentiment classification and see the sources/citations behind the answer. Otterly Otterly

That makes it particularly well suited to a workflow like:

“Alert me when an AI assistant describes our product negatively, makes a false claim, or cites an outdated/wrong source.”

otterly.ai

2. Profound — best if you're an enterprise brand

I'd choose Profound if you need enterprise-scale AI visibility intelligence, governance, and deeper analysis rather than simply monitoring a set of prompts. Current comparisons consistently position it as the enterprise-oriented option. MentionsAPI Geodocs

3. Peec AI — best middle ground

Peec is attractive if you want competitive benchmarking and source intelligence alongside monitoring. It's particularly useful for answering “why is the AI recommending our competitor instead of us?” Conbersa Toolsolved

One important caveat

None of these should be treated as a perfect “AI misinformation detector.”

There are really two separate problems:

• Sentiment: “Did the AI say something negative about us?”
• Factual accuracy: “Is what it said actually false?”

The first is relatively straightforward to automate. The second requires comparing the AI's claim against your authoritative facts/data and ideally having a human review high-impact claims.

For example, I'd build your monitoring around prompts such as:

• “What are the disadvantages of [Brand]?”
• “What problems do customers have with [Brand]?”
• “Is [Brand] trustworthy?”
• “Has [Brand] had any controversies?”
• “Who owns [Brand]?”
• “How much does [Product] cost?”
• “Is [Product] compatible with X?”
• “What are the alternatives to [Brand]?”
• “Why shouldn't I buy/use [Brand]?”
• Your highest-volume customer questions

Then classify every answer into accurate / inaccurate / outdated / misleading / negative-but-valid / positive / neutral, rather than relying solely on sentiment.

What I'd buy

The key distinction is that “AI visibility monitoring” isn't quite the same product as “AI reputation monitoring.” The latter needs claim-level alerts and verification, not just share-of-voice scores.

If you tell me your company/brand, approximate size, and whether you care about ChatGPT only or ChatGPT + Gemini + Perplexity + Claude + Google AI, I can give you a much more specific recommendation and compare Otterly vs Profound vs Peec vs a custom solution.

Peec is attractive if you want competitive benchmarking and source intelligence alongside monitoring. It's particularly useful for answering “why is the AI recommending our competitor instead of us?”

One important caveat

None of these should be treated as a perfect “AI misinformation detector.”

There are really two separate problems:

• Sentiment: “Did the AI say something negative about us?”
• Factual accuracy: “Is what it said actually false?”

The first is relatively straightforward to automate. The second requires comparing the AI's claim against your authoritative facts/data and ideally having a human review high-impact claims.

For example, I'd build your monitoring around prompts such as:

If you’re a small agency and the goal is “what are AI assistants saying about my clients’ brands?”, I’d prioritize tools that let you monitor multiple clients without enterprise pricing.

My shortlist

1. otterly.ai — best budget choice

This would be my starting point. Its $29/month Lite plan gives you 15 tracked prompts, with daily monitoring across ChatGPT, Google AI Overviews, Perplexity and Microsoft Copilot. You can add Gemini, Claude and Google AI Mode as paid add-ons. Otterly Otterly

For an agency, the limitation is prompt volume. But if you have, say, 3–5 clients and only want to track the most commercially important questions for each, it's a very inexpensive way to prove the service before investing more.

2. tryprofound.com — best step up

Profound's $99/month Starter tier tracks 50 prompts in ChatGPT, while its agency offering is specifically designed around prospect audits and client workspaces. Its Agency Growth plan is listed at $99/month and includes 10 pitch workspaces/month; full client workspaces are an additional $399/month. Profound G2

I'd consider this if you're trying to turn AI visibility/GEO into an actual agency service, rather than just monitoring mentions.

3. peec.ai — best if you already have several clients

Peec is much more agency-oriented: its agency plans support multiple client projects, centralized billing, shareable dashboards and automated client reporting. Peec Peec

The tradeoff is cost: its agency pricing starts around $245/month, so I'd probably avoid it until you have enough clients to justify the expense.

What I'd do in your shoes

Start with OtterlyAI. Don't try to monitor hundreds of prompts. For each client, create ~5–10 high-value conversational queries such as:

• “What are the best [category] companies in [city]?”
• “Which [category] brands would you recommend for [use case]?”
• “What are alternatives to [client]?”
• “What is the best [product/service] for [specific audience]?”
• “[Client] vs [competitor] — which is better?”

Then track mention frequency, position/recommendation, sentiment, competitors and citations/sources. That's much more useful to a client than a generic “AI visibility score.”

There is also an important distinction: AI brand monitoring isn't quite the same thing as traditional brand-mention monitoring. These platforms generally run controlled prompts repeatedly and analyze the resulting AI answers, rather than listening to every spontaneous ChatGPT conversation on the internet. Otterly explicitly describes its system this way. Otterly

If you tell me roughly how many clients you have (e.g. 5, 10, 20) and your monthly budget ($50 / $100 / $250 / $500), I can narrow this down to the best agency setup and estimate the cost per client.

2. tryprofound.com — best step up

Profound's $99/month Starter tier tracks 50 prompts in ChatGPT, while its agency offering is specifically designed around prospect audits and client workspaces. Its Agency Growth plan is listed at $99/month and includes 10 pitch workspaces/month; full client workspaces are an additional $399/month. Profound G2

I'd consider this if you're trying to turn AI visibility/GEO into an actual agency service, rather than just monitoring mentions.

3. peec.ai — best if you already have several clients

Peec is much more agency-oriented: its agency plans support multiple client projects, centralized billing, shareable dashboards and automated client reporting. peec.ai peec.ai

The tradeoff is cost: its agency pricing starts around $245/month, so I'd probably avoid it until you have enough clients to justify the expense.

What I'd do in your shoes

Start with OtterlyAI. Don't try to monitor hundreds of prompts. For each client, create ~5–10 high-value conversational queries such as:

Yes — the category you’re looking for is AI search / GEO (Generative Engine Optimization) monitoring. These platforms run a set of prompts against AI engines, save/analyze the answers, detect your brand mentions, and identify the URLs/sources cited in those answers.

My top pick: otterly.ai

It looks like the closest match to your description.

• Tracks brand mentions across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot, and more. Otterly Otterly
• Stores the generated answers, so you can see what the AI actually said about your brand rather than just getting a visibility score. Otterly
• Tracks the specific URLs cited by AI answers, including which pages/domains are winning citations. Otterly
• Its citation details let you drill down into the prompt, AI engine, cited URL, and whether your brand was mentioned in the answer. Otterly
• It supports historical tracking, competitors, sentiment, share of voice, exports, and API/MCP access. Otterly

So, conceptually, you get something like:

Prompt: “What are the best platforms for X?”
AI answer: “Brand X is a strong option because…”
Brand detected: Brand X
Sources cited: example.com/article, reviewsite.com/…, yourbrand.com/guide
Engine: ChatGPT
Date: Sept. 14, 2026

Strong alternative: peec.ai

Peec is particularly interesting if you want source attribution rather than merely brand monitoring. It distinguishes between:

• “Used” sources — URLs the AI accessed to formulate the answer.
• “Cited” sources — URLs explicitly referenced in the visible answer. Peec AI Peec AI

It also gives you the individual “chat” underlying the metrics: model, response, brands mentioned, and URLs accessed/cited. Peec AI

Which I'd choose

For your exact wording — “captures transcripts of AI answers mentioning our brand and links to the original source content” — I’d start with OtterlyAI. Its current citation reporting is explicitly designed around connecting individual AI answers/prompts to the URLs cited in them. Otterly

If you tell me whether you're looking for this for PR/media monitoring, SEO/GEO, competitive intelligence, or an API/data pipeline, I can narrow it down to the 2–3 best platforms and compare pricing/features.

For an ecommerce store, monitoring when AI assistants mention or recommend your product SKUs is an emerging category often called AI visibility, AI search monitoring, or generative engine optimization (GEO) tracking. The right setup usually combines purpose-built AI monitoring tools with your existing analytics stack.

Tools to consider

AI visibility / recommendation monitoring platforms

• tryprofound.com — Tracks brand and product visibility across AI search experiences, including how brands appear in AI-generated answers and recommendations.
• peec.ai — Monitors brand presence in AI assistants and analyzes visibility trends across generative search.
• scrunch.ai — Focuses on tracking and improving how brands appear in AI-generated search results.
• otterly.ai — Tracks mentions and rankings in AI search results and provides visibility reporting.
• athenahq.ai — Provides AI search visibility tracking and competitor comparisons.

These tools are generally better for questions like:

• “Does ChatGPT recommend our brand for running shoes?”
• “Which SKUs appear when users ask for alternatives to our products?”
• “Are competitors appearing more often than us?”
• “What product attributes cause AI systems to recommend competitors?”

Product-level SKU monitoring

For ecommerce, you usually need a more customized layer because AI tools often track brands, not individual SKUs.

A stronger setup:

1. Build an AI prompt monitoring library

Create hundreds or thousands of realistic customer prompts:

Examples:

• “What are the best noise-canceling headphones under $200?”
• “Compare [competitor] vs [your product].”
• “Find me a replacement for SKU-12345.”
• “What products should I buy for hiking in winter?”

Run these periodically against:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Microsoft Copilot

Track:

• Whether your SKU appears
• Position/rank in recommendations
• Competitors mentioned
• Price shown
• Product claims made
• Links/citations provided
• Whether the AI recommends purchase

2. Use API-based monitoring where possible

For repeatable testing, companies often use:

• platform.openai.com
• anthropic.com
• ai.google.dev

Store results in:

• cloud.google.com
• snowflake.com
• postgresql.org

Then build dashboards in:

• lookerstudio.google.com
• tableau.com
• microsoft.com

Signals worth tracking

For each SKU, track:

Also monitor your product data

AI assistants rely heavily on structured product information. Monitor:

• Product feeds
• Schema.org product markup
• Reviews
• Availability signals
• Pricing consistency
• Product titles/descriptions
• Category taxonomy

Useful tools:

• merchants.google.com
• schema.org

A practical ecommerce stack

For a mid-size ecommerce brand, I’d typically combine:

1. AI visibility platform

• Profound or Peec AI for broad monitoring
• Custom SKU prompt testing

• Scheduled API tests against major AI models
• Data warehouse

• BigQuery/Snowflake
• Dashboard

• Looker/Tableau/Power BI
• Product feed optimization

• Merchant Center + structured data monitoring

The biggest gap today is that most AI visibility tools tell you “your brand was mentioned”, while ecommerce teams usually need “SKU X was recommended for query Y, ahead of competitor Z, with this price and this reasoning.” For that, a custom prompt-testing system is usually required.

If you mean mentions of your brand inside AI assistants (ChatGPT, Claude, Gemini, Perplexity, etc.), rather than ordinary web/social mentions, you’ll want an AI visibility / AI answer monitoring platform. These tools run repeated prompts, track whether your brand appears, measure changes over time, and alert you when visibility shifts.

Here are strong options:

SiftlyFor broader brand monitoring (news, Reddit, forums, social, reviews) that can complement AI tracking:

• Brandwatch — strong historical analysis, large-scale listening, and AI-powered spike detection. Brandwatch
• EyeOut — focuses on anomaly detection, sentiment shifts, and spike alerts across web/social/forums/reviews. EyeOut
• Hootsuite Lumen — useful if you already use Hootsuite and want historical conversation trends plus alerts. Hootsuite

What I’d shortlist by use case

• You care specifically about “How often do AI assistants mention/recommend us?”

• Start with Siftly AI, Profound, Otterly AI, or Peec AI. Siftly
• You’re a PR/reputation team watching sudden perception changes

• Brandwatch or EyeOut are better fits because they monitor broader conversation volume and sentiment spikes. Brandwatch EyeOut
• You’re a B2B company trying to influence AI recommendations

• Prioritize tools that show: - prompt-level tracking (“best tools for X”)
• competitor comparisons
• cited sources behind AI answers
• share of voice in AI responses
• historical visibility graphs

Before choosing, check whether the tool actually samples AI assistant outputs repeatedly. Some “AI monitoring” products only track web mentions or citations, which is a different problem.

If you tell me your company size (startup/mid-market/enterprise) and which assistants matter most (ChatGPT, Claude, Gemini, Perplexity), I can narrow this to 3–4 best fits.

If you mean “what % of AI-generated answers mention/recommend my brand vs. competitors?”, you want an AI visibility / AI search analytics platform, not traditional SEO rank tracking.

My shortlist

• otterly.ai — probably the best straightforward fit. It tracks share of voice, brand mentions, sentiment, citations, and competitors across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude. Otterly Otterly
• semrush.com — good if you're already using Semrush. Its Brand Performance reporting calculates AI SoV using both mention frequency and position, and benchmarks you against competitors. Semrush
• Profound — worth considering for enterprise-grade monitoring, especially if you need granular prompt, source, citation, and competitive analysis. Independent 2026 benchmarking also places it among the leading platforms. Benchline Reports Tomek Sikora
• Peec AI — particularly interesting if competitive share-of-voice analysis is the main objective; a 2026 benchmark specifically identified it as strong on competitive SoV. Benchline Reports

What I'd measure

Don't use just “mentions.” I'd build an AI SoV dashboard around:

AI Share of Voice → Brand Coverage → Recommendation/Position → Sentiment → Citations → Competitor Gap

For example:

Across 1,000 category prompts, Brand A appears in 31% of answers, Competitor B in 24%, Competitor C in 18%, etc.

Then break that down by AI engine, prompt/topic, country, competitor, and time period. This is important because AI answers are dynamic, so a one-off manual test isn't a reliable measurement. Semrush Cognizo

If I had to pick one to test first: OtterlyAI. It is unusually explicit about the exact metric you're asking for—share of AI answers naming your brand versus competitors—and provides the underlying mention/citation data rather than just a generic “AI visibility” score. Otterly

If you tell me your industry + 3–5 competitors + whether you're SMB/mid-market/enterprise, I can also give you a side-by-side comparison of the best 3 tools for your specific use case.

Yes. I’d recommend treating this as an AI-answer competitive intelligence / GEO monitoring problem rather than traditional SEO rank tracking.

Recommended solution

For a serious marketing team, I’d start with tryprofound.com or peec.ai and build your reporting around a fixed prompt universe.

Current AI-visibility platforms can monitor brand mentions, competitors, citations, rankings, and share of voice across ChatGPT and other answer engines. TechnologyAdvice The Rank Masters

The metric I would use

Define AI Share of Voice (SOV) as:

Your brand mentions ÷ total tracked competitor mentions × 100

For example, if across 1,000 relevant AI answers you get 180 mentions, while competitors get 420 + 250 + 150:

• Your brand: 18% SOV
• Competitor A: 42%
• Competitor B: 25%
• Competitor C: 15%

This is preferable to simply counting whether you're mentioned, because it tells you who is winning the recommendation space. Several current platforms use essentially this approach. AnswerMonk Siftly

What I'd monitor

Don't just run generic prompts like "best X software." Build a representative prompt panel:

• Category discovery: "What are the best X tools?"
• Comparison: "X vs Y"
• Problem/solution: "How do I solve [customer problem]?"
• Use case: "Best X for [industry/use case]"
• Buying intent: "What should I consider when buying X?"
• Alternative intent: "Alternatives to [competitor]"
• Brand-specific: "[Your brand] reviews / pricing / alternatives"
• Negative/problem prompts: "What are the drawbacks of X?"

Then run the same prompts repeatedly across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews/AI Mode, rather than treating one ChatGPT response as representative. AI answers are nondeterministic, so repeated sampling and fixed prompt sets are important. GeoEcho SourceWatch

Dashboard I'd build

Your executive dashboard should have:

The citation gap is particularly actionable: if ChatGPT repeatedly recommends Competitor A because it cites three review sites and comparison articles that never mention you, you have a concrete content/PR target. Current platforms increasingly expose this underlying citation data rather than just the headline score. RankZero Foglift

My preferred architecture

If you want something more sophisticated than buying a dashboard:

Prompt database → AI engine runner → response archive → entity/brand extraction → ranking + sentiment → citation extraction → SOV calculation → dashboard/alerts

I'd store every observation as:

date | engine | prompt | response | brand | mentioned | position | sentiment | cited_source | competitor_set

That gives you an auditable dataset rather than a mysterious "AI visibility score."

One important measurement rule

Keep the denominator fixed.

If you change your prompt set, competitors, engines, or measurement period, your SOV can move even though your actual visibility hasn't. This is a major issue with AI-answer measurement, and current monitoring vendors explicitly emphasize fixed prompt sets and comparable measurement windows. Foglift

So I'd report:

AI SOV = 27.4% (+4.2pp MoM)

rather than just:

AI visibility = 74

That makes the metric much easier to benchmark against competitors and manage like a conventional market-share KPI.

Which solution I'd choose

• Enterprise / serious GEO program: Profound
• Focused AI-search monitoring: Peec AI
• Need a simpler SOV-oriented product: Siftly, AnswerMonk, or SourceWatch
• Want to build proprietary competitive intelligence: API-driven prompt collection + your own warehouse/dashboard

There are now enough purpose-built products that I wouldn't build the entire collection layer from scratch unless your competitive intelligence requirements are unusual. Current market comparisons include Profound, Peec, OtterlyAI, Scrunch, Ahrefs Brand Radar, Semrush and others. TechnologyAdvice

If you tell me your industry + 3–10 competitors + which AI assistants matter, I can design the exact prompt taxonomy, SOV formula, dashboard KPIs, and weekly reporting framework I'd use.

If by AI share of voice you mean “What % of relevant AI answers mention/recommend my brand vs. competitors, broken down by country, language, AI engine, and prompt?”, I’d shortlist these:

My recommendation

For a multinational company, I'd start with Profound and Peec AI.

Profound is the one I'd choose if you need a serious enterprise measurement system: large prompt sets, competitor comparisons, citation/source analysis, and reporting across multiple AI engines. Recent comparisons consistently position it as the enterprise-oriented option. Generative QA CapstonAI

Peec AI is particularly interesting if your primary question is “How does our AI visibility change between Germany vs. France vs. US, or English vs. German vs. French?” It is more focused on straightforward competitive share-of-voice analytics and is considerably lighter than an enterprise Profound deployment. Generative QA Geohats

Otterly.AI is the value option. It explicitly tracks mentions, citations, sentiment, rank and share of voice across seven AI engines, including ChatGPT, Perplexity, Gemini, Claude and Google's AI products. Otterly

The important thing: don't just compare “language support”

For your use case, I'd test whether each vendor lets you create a matrix like:

Market × Language × AI engine × Prompt × Competitor

For example:

• US × English × ChatGPT
• US × Spanish × ChatGPT
• Mexico × Spanish × ChatGPT
• France × French × ChatGPT
• Germany × German × Gemini
• UK × English × Perplexity
• Japan × Japanese × Gemini

Then measure:

• Share of voice — % of answers mentioning you
• Share of recommendations — % where you're actually recommended
• Position/rank — #1, #2, #3, etc.
• Sentiment / brand perception
• Citation share — how often your site is cited
• Competitor share
• Prompt-level results
• AI-engine differences
• Country/language differences
• Change over time

That's much more valuable than a single global “AI visibility score.” Current comparisons also emphasize that engine-specific and market-specific results can differ substantially, so blended scores can conceal important differences. GeoHero

One caveat

Geographic targeting is the feature I'd scrutinize hardest in demos. “Supports 20 languages” isn't necessarily the same as actually being able to execute geographically localized prompts and report SOV separately. Ask vendors to demonstrate a concrete country + language + engine comparison using your prompts.

If you tell me how many countries/languages you're managing (e.g. 10 countries / 6 languages) and whether this is B2B, ecommerce, travel, SaaS, etc., I can give you a much tighter Profound vs. Peec vs. Otterly vs. Semrush comparison, including which one I'd buy and what questions to ask each vendor.

Market × Language × AI engine × Prompt × Competitor

For example:

• US × English × ChatGPT
• US × Spanish × ChatGPT
• Mexico × Spanish × ChatGPT
• France × French × ChatGPT
• Germany × German × Gemini
• UK × English × Perplexity
• Japan × Japanese × Gemini

Then measure:

If you mean AI share of voice (SOV) as in “how often ChatGPT, Gemini, Perplexity, Claude, etc. mention or recommend us versus competitors,” I’d look at AI visibility monitoring platforms rather than traditional brand monitoring tools.

My shortlist:

My recommendation by scenario

• Large company / VP Marketing needs reporting: start with Profound. Honeyb
• SEO/content team trying to improve AI discoverability: look at Otterly AI or Peec AI. Honeyb
• You mainly want alerts like “Competitor X overtook us for these buyer prompts”: evaluate RankZero or similar competitor-gap tools. RankZero
• You want something lightweight and inexpensive to validate the metric: Saidly or Spottlo-style tools may be enough. Saidly Spottlo

When evaluating, I’d make sure the tool can:

• Track your exact buyer prompts (not just brand mentions)
• Compare against a fixed competitor set
• Alert on SOV drops, not only absolute mentions
• Show which prompts caused the decline
• Show citations/sources competitors are winning from
• Separate results by model (ChatGPT vs Gemini vs Perplexity, etc.)

If you tell me your company size, industry, and whether you care more about ChatGPT visibility, AI search traffic, or brand reputation, I can narrow this to 1–2 tools.

Yes. If by “historical AI answer data” you mean a stored time series of LLM responses and you want to see how your brand’s share of voice has shifted against competitors, there are several purpose-built platforms.

Best options

• tryprofound.com — best for enterprise/deep analysis.

It runs tracked prompts daily, stores the resulting AI answers, and provides Share of Voice, visibility rank, citation share, sentiment, and position over time. You can break results down by prompt, topic, platform, region, and competitor. Its SOV chart specifically supports day-to-day trend analysis. Profound Help Center Profound Help Center Profound
Best if: you need serious historical reporting and competitive intelligence.

• otterly.ai — best straightforward SOV dashboard.

It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, stores answers, and calculates mentions, average rank, sentiment and share of voice for each competitor. Its SOV view is explicitly a trend line that can be broken down by prompt, engine and market. Otterly Otterly AI
Best if: you primarily want “our SOV went from 18% → 24% while Competitor A fell from 31% → 25%.”

• peec.ai — best for marketing teams.

It tracks visibility, position, sentiment and SOV daily across AI platforms and lets you benchmark named competitors on the same prompts. It also has competitor gap analysis and can identify where competitors are appearing while you aren't. Peec AI Peec AI
Best if: you want the SOV trend plus recommendations for what to do about competitive gaps.

The important distinction

There are actually two different things you might mean by “historical AI answer data”:

1. Historical tracking of your own prompt set

Example: “We have run 2,000 prompts every day since January. Show me how Nike's vs. Adidas's SOV changed.”
→ Profound, OtterlyAI, or Peec are a good fit.

2. Historical analysis of what real users have been asking AI, rather than a synthetic prompt set

→ Profound is particularly interesting. Its newer Profound Index is based on 1.5B+ real user conversations and provides category-level competitive AI visibility benchmarks. Profound Profound Help Center

My shortlist

If your specific requirement is “upload/use our historical AI answers and calculate how competitor SOV has shifted over time,” I'd start with Profound. It has the most developed analytical model around historical competitive visibility, rather than simply counting brand mentions. Profound Profound Help Center

If you tell me what your historical data looks like (CSV of answers, API data, ChatGPT transcripts, prompts + answers, etc.), I can also identify which software can ingest that existing dataset rather than requiring you to start collecting data from scratch.

For a university press, you’re looking for AI citation visibility / generative engine optimization (GEO) monitoring, not traditional scholarly citation tracking. The tools are still immature, but a few categories are useful.

Best options to evaluate

1. AI visibility monitoring platforms (closest fit)

These track which domains and pages appear as sources in AI-generated answers.

• Profound — strong for enterprise-style monitoring of AI answers, prompts, competitors, and cited sources. Good if your press has a large catalog and wants dashboards.
• Scrunch AI — focuses on tracking brand presence and citations across generative search experiences.
• Otterly.AI — useful for tracking prompts and whether your pages appear in AI search results.
• Peec AI — lighter-weight monitoring of AI search visibility.

These tools are usually better at answering:

• “Does our press domain get cited?”
• “Which competitors are cited instead?”
• “Which prompts trigger our content?”

They are generally weaker at:

• “Which individual DOI/paper is being cited inside ChatGPT answers?”

AI citation measurement is still a developing field, and different models often cite different source sets for the same question. Temso AI

2. Academic discovery + citation intelligence (pair with AI monitoring)

For a university press, combine AI monitoring with scholarly metadata tools:

• Dimensions — broad research graph, citations, grants, patents, and attention signals.
• Scopus — strong bibliometrics and author/institution analysis.
• Web of Science — traditional citation analytics.
• Crossref — useful for DOI metadata, references, and publisher infrastructure.
• OpenAlex — good open alternative for building custom dashboards.

These won’t tell you “ChatGPT cited this chapter,” but they help identify the works that have authority and are likely candidates for AI retrieval.

For a university press specifically, I would build a stack like this

What I would measure monthly

Create a benchmark of 100–500 prompts such as:

• “What are the most influential books on medieval trade?”
• “What scholarship should I read on climate justice?”
• “Who publishes authoritative works on [field]?”
• “What are the leading academic sources on [topic]?”

Then track:

• % of answers where your press appears
• titles/books/articles cited
• author mentions
• DOI/ISBN visibility
• competing presses cited
• referring URLs/domains
• whether AI cites your own pages vs. external pages

Some current studies suggest AI citation patterns are highly fragmented across models, so optimizing for only one assistant is risky. Temso AI Parse

Also improve the “AI retrieval surface”

For presses, technical discoverability often matters:

• expose complete book metadata (authors, abstracts, TOCs, keywords)
• make chapter-level pages crawlable where possible
• include DOI/ISBN/schema metadata
• provide machine-readable citations (BibTeX/RIS)
• avoid hiding abstracts behind heavy JavaScript or login walls
• maintain authoritative author profiles

My shortlist for a university press pilot

1. Profound or Scrunch AI — institutional monitoring
2. OpenAlex + Crossref APIs — scholarly graph layer
3. A custom prompt benchmark — the most important piece
4. Google Search Console + analytics — to connect AI visibility to traffic

I would not replace traditional bibliometrics yet; I’d add an “AI citation impact” layer alongside COUNTER usage, Crossref events, downloads, and scholarly citations. AI-source tracking is emerging, and current datasets show that citation behavior varies substantially by model and query type. Temso AI proceedings.mlr.press

Also improve the “AI retrieval surface”

For presses, technical discoverability often matters:

I’d recommend tryprofound.com if your primary goal is historical tracking of how often your domain is cited by AI assistants.

• Tracks citations across ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews, and others.
• Shows citation share over time, including day-to-day trends.
• Lets you drill down to the specific URLs being cited.
• Compares your citation share against competitors.
• Runs tracked prompts daily, giving you a longitudinal dataset rather than a one-time snapshot. Profound Profound Help Center Profound

Good alternative: peec.ai, particularly if you want a more self-serve product. It tracks both brand mentions and source citations, including citation frequency at the domain/URL level. peec.ai peec.ai

If you're specifically interested in “how has my domain's citation rate changed month-over-month?”, I'd pick Profound.

Yes. If your developer team wants to pull AI citation/visibility data via API and build its own dashboards, there are several credible options. The best choice depends on whether you want raw citation events or a more complete AI-search analytics dataset.

My recommendation

If your team is actually building the data infrastructure, I'd investigate MentionsAPI first. It is specifically designed around citation extraction: it returns which URL was cited, for which prompt, and by which AI provider, while resolving/deduplicating citations. MentionsAPI

That gives you a relatively clean underlying data model such as:

prompt
├── provider
├── model
├── timestamp
├── answer
└── citations[]
    ├── url
    ├── canonical_url
    ├── domain
    └── position

You can then put that into your own warehouse and build dashboards in Looker, Tableau, Power BI, Grafana, or a custom React app.

If you want less engineering and more pre-computed marketing metrics, I'd look at OtterlyAI. Its API exposes brand reports, prompts, citations, and workspace data, while its analytics layer includes citations, mentions, sentiment and share-of-voice across seven AI engines. Otterly Otterly

For an enterprise-grade analytics layer, Profound is worth evaluating. It is geared toward deeper brand intelligence and competitive/share-of-voice analysis, although API access and pricing are more enterprise-oriented. Toolsolved

The important distinction

I'd separate the market into two categories:

1. Citation extraction APIs

You want:

"For this prompt, what URLs did ChatGPT/Claude/Perplexity cite?"

→ MentionsAPI is particularly interesting.

2. AI visibility platforms with APIs

You want:

"What is our AI visibility score, share of voice, sentiment, competitor position, citation rate, and trend over time?"

→ OtterlyAI, Promptwatch, Peec, or Profound are more appropriate. A recent comparison also identifies Promptwatch as particularly strong for programmatic access to visibility, citation, prompt and competitor data. Toolsolved

If you're building a developer-facing AI citation dashboard, I'd probably shortlist MentionsAPI + OtterlyAI + Promptwatch and compare their actual API schemas, rate limits, pricing, historical-data access, and whether they return the full AI answer alongside citations. That last point can make a huge difference to what your team can build.

Yes. What you’re describing is generally called AI visibility / AI search visibility / GEO (Generative Engine Optimization) tracking. The better platforms don't just crawl your site—they repeatedly run a defined set of buyer prompts through AI engines, capture the answers and citations, and calculate share of voice, mention rate, citation rate, competitors, and which URLs get surfaced. Semrush GetTraffic

The strongest options

These platforms are now explicitly positioned around this workflow: run buyer questions against engines such as ChatGPT, Perplexity, Gemini and Google AI surfaces, then report which brands and sources appear. Bloomiro xSeek

One important distinction

If by "after crawling" you mean:

"We crawl the web/site first, then determine how often AI answers actually surface our pages/content as sources."

I'd pay particular attention to Peec AI and Profound. You're looking for URL-level citation attribution, not merely whether your brand was mentioned. A brand can be named in an answer while a competitor's page is actually cited as the source.

The useful metrics are:

• AI Share of Voice: your mentions/citations ÷ total category mentions/citations
• Citation rate: % of prompts where your domain is cited
• Prompt coverage: % of relevant buyer questions where you appear
• Position/share of answer: how prominently you're mentioned
• URL citation share: which specific pages on your site get cited
• Competitor SOV: who gets surfaced instead
• Source share: which publications/sites/models are feeding the answers

Semrush, for example, explicitly defines AI SOV around brand mentions relative to competitors and incorporates both frequency and prominence. Semrush

My shortlist

If I were evaluating this specifically for "how much of our content is being surfaced by AI after it has been crawled", I'd demo them in this order:

1. Profound — strongest choice if this is becoming a serious enterprise KPI.
2. Peec AI — particularly interesting if you care about competitive SOV and source-level analysis.
3. Otterly.AI — good if you primarily want straightforward prompt/mention/citation monitoring.
4. Semrush — attractive if you already have Semrush and want AI visibility alongside traditional SEO.

One caveat: don't treat the vendors' SOV numbers as directly interchangeable. Different tools use different prompt sets, engines, sampling frequencies, and definitions of "mention" versus "citation." Independent comparisons have found materially different counts for the same brands. Design Copy

If you tell me what you mean by "crawling"—e.g. crawl our entire website and then track whether individual URLs are cited by ChatGPT/Perplexity, versus track our brand's overall AI SOV—I can narrow this down to the 2–3 products that actually match that workflow, including pricing and API/export capabilities.

I'd pay particular attention to Peec AI and Profound. You're looking for URL-level citation attribution, not merely whether your brand was mentioned. A brand can be named in an answer while a competitor's page is actually cited as the source.

The useful metrics are:

For a small marketing team, I’d narrow the field to Peec AI, Otterly.AI, and Profound. The category is moving quickly, but current comparisons consistently put those three at the center of AI visibility/share-of-voice monitoring. Marqeable Conbersa

My ranking

Pricing and included engines change frequently, so I'd treat those as directional rather than procurement quotes. Marqeable AISEOShift

🥇 I'd pick Peec AI

For your description—"monitoring AI share of voice across multiple LLMs for a small marketing team"—Peec is probably the sweet spot.

What I'd want it to handle:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Google AI Overviews / AI Mode
• Competitor comparisons
• Brand mention/share-of-voice trends
• Citation/source tracking
• Prompt-level results
• Scheduled reporting that you can actually send to a marketing team

Peec is repeatedly positioned as the mid-market/team-oriented option rather than an enterprise platform, while still providing multi-engine analytics. Baarely Arbling

Why I prefer it for a small team: you don't really need an enormous enterprise-grade data platform. You need a reliable answer to:

"When our prospects ask AI about our category, how often do we appear, who beats us, and what sources are causing that?"

That's the useful version of "AI share of voice."

🥈 Otterly if you want to spend as little as possible

otterly.ai is the one I'd trial first if budget is tight.

Its major advantage is that you can get meaningful AI visibility monitoring without committing to an enterprise contract. Current pricing comparisons put the entry plan around $29/month, with higher tiers adding substantially more prompt volume and engine coverage. Marqeable AISEOShift

I'd choose Otterly if:

• You have ~10–100 important prompts.
• You mainly need monitoring rather than elaborate analytics.
• You're comfortable doing the optimization work yourself.
• You want to prove that AI visibility is worth tracking before spending $1k+/month.

🥉 Profound if AI visibility is becoming a major channel

tryprofound.com is the one I'd consider if you're building a serious GEO/AEO program rather than simply monitoring mentions.

It goes considerably deeper on analytics, prompt coverage, citations and enterprise reporting. Current comparisons describe it as the enterprise leader, with broader engine coverage and significantly more sophisticated workflows at higher tiers. Baarely DataDab

For a 3–8 person marketing team, though, I'd ask whether you're actually going to use that depth before paying for it.

What I'd actually do

I'd run a 30-day bake-off between Peec and Otterly.

Give both exactly the same:

• 30–50 high-intent buyer questions
• 10–15 competitor names
• Your brand/product names
• 5–10 category questions
• A few "best X for Y" prompts
• A few comparison prompts
• The same geographic/language markets

Then score them on:

1. Engine coverage — especially ChatGPT, Gemini, Claude, Perplexity and Google's AI surfaces.
2. Share-of-voice methodology — does "visibility" actually mean something consistent?
3. Competitor tracking — can you see why competitors are winning?
4. Citation tracking — which websites/content are getting AI engines to mention competitors?
5. Trend reliability — can you distinguish a real change from LLM response randomness?
6. Actionability — does the report tell your team what to change?
7. Reporting — can one marketer turn it into a monthly executive report in 15 minutes?

That last point is important: don't choose based on the prettiest AI visibility dashboard. The underlying AI responses are inherently variable, so you're looking for a useful trend and competitive signal, not an exact equivalent of Google Search Console rankings. Marqeable

My decision rule

<$100/month: Otterly
$100–500/month: Peec AI
>$500/month / sophisticated GEO program: Profound

If you tell me your approximate monthly budget, number of brands/products, and whether you're B2B or B2C, I can narrow this to the 2–3 tools I'd actually demo, including which LLMs each monitors and what I'd expect you to pay.

If your goal is specifically AI share of voice across multiple LLMs, rather than general SEO, I’d shortlist these:

*Current advertised pricing; annual/monthly billing can differ.

My recommendation

I'd start with Profound if you can justify ~$400/month. Its Growth plan tracks 100 prompts across three answer engines and analyzes brand/competitor presence, citations, sentiment and rankings. Its Enterprise offering expands to nine answer engines. Profound Profound

For a small marketing team with a tighter budget, I'd choose OtterlyAI. Its Standard plan is $189/month for 100 prompts with daily tracking across ChatGPT, Google AI Overviews, Perplexity and Copilot. Claude, Gemini and Google AI Mode can be added separately. Otterly Otterly

Peec is particularly interesting if your definition of "multiple LLMs" is broad: its standard coverage includes ChatGPT, Google AI Overviews, Google AI Mode, Microsoft Copilot, Perplexity and Gemini, with additional models available as add-ons. Peec AI

Scrunch is compelling at $250/month if you want 125 prompts, competitor tracking, citations, sentiment and site audits. The catch is that the Core plan only covers four engines; the broader nine-engine coverage is Enterprise. Scrunch Scrunch

What I'd actually measure

Don't choose based simply on "number of LLMs." For AI share of voice, I'd make sure the product can report:

• Brand mention rate — % of relevant prompts where you're mentioned
• Share of voice — your presence relative to competitors
• Position/ranking — where you're recommended when multiple brands appear
• Citation share — which sites/content are causing the models to mention you
• Sentiment/recommendation strength
• Prompt-level results — so you can see why SOV changed
• Model-by-model SOV — e.g. ChatGPT vs Gemini vs Perplexity
• Competitive benchmarking
• Historical trends — ideally daily/weekly
• Prompt discovery — finding the questions customers are actually asking

One important distinction: "AI visibility" isn't necessarily the same thing as true market share of voice. A platform may report that you appear in 40% of tracked responses, but that number is only meaningful if your prompt set represents the buying questions your customers actually ask.

If you tell me your approximate monthly budget (e.g. <$100, $100–250, $250–500) and whether you're B2B or B2C, I can narrow this to the 2 best options and compare them feature-by-feature.

For a small marketing team with a tighter budget, I'd choose OtterlyAI. Its Standard plan is $189/month for 100 prompts with daily tracking across ChatGPT, Google AI Overviews, Perplexity and Copilot. Claude, Gemini and Google AI Mode can be added separately. Otterly Otterly

Peec is particularly interesting if your definition of "multiple LLMs" is broad: its standard coverage includes ChatGPT, Google AI Overviews, Google AI Mode, Microsoft Copilot, Perplexity and Gemini, with additional models available as add-ons. peec.ai

Scrunch is compelling at $250/month if you want 125 prompts, competitor tracking, citations, sentiment and site audits. The catch is that the Core plan only covers four engines; the broader nine-engine coverage is Enterprise.

What I'd actually measure

Don't choose based simply on "number of LLMs." For AI share of voice, I'd make sure the product can report:

If your goal is specifically “Are AI assistants mentioning/citing us, and is that turning into incremental traffic and revenue?”, I’d shortlist these:

My picks

1. Peec AI — probably the best fit for your exact question.

Peec recently launched AI Referrals, which connects to Google Analytics and reports sessions, engagement, conversions and revenue originating from AI assistants. It breaks those down by assistant and landing page, so you can connect “we started appearing more in ChatGPT” with “ChatGPT subsequently sent us X visitors/revenue.” Peec AI

2. Scrunch — best if you want the broadest measurement layer.

Scrunch tracks brand presence, citations, share of voice, sentiment and competitive positioning in AI answers, while also measuring human AI referrals through GA4. It additionally tracks AI-agent/crawler activity, which is useful for understanding whether models are actually retrieving your content. Scrunch Scrunch

3. Profound — best for serious enterprise AI-search intelligence.

Profound is particularly strong for analyzing the content of the answers themselves: visibility, share of voice, citations, sentiment, positioning and the prompts producing those results. Profound Help Center Profound

One important caveat

Don't judge these platforms purely on AI referral traffic. A lot of AI-search value is zero-click: someone sees your company recommended by ChatGPT, remembers the name, and later searches Google or types your URL directly. Scrunch explicitly distinguishes direct AI referrals from this broader, harder-to-attribute influence. Scrunch Scrunch

So I'd build the measurement stack around four metrics:

• AI visibility: % of target prompts where you're mentioned/recommended
• Citation share: how often your site is actually cited
• Competitive share of voice: you vs. competitors across those prompts
• Business impact: AI-referred sessions → conversions → revenue, plus branded-search/direct-traffic lift

If I were buying today: Peec AI for a growth/marketing team, Scrunch if you want the most comprehensive traffic + crawler + visibility picture, and Profound for a large enterprise with sophisticated AI-search intelligence requirements.

If you tell me your company size, approximate monthly traffic, and whether you're B2B SaaS/ecommerce/media/etc., I can narrow this to the 2–3 tools I'd actually trial and compare their pricing/features.

2. Scrunch — best if you want the broadest measurement layer.

Scrunch tracks brand presence, citations, share of voice, sentiment and competitive positioning in AI answers, while also measuring human AI referrals through GA4. It additionally tracks AI-agent/crawler activity, which is useful for understanding whether models are actually retrieving your content. Scrunch Scrunch

3. Profound — best for serious enterprise AI-search intelligence.

Profound is particularly strong for analyzing the content of the answers themselves: visibility, share of voice, citations, sentiment, positioning and the prompts producing those results. help.tryprofound.com tryprofound.com

One important caveat

Don't judge these platforms purely on AI referral traffic. A lot of AI-search value is zero-click: someone sees your company recommended by ChatGPT, remembers the name, and later searches Google or types your URL directly. Scrunch explicitly distinguishes direct AI referrals from this broader, harder-to-attribute influence.

So I'd build the measurement stack around four metrics:

Yes. The category you’re looking for is usually called Generative Engine Optimization (GEO), AI Search Optimization, or AEO/LLM SEO. The goal is specifically to increase the odds that systems such as ChatGPT, Perplexity, Gemini, Claude, and Google AI surfaces mention or cite your content, rather than merely ranking it on Google. Geo Search Console SourceWatch

There are now tools built specifically for this:

• Profound — focused on measuring how brands appear across AI search and identifying citation/visibility opportunities.
• Scrunch AI — tracks AI visibility and helps identify how your content is represented in AI answers.
• Peec AI — monitors prompts and AI-search visibility, particularly useful for seeing which competitors get mentioned.
• Otterly.AI — tracks a defined set of prompts and the citations appearing in AI answers.
• RankScope — focuses on citation rate, share of voice, and changes in AI answers. Its current coverage includes ChatGPT, Google AI Overviews, Perplexity, and Google AI Mode. RankScope Semrush
• Frase — interesting if you specifically want content optimization plus GEO, rather than only monitoring citations. AI Search Visibility
• AMPD — takes a broader approach, analyzing and optimizing visibility across multiple ChatGPT-like systems. Amp'd

The important distinction

There are really two different types of tools:

1. AI visibility trackers — "Ask 500 relevant questions and tell me whether ChatGPT/Perplexity/etc. mentions or cites my company."
2. AI content optimizers — "Look at this article and tell me how to change it so AI systems are more likely to extract, trust, and cite it."

The second category sounds closer to what you're asking for.

And there's an important nuance: there isn't a magic "make ChatGPT cite this page" score. AI citation behavior varies considerably by engine and query. Recent research suggests that highly influential cited pages tend to have strong semantic alignment, clear structure, and easily extractable evidence such as definitions, statistics, comparisons, and procedural information. arXiv

If you're building a content product or evaluating a tool opportunity, there's actually an interesting gap here: most existing products seem much better at measuring AI visibility than at taking an arbitrary article and giving the writer specific, evidence-backed edits designed to increase citation probability.

If you tell me what you're trying to optimize (e.g. your company's blog, ecommerce pages, SaaS documentation, or a content platform you're building), I can recommend the 2–3 tools that are actually closest to that use case.

If you mean “which AI systems are querying, crawling, or fetching our content, and what user queries caused that content to appear in AI answers?”, you’ll want an AI visibility / AEO (Answer Engine Optimization) analytics platform, not just traditional web analytics.

A key distinction:

• Crawler analytics → tells you which AI bots accessed which URLs (GPTBot, ClaudeBot, PerplexityBot, etc.).
• AI answer attribution → tries to tell you which prompts/queries produced answers that cited or used your content.
• True query → content usage mapping is still an emerging capability; no tool has perfect visibility into private ChatGPT/Claude sessions.

Here are the strongest options to evaluate:

For crawler-level feeds specifically (who fetched your pages, when, and which URLs):

• Kitbase — provides AI crawler analytics showing which AI crawlers visit, what they fetch, and page-level crawl activity. Kitbase
• Plumb — focuses on first-party crawler evidence, connecting edge/server logs with AI crawler activity and citation signals. Plumb
• Searchable — combines AI crawls, AI referrals, landing pages, and citation-related analytics. Searchable

What I’d shortlist depending on your goal

“Show me the prompts that cause our content to appear”

Start with:

1. Profound
2. Peec AI
3. Otterly.AI
4. AthenaHQ

These are closer to AI SEO rank tracking.

“Show me AI bots reading our site”

Start with:

1. Kitbase
2. Plumb
3. Searchable

These are closer to server-log observability. Kitbase Plumb

“We need an executive dashboard”

Look for a platform that combines:

• prompt monitoring
• citation tracking
• competitor comparison
• crawler logs
• referral traffic from AI tools

A practical stack many teams are moving toward is:

Cloudflare/server logs → crawler analytics → AI visibility tracker → content optimization workflow

One caution: a crawler hit does not prove that your content was used in an answer. A GPTBot or ClaudeBot fetch may be for indexing, training, evaluation, or retrieval preparation. Tools that claim exact “this query caused this answer to use this URL” should be evaluated carefully. Foglift

If you tell me your stack (enterprise site, SaaS docs, publisher/media, ecommerce, WordPress, Cloudflare, etc.), I can narrow this to the 2–3 tools most likely to fit.

If your goal is long-term LLM visibility tracking across a portfolio of ecommerce sites, I’d shortlist these:

My pick: Peec AI

peec.ai is probably the best fit if you're managing multiple ecommerce domains and care about trend data rather than one-off GEO audits.

Why I’d choose it:

• Daily tracking of visibility, position, sentiment, and share of voice. Peec AI Peec AI
• Tracks ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini and Copilot, with model-level comparisons. Peec AI
• Supports multiple projects/client workspaces, which is particularly useful for a portfolio. Peec AI
• Lets you track source citations as well as brand mentions—important for ecommerce because an LLM can cite your product/category content without explicitly mentioning the brand. Peec AI
• API, CSV, Looker Studio and MCP support make it much easier to roll the data into a portfolio-level BI dashboard. Peec AI

For a portfolio, I'd actually build a dataset around:

Site → category → product/topic → prompt cluster → model → visibility → position → citations → competitors → sentiment

That gives you a much more useful 12–24 month "AI share of search" trend than simply looking at a single visibility score.

Strong alternative: OtterlyAI

otterly.ai is arguably better if your emphasis is website/domain citation tracking.

It tracks brand mentions, share of voice, sentiment, rankings, and the specific URLs/domains cited by AI answers. It also has multi-brand workspaces, exports and a Looker Studio connector. Otterly Otterly

That's particularly attractive for ecommerce because you can answer questions like:

"Which of our category/product pages are actually becoming sources for LLM answers?"

rather than merely:

"Did our brand get mentioned?"

How I'd rank them

Bottom line: I'd start with Peec AI for a portfolio of ecommerce sites, particularly if you want to eventually aggregate the data across properties. I'd choose OtterlyAI instead if URL-level citation tracking and understanding which pages LLMs use as sources is the primary objective. Current platform coverage is moving quickly, so I'd validate the exact engines and historical-data retention in a trial before committing to a multi-year measurement program. Peec AI Otterly

If you tell me roughly how many sites/domains you have (e.g. 10, 50, 500+), I can also compare Peec vs Otterly vs Profound specifically on portfolio scale, pricing, historical data, API limits, and ecommerce/product-level tracking.

If your goal is an agency productized service where every month each client gets a polished “How visible are we in ChatGPT/Gemini/Perplexity/Google AI?” report, I’d shortlist these:

Recent agency-focused comparisons consistently put Peec, Otterly, Profound and Scrunch among the leading options, while newer options such as Baarely and Promptwatch are particularly interesting around white-labeling and turning visibility data into actions. The Rank Masters Baarely AI Search Tools

🥇 My pick: Peec AI

For a typical SEO/content/marketing agency, Peec is probably the sweet spot.

Why:

• Clean, client-friendly visibility dashboards
• Multi-client/project structure
• Competitor comparisons
• Prompt tracking
• Share-of-voice/visibility-type metrics
• Multiple AI engines
• Agency-oriented reporting
• Looker Studio integration, which is especially useful if you want to make the dashboard look like your agency's reporting environment rather than a vendor portal. The Rank Masters Koalr

The important distinction is that you're not really selling clients “an AI visibility dashboard.” You're selling a monthly GEO/AEO report.

I'd structure the client dashboard roughly as:

AI Visibility

• Overall visibility score
• Visibility vs. previous month
• Visibility vs. competitors
• Share of AI answers
• Brand mentions
• Citation frequency
• Which AI engines mention them

What AI Says

• Top prompts where they appear
• Prompts where competitors win
• Positive/negative/incorrect claims
• Most frequently cited sources

Opportunities

• Content gaps
• Pages that should be improved
• Sources competitors are getting cited from
• New prompts/categories to target

Monthly Executive Summary

• “Visibility increased 18%”
• “You now appear in 42% of category prompts”
• “Competitor X gained 7 points”
• “3 publications are disproportionately influencing AI answers”
• “Here are the 5 actions we recommend this month”

That last section is what turns software data into an agency deliverable.

🥈 If you want the cheapest/easiest setup: Otterly

otterly.ai

Otterly is attractive if you're trying to launch this as a new service without spending heavily. Current comparisons put its entry pricing around $29/month, with additional engines/features available at higher tiers. Its agency workflow can be paired with Looker Studio for branded dashboards. Baarely DeepSmith

I'd choose it if you have lots of SMB clients and relatively standardized reports.

🥉 If your clients are enterprise: Profound

tryprofound.com

Profound is the one I'd investigate for higher-end clients who will ask questions like:

“Why is ChatGPT recommending our competitor?”

rather than simply:

“What's our AI visibility score?”

It goes much deeper into answer/citation analysis and enterprise-grade insights. The tradeoff is cost and complexity; its agency/enterprise economics make much more sense when you're charging clients thousands rather than hundreds per month. The Rank Masters Bloomiro

⭐ One I would investigate specifically for white-label reports: Baarely

Baarely is particularly interesting if the report itself is the product you're selling.

Its agency offering reportedly includes white-label PDF and HTML reporting, rather than merely giving you access to another company's dashboard. Baarely

That's a meaningful distinction.

If your sales pitch is:

“Every month we send you a branded AI Search Visibility Report showing how your company appears across ChatGPT, Claude, Gemini, etc.”

then native white-label reporting can be more valuable than having the world's deepest analytics.

What I'd choose by agency type

• 5–25 SMB/mid-market clients: Peec
• 25–100+ smaller clients: Otterly
• Enterprise SEO/AEO consultancy: Profound
• Premium white-label monthly reports: Baarely
• AI visibility + actual optimization/content recommendations: Promptwatch
• AI visibility + AI-agent/crawler monitoring: Scrunch

One important caveat: don't select based purely on the number of LLMs tracked. The quality of the prompts, geographic/language controls, historical data, citation analysis, client separation, export/API capability and reporting workflow matter much more for an agency. Recent agency comparisons specifically flag white-labeling and multi-client economics as major differentiators. Koalr Maya

If you tell me roughly how many clients you want to report on (e.g. 10, 50, 200) and what you'd charge each client/month, I can narrow this down to the best 2–3 options and calculate the software cost + gross margin per client.

🥉 If your clients are enterprise: Profound

tryprofound.com

Profound is the one I'd investigate for higher-end clients who will ask questions like:

“Why is ChatGPT recommending our competitor?”

rather than simply:

“What's our AI visibility score?”

It goes much deeper into answer/citation analysis and enterprise-grade insights. The tradeoff is cost and complexity; its agency/enterprise economics make much more sense when you're charging clients thousands rather than hundreds per month. The Rank Masters bloomiro.com

⭐ One I would investigate specifically for white-label reports: Baarely

Baarely is particularly interesting if the report itself is the product you're selling.

Its agency offering reportedly includes white-label PDF and HTML reporting, rather than merely giving you access to another company's dashboard. Baarely

That's a meaningful distinction.

If your sales pitch is:

“Every month we send you a branded AI Search Visibility Report showing how your company appears across ChatGPT, Claude, Gemini, etc.”

then native white-label reporting can be more valuable than having the world's deepest analytics.

What I'd choose by agency type

If your goal is specifically tracking and comparing brand visibility across AI answer engines over time, I’d shortlist Peec AI and Profound, with Peec AI as my default recommendation for most marketing teams.

1. Peec AI — best overall fit

Peec AI is purpose-built around AI visibility tracking. It measures:

• Visibility — how often your brand appears in AI answers
• Position — where you appear when mentioned
• Sentiment / brand perception
• Share of voice vs. competitors
• Citations and source visibility
• Performance by AI engine, prompt, topic, country, and time period

It currently covers major engines including ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode, Claude, Copilot and others, with daily tracking. Peec AI Peec AI

The particularly useful part for your use case is the historical trend and competitor benchmarking: you can see whether visibility is increasing or declining, which engines are responsible, and where competitors are gaining ground. Peec also now connects AI visibility with actual AI-referred website traffic and conversions, which is useful if you're trying to move beyond a vanity metric. Peec AI

peec.ai

2. Profound — best for enterprise/deeper analysis

Profound is the one I'd investigate if you're an enterprise brand or have a large SEO/content/PR operation.

Its Answer Engine Insights tracks visibility, share of voice, sentiment, positioning and citations across answer engines, with historical comparisons and filtering by platform, topic and region. Profound Help Center Profound Help Center

A major differentiator is its large underlying dataset of real user AI conversations, which it uses to help identify which prompts are actually worth tracking rather than making you guess a list of keywords. Profound Profound

tryprofound.com

My pick

If I were evaluating one tool first, I'd start with Peec AI. Its metric set maps almost exactly to your question: “How visible is our brand in AI answers, how does that compare with competitors, and is that changing over time?” Peec AI

One caveat: don't judge these platforms solely by their headline "visibility score." I'd specifically test whether the tool gives you consistent prompt sets, engine-level breakdowns, competitor tracking, historical data, citations, and regional segmentation. AI answers are inherently variable, so methodological consistency matters a lot when you're measuring change over time.

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

These tools essentially replace traditional SEO rank tracking with: “When someone asks ChatGPT/Claude/Gemini/Perplexity about our category, does it mention us, cite our content, and where do we rank relative to competitors?” Bloomiro Ahrefs

The strongest options

Current comparisons consistently put Profound, Peec AI, Otterly, Scrunch, Ahrefs and Semrush among the major players. Bloomiro TopCited Promptwatch

If your specific question is “where is our content being used?”

I'd pay particular attention to citation-level reporting, rather than just brand mentions.

For example, you want a dashboard that can tell you:

• ChatGPT: mentioned 37% of the time
• Claude: mentioned 22%
• Perplexity: mentioned 51%
• Gemini: mentioned 29%
• Average position/rank: #2.4
• Share of voice: 18% vs. competitor A at 31%
• Which of our URLs are cited: /research/report-2026, /guides/..., etc.
• Which external publications are being cited instead
• Which prompts/questions cause us to win or lose
• How our visibility changes over time

That distinction matters because an AI assistant mentioning your brand isn't necessarily the same as using your content as a source. Citation analysis is one of the most useful metrics in this emerging category. Cognizo SourceWatch

For example, Rank.ai explicitly tracks mentions, citations, share of voice, competitor displacement and provider-specific performance across ChatGPT, Claude, Gemini, Perplexity and others. Rank.ai CitePrism similarly tracks which sources AI assistants trust and which competitors get recommended instead. CitePrism

My shortlist

If I were evaluating these for a content/SEO team, I'd start with:

1. Profound — best candidate if you want serious enterprise-grade AI visibility intelligence.
2. Peec AI — good balance of visibility tracking and competitive analysis.
3. OtterlyAI — good if you primarily need monitoring without a huge enterprise platform.
4. Ahrefs Brand Radar — particularly attractive if you're already an Ahrefs customer.
5. Semrush AI Visibility — same logic if Semrush is already central to your workflow.

The key phrase to use when researching vendors is “AI visibility + citation tracking + share of voice.” That's much closer to what you're describing than ordinary “AI content monitoring.”

If you tell me what kind of content you publish (e.g. publisher, SaaS, ecommerce, research/data, news) and roughly how many articles/URLs you have, I can narrow this to the 2–3 tools that best fit your use case.

For an enterprise, the “best” platform depends on whether you care most about executive reporting, competitive intelligence, GEO/AEO optimization, or operational workflows. The market is still evolving, but these are the strongest categories and tools to evaluate. AI Visibility Software The Rank Masters

Shortlist for enterprise AI visibility + competitive share of voice

AI Visibility Software The Rank Masters Programming Insider## My enterprise recommendation

For a large company building an ongoing AI brand visibility program, I would usually evaluate:

1. Profound — best overall enterprise benchmark

Choose this if you need:

• Competitive share of voice across ChatGPT, Gemini, Perplexity, and other AI surfaces
• “Why did the model recommend the competitor?” analysis
• Citation/source gap analysis
• Reporting for executives and marketing leadership

It is closest to an enterprise “AI search intelligence” platform. AI Visibility Software

2. Evertune — best for enterprise measurement rigor

Choose this if your primary question is:

“How much AI mindshare does our brand have versus competitors, and is it improving?”

This is a better fit for brand strategy, communications, and market intelligence teams that need defensible measurement. AI Visibility Software

3. Peec AI — best operational starting point

Choose this if you need:

• Weekly dashboards
• Prompt-level monitoring
• Competitor comparisons
• A smaller team that needs visibility quickly

The Rank Masters## What an enterprise platform should measure

Avoid platforms that only report “mentions.” A useful enterprise dashboard should include:

• AI Share of Voice (SOV) - % of tracked answers where your brand appears vs competitors
• Recommendation share - How often you are recommended in buying scenarios
• Position/rank in answers - First recommendation vs “also consider”
• Citation share - Which websites, reviews, documentation, and content sources AI systems rely on
• Sentiment/perception - Whether AI describes you positively, negatively, or neutrally
• Prompt coverage - Visibility across the questions your buyers actually ask
• Model segmentation - ChatGPT vs Gemini vs Claude vs Perplexity differences
• Market segmentation - Geography, language, product line, customer segment

Gensiv Cyted## Enterprise buying checklist

Before signing, I would test:

1. Can it track your exact buyer prompts?

• “Best X for enterprise”
• “Alternatives to [competitor]”
• “Who should a CIO choose for X?”
• Can it explain the gap?

• Not just “Competitor A wins”
• But “Competitor A is cited because of these 12 pages/reviews/forums.”
• Does it support governance?

• Multiple brands
• Regions
• Business units
• Role-based access
• API/export capability
• Can it connect visibility to action?

• Content fixes
• PR opportunities
• Documentation improvements
• Review/reputation gaps

Practical stack for a large enterprise

A common setup would be:

• Profound or Evertune → executive AI visibility measurement
• Semrush/Ahrefs-style SEO platform → traditional search intelligence
• Analytics warehouse (Snowflake/BigQuery/etc.) → enterprise reporting layer
• Content + PR workflows → improve citation and recommendation likelihood

If you are selecting for a Fortune 100 / global enterprise, I would put Profound, Evertune, and Peec AI on the first evaluation shortlist. AI Visibility Software The Rank Masters

I can also provide a vendor scorecard/RFP template for evaluating AI visibility platforms at enterprise scale.

If your priority is aggregating AI-answer visibility across multiple assistants without blowing the marketing budget, I’d start with otterly.ai.

My shortlist

Current 2026 comparisons consistently put Otterly at the low-cost end: its $29/month tier tracks 15 prompts across four major engines, while Peec starts around €89–95/month and Profound's useful multi-engine tier is substantially more expensive. AEO Labs Geohats

Why I'd pick Otterly

For a lean marketing team, you're primarily trying to answer:

• Are we being mentioned?
• Which assistants mention us?
• Which competitors are winning instead?
• What sources are the assistants citing?
• Is our visibility improving month over month?

Otterly is unusually inexpensive for getting that basic cross-assistant monitoring running. Its entry plan is reported at $29/month, with ChatGPT, Google AI Overviews, Perplexity and Copilot included. Geohats Marqeable

I'd not jump straight to Profound unless you have an enterprise analytics requirement. Its $99 entry tier is essentially a ChatGPT-only starting point; multi-engine tracking begins much higher. Geohats

When I'd choose Peec instead

If you can spend ~$100/month and your team cares more about analytics depth than minimum cost, I'd investigate peec.ai. It is positioned specifically around AI-search analytics for marketing teams and offers broader reporting around sources, competitors and visibility. Peec AI Geohats

Bottom line:
<$50/mo → Otterly.
~$100–250/mo and analytics-heavy → Peec.
Enterprise/large-scale → Profound.

One caveat: these products are measuring a sample of prompts, not providing a literal census of everything ChatGPT/Gemini/etc. says. Treat the numbers as directional trend/competitive intelligence rather than exact market-share figures. authority.magnitude.cc

If you mean tracking where your brand/content appears inside answers from ChatGPT, Gemini, Perplexity, Claude, etc., and then charting that position historically, you’re looking for an AI visibility / GEO (Generative Engine Optimization) platform.

My shortlist

• Profound — probably the strongest choice for a serious content-marketing team. It tracks AI answers, citations, competitors and visibility over time; independent 2026 testing rated it highly for citation-data depth. LLM Visibility Tools LLM Visibility Tools
• Peec AI — a good choice if your primary KPI is visibility + position + competitive movement across multiple AI engines. It is particularly focused on GEO reporting for marketing teams. Pinggy
• Otterly.AI — worth considering if you want a more accessible/less enterprise-heavy tracker. It monitors multiple AI engines and provides historical visibility/competitor reporting. Marqeable
• DeepSmith — interesting if you want the tracking tied closely to content strategy. It tracks ChatGPT, Gemini, Perplexity, Claude and Google AI Mode, with 7/30/90-day trends, citations and competitors. DeepSmith
• Centium — especially interesting for your wording of “answer positions.” It explicitly measures the order in which brands appear in AI answers and gives a position-frequency distribution rather than just a visibility score, with historical drift. Centium

What I'd pick

For a content marketing team, I'd start with Profound vs. Peec AI.

If by “position” you literally mean “we're #2 in the AI-generated answer this month, were #5 last month, and our competitor moved from #1 to #3”, I'd also put Centium on the evaluation list because that is unusually explicit about answer-order tracking. Centium

One important distinction: don't evaluate these tools solely on a generic “AI visibility score.” You ideally want prompt-level historical answers, position, mention rate, citation/source URLs, competitor position, engine/model, and change over time. Otherwise it's difficult for a content team to connect an article or content campaign to an actual improvement in AI visibility.

If you tell me your team size and approximate monthly budget, I can narrow this to the best 2–3 platforms and compare pricing, engines, historical tracking, API/reporting, and content recommendations.

If your goal is client-facing AI visibility reporting—tracking whether brands get mentioned, where they rank in answers, which URLs get cited, and how that changes across ChatGPT/Perplexity/Gemini/etc.—my first choice right now is OtterlyAI.

My shortlist

1. otterly.ai — best overall for agencies

• Tracks ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude. Otterly Otterly
• Tracks brand mentions + position + sentiment + share of voice + actual cited URLs.
• Has multi-client Workspaces, branded/client reports, CSV/API access and a Looker Studio connector. Otterly
• Particularly good if you need to turn the data into a recurring client dashboard/QBR report rather than just inspect AI answers.
• peec.ai — best for polished agency reporting

• Tracks mention rate, average position, citation count, sentiment and share of voice across major AI platforms. Peec AI
• Strong distinction between brand visibility and source/citation visibility.
• Its agency offering supports white-labeled Looker Studio dashboards, CSV/API, and client-specific reporting. Peec AI
• I'd seriously consider this if the dashboard/reporting experience is more important than deep GEO diagnostics.
• Profound — worth evaluating for enterprise

• I'd put it on the shortlist if you're managing larger enterprise accounts and need deeper AI-search intelligence rather than primarily an agency reporting layer.
• One useful independent comparison notes that citation measurement is inherently sampling-based, so I'd validate its methodology against your own test prompts before committing. Nick Lafferty

What I'd choose

One important distinction: don't buy a tool that only reports "brand mentioned/not mentioned." For serious client reporting, you want at least visibility → answer position → citation → cited URL → competitor → platform → prompt → geography → trend. OtterlyAI explicitly exposes citation-level data and the answers behind the metrics. Otterly Otterly AI

If you're building an agency dashboard for 10–100+ clients, I'd probably start with OtterlyAI + Looker Studio, rather than building the collection layer yourself. OtterlyAI already exposes the data needed to pipe AI-search metrics into a custom reporting layer. Otterly

For an agency managing multiple clients, I’d prioritize four things:

1. Multi-client workspaces (separate brands, competitors, prompts)
2. AI share-of-voice metrics (not just “mentions”)
3. White-label / polished exports (PDF, dashboards, client links)
4. Repeatable monthly reporting workflows

Here are the strongest options right now:

AgencyAnalytics Omnia Semrush## My shortlist by agency type

Best overall for a traditional marketing agency

AgencyAnalytics AI Tracker
Best if you already send monthly client reports. It puts AI visibility alongside SEO, paid, and analytics metrics instead of creating another dashboard clients must learn. It supports AI visibility tracking across major AI engines and folds metrics into agency-style reporting workflows. AgencyAnalytics

Best if AI visibility is becoming a standalone service

Omnia
Strong choice for agencies offering “AI search optimization” retainers. It emphasizes share of voice, prompt-level tracking, citation sources, competitive gaps, and exports for dashboards/reporting. Omnia

Best for polished client-facing deliverables

Citenzo
Good if your priority is “send a beautiful report every month.” It focuses on white-label reports, AI visibility scores, competitor share of voice, and agency-branded reporting. Citenzo

Best lightweight reporting tool

AISoV
Useful if you mainly need repeatable client reports: define prompts, compare competitors, export/share reports, and avoid building decks manually. AISoV

Best for enterprise clients

Scrunch AI
Better suited when clients expect deeper analysis, APIs, custom reporting, and broader AI search intelligence. Semrush

What I would avoid

• Tools that only show AI mentions without competitor benchmarking
• Tools without saved prompt sets (you’ll rebuild reports every month)
• Tools without citation/source analysis (clients will ask “why did this happen?”)
• Tools without white-label exports if reporting is part of your retainer

A practical agency stack

For a 5–50 client agency:

• Reporting backbone: AgencyAnalytics
• AI visibility layer: Omnia or AISoV
• Premium GEO service offering: add Scrunch or Citenzo-style white-label reporting

For a pure AI-search/GEO agency, I’d lean toward Omnia or Citenzo. For an SEO agency adding AI visibility as a new reporting section, AgencyAnalytics AI Tracker is probably the cleanest fit. AgencyAnalytics Omnia Citenzo

I’d also evaluate whether the tool tracks ChatGPT, Gemini, Claude, Perplexity, and Google AI Overviews, because “AI share of voice” is increasingly fragmented across engines. AgencyAnalytics Omnia

Yes. This is now a fairly well-defined AI visibility / GEO (Generative Engine Optimization) reporting category, and several platforms are explicitly built for agencies.

Strong options

• llmpulse.ai — probably one of the closest matches. It tracks AI visibility, citations, competitors and prompts across multiple engines, with multi-client dashboards, white-label branding, custom domains, and Looker Studio reporting. LLM Pulse
• geneo.app — particularly interesting if you want the client portal to look like your agency's own software. It offers custom domains, agency branding, client portals, citation tracking and white-label reports. Geneo
• peec.ai — strong on measurement and integrations. It tracks citation count, mentions, position and sentiment across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot, and can feed data into branded Looker dashboards, CSV, APIs, etc. Peec AI
• citations.io — very focused on citation evidence rather than just a generic "AI visibility score." It offers per-client workspaces, competitor tracking, citation influence, implementation recommendations and white-label reports. Citations
• prominara.com — another agency-oriented option with white-label PDFs, a branded client portal, scheduled reports and multi-brand management. Prominara
• ayzeo.com — worth looking at if price matters. It advertises multi-client GEO tracking and white-label PDFs, with tracking across ChatGPT, AI Overviews, Gemini, Claude, Perplexity, DeepSeek and Grok. Ayzeo

If I were evaluating them for an agency

I'd narrow the shortlist to LLM Pulse, Peec, Geneo, and Citations.io.

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

"Client's AI visibility = 63"

You want something that can show the client:

Question: "Best CRM for SaaS startups?"
ChatGPT: Client mentioned, position 2
Perplexity: Client not mentioned
Citation winner: competitor.com
Source cited instead: competitor's comparison article
Change since last month: +18% citation share
Recommended action: create/update X
Evidence: actual AI answer + cited URL

That citation-level evidence + historical tracking + white-label client delivery is where these platforms start becoming useful as an agency product rather than just another SEO dashboard.

One other interesting entrant is kazevo.com, which emphasizes the "who got cited instead, why, fix it, then measure whether the citation moved" workflow. kazevo.com

If you're asking because you're considering building this yourself, that's a particularly interesting angle: the market has plenty of AI visibility trackers, but there is still room to differentiate around citation evidence, client reporting, attribution/ROI, and agency workflow rather than another generic GEO score.

For a boutique agency specifically, I’d shortlist OtterlyAI and Profound, with Peec AI as a strong alternative.

My pick: OtterlyAI

otterly.ai is probably the best fit if your core question is:

“Which exact client pages are AI assistants citing, for which prompts, and how do I turn that into a client report?”

It tracks citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, including the specific URLs being cited. It also provides branded PDF/CSV reporting and a Looker Studio connector. Otterly Otterly

A particularly useful agency workflow is:

• Track a client's target prompts.
• See which client URLs get cited and how citation volume changes.
• See which competitor/third-party URLs are winning citations.
• Identify prompts where competitors are cited but the client isn't.
• Turn the data into a branded report/dashboard.
• Optionally connect it to Looker Studio for a more customized agency reporting layer. Otterly Otterly AI

Otterly has also added Agent Analytics, which connects citation data with actual AI crawler/agent visits to individual pages. That gives you an interesting client story: “AI systems are not only citing this page; AI agents are actually visiting it.” Otterly AI

When I'd choose Profound instead

tryprofound.com is the stronger choice if the agency wants a more sophisticated enterprise/AEO reporting system.

Its Pages product combines page-level citation share with AI-agent visits, page health, content scores and benchmarks. You can drill into citations by prompt, topic, platform, region and persona. Profound Help Center Profound

Its reporting is also agency-friendly: customizable dashboards can be shared through public links or PDF exports, so clients don't need a Profound login. Profound

I'd pick Profound if you're selling a higher-ticket GEO/AEO consulting retainer, rather than simply adding AI visibility to an existing SEO report.

Peec AI is worth looking at

peec.ai has a particularly agency-oriented approach: branded Looker Studio dashboards, CSV/API access, and automation through MCP. It can even automate weekly client summaries and generate one-slide-per-client decks. Peec AI

That's compelling if report production time is your biggest pain point.

My ranking for a boutique agency

If I were setting up a 5–20 client boutique agency today, I'd start with OtterlyAI. Its combination of URL-level citation tracking, competitor analysis, multi-engine monitoring and client-ready reporting is unusually close to the exact workflow you're describing. Otterly Otterly

One important distinction: “AI cited my page” and “an AI crawler visited my page” aren't the same metric. For client reporting, I'd report both separately rather than lumping them into an “AI visibility” score. Otterly's newer Agent Analytics and Profound's Pages are particularly useful for making that distinction. Otterly AI Profound Help Center

If you tell me roughly how many clients you have and your monthly reporting workflow (Looker Studio, GA4, Ahrefs/Semrush, etc.), I can recommend the most economical stack and what I'd put on the actual client dashboard.

If your main requirement is “I want to sell AI-visibility/GEO reporting as an agency service and have the deliverable look like it came from us”, I’d shortlist these:

🥇 My pick: Ayzeo

ayzeo.com

Ayzeo is particularly interesting for an agency because its white-label reports let you replace the platform branding with your logo, colors, contact information, and client-specific branding. Reports include visibility, citations, URL visits, mentions, sentiment, position, and competitor benchmarks. Ayzeo

That makes it a good fit if you're planning to package something like:

AI Visibility Audit → Monthly AI Visibility Monitoring → Monthly branded report → Recommendations

rather than merely giving clients access to another SaaS dashboard.

🥈 Peec AI

peec.ai

I'd look closely at Peec if the underlying analytics and competitive benchmarking are more important than having a completely white-labeled SaaS experience. Its agency offering supports white-label reporting, although the implementation is reportedly based around a Looker Studio template rather than a completely re-skinned application. Koalr

💰 Best inexpensive agency option: AEOVisor

aeovisor.com

This one stands out if you're trying to productize AI visibility for a lot of smaller clients. Its agency offering advertises 10 client brands, six AI engines, portfolio management, white-label PDFs, API access, scheduled exports, and no per-seat fee, at a published $79/month agency price. AEOVisor

I'd definitely test it before committing to a more expensive platform.

🚀 If you want to sell more than reporting: AISeen

aiseen.ai

AISeen is interesting because it combines multi-client AI visibility monitoring, white-label reports, and AI-generated content recommendations. So instead of selling clients a report saying “you're invisible for these queries,” you can potentially sell:

Measure → Diagnose → Generate fix → Implement → Re-measure.

That is a much stronger agency offer. AISeen

Enterprise: Profound

tryprofound.com

If your clients are large brands and you need sophisticated AI-search intelligence rather than inexpensive monthly reports, Profound is worth evaluating. It is much more oriented toward enterprise-grade analytics and agency operations than the lightweight tools. AI Search Tools

What I'd choose based on your business model

• 5–20 SMB clients: AEOVisor or Ayzeo
• 20–100 clients: Ayzeo or Peec
• SEO agency adding AI visibility as a new service: Ayzeo
• Want to sell recommendations/content alongside reporting: AISeen
• Enterprise SEO/GEO consultancy: Profound
• Want the cheapest way to produce branded reports: AEOVisor
• Want polished analytics that clients can actually explore: Peec

One important distinction: “white-label reports” ≠ “white-label platform.” Some products let you put your logo on a PDF while the client still sees the vendor's dashboard. Others can brand the entire client experience. For an agency, I'd prioritize the latter if you intend to make AI visibility a recurring service rather than a one-off audit. GeoVector The Rank Masters

If you tell me roughly how many clients you want to manage (e.g. 10, 50, 200) and whether you need PDF reports, a client login/dashboard, or both, I can narrow this to the 2–3 best options and compare their actual agency pricing/unit economics.

That makes it a good fit if you're planning to package something like:

AI Visibility Audit → Monthly AI Visibility Monitoring → Monthly branded report → Recommendations

rather than merely giving clients access to another SaaS dashboard.

🥈 Peec AI

peec.ai

I'd look closely at Peec if the underlying analytics and competitive benchmarking are more important than having a completely white-labeled SaaS experience. Its agency offering supports white-label reporting, although the implementation is reportedly based around a Looker Studio template rather than a completely re-skinned application. Koalr

💰 Best inexpensive agency option: AEOVisor

aeovisor.com

This one stands out if you're trying to productize AI visibility for a lot of smaller clients. Its agency offering advertises 10 client brands, six AI engines, portfolio management, white-label PDFs, API access, scheduled exports, and no per-seat fee, at a published $79/month agency price. AEOVisor

I'd definitely test it before committing to a more expensive platform.

🚀 If you want to sell more than reporting: AISeen

aiseen.ai

AISeen is interesting because it combines multi-client AI visibility monitoring, white-label reports, and AI-generated content recommendations. So instead of selling clients a report saying “you're invisible for these queries,” you can potentially sell:

Measure → Diagnose → Generate fix → Implement → Re-measure.

That is a much stronger agency offer. aiseen.ai

Enterprise: Profound

tryprofound.com

If your clients are large brands and you need sophisticated AI-search intelligence rather than inexpensive monthly reports, Profound is worth evaluating. It is much more oriented toward enterprise-grade analytics and agency operations than the lightweight tools.

If your main goal is “What are ChatGPT, Gemini, Claude, Perplexity, etc. saying about my brand—and is the tone positive or negative?”, I’d shortlist these:

My recommendation

1. Peec AI — if sentiment is the centerpiece.

Peec explicitly tracks brand sentiment, attributes/perception, visibility, position and share of voice across AI engines. It can show how AI describes a brand—for example, whether it associates you with attributes such as “reliable,” “expensive,” or “outdated”—rather than merely counting mentions. Peec AI Peec AI

2. Profound — if you're an enterprise brand/communications team.

Profound's Answer Engine Insights combines visibility, citations, sentiment, share of voice and positioning, and it queries answer engines on a recurring basis to build a dataset of how your brand is represented. Profound Help Center TechnologyAdvice

3. OtterlyAI — if you want something straightforward and relatively broad.

Otterly monitors responses across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and scores mentions, sentiment, rank and share of voice. It also stores the underlying responses and citations, which is useful for investigating why sentiment changed. Otterly Otterly AI

One important distinction

Don't evaluate these tools solely on “sentiment score.” For AI-generated answers, I'd want at least five metrics:

• Mention/coverage: Does the assistant mention your brand?
• Position: Where does it place/recommend you?
• Sentiment: Positive, neutral or negative?
• Attributes: Why is it positive/negative?
• Source/citation attribution: Which websites, reviews, Reddit threads, news stories, etc. are influencing the answer?

That last piece is particularly important because an AI model can have a negative perception of your brand even when your own website says nothing negative—the model may be synthesizing third-party sources. Peec and Otterly both expose source/citation information alongside brand perception. Peec AI Otterly

If I were buying today:
Peec AI for a brand/consumer-insights team, Profound for a large enterprise/PR organization, and OtterlyAI for a leaner marketing or SEO team.

If you tell me your company size, approximate number of brands, and whether you care more about PR/reputation or SEO/GEO, I can narrow this to the best 2–3 and compare pricing, assistant coverage, API access, historical data, sentiment methodology, and reporting.

Profound's Answer Engine Insights combines visibility, citations, sentiment, share of voice and positioning, and it queries answer engines on a recurring basis to build a dataset of how your brand is represented. help.tryprofound.com technologyadvice.com

3. OtterlyAI — if you want something straightforward and relatively broad.

Otterly monitors responses across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and scores mentions, sentiment, rank and share of voice. It also stores the underlying responses and citations, which is useful for investigating why sentiment changed.

One important distinction

Yes. What you’re describing is usually sold as AI search visibility / LLM brand monitoring / GEO monitoring rather than traditional web crawling. These tools submit relevant prompts to AI assistants, capture the resulting answers, detect your company’s mentions, and classify the context/sentiment.

Best fits

• otterly.ai — probably the closest match. It monitors ChatGPT, Perplexity, Gemini, Google AI Overviews/AI Mode and Copilot, tracking brand mentions, citations, share of voice, and sentiment. Otterly Otterly
• peec.ai — good if you want granular analysis of AI-generated mentions and competitive visibility. It covers ChatGPT, Perplexity, Gemini and Google AI Overviews. Slate
• tryprofound.com — stronger enterprise-oriented option, with broad LLM coverage, sentiment analysis and brand intelligence. Slate
• foglift.io — particularly interesting if you want the actual answer evidence, cited URLs, sentiment, competitors and an API rather than just a visibility score. It monitors ChatGPT, Perplexity, Claude, Gemini and Google AI Overviews. Foglift Foglift
• searchprism.io — unusually good fit if your requirement is specifically “give me the snippets/answer text mentioning my company.” It says it stores the complete AI answer word-for-word, then extracts the brand mention, position, sentiment, competing brands and cited URLs. Prism
• gumshoe.ai — useful if you care about how different buyer personas perceive your company, rather than simply counting mentions. It tracks visibility, recommendation rates and sentiment across multiple AI models. Gumshoe AI

My shortlist for your exact use case

One important distinction: these systems generally don't crawl ChatGPT/Claude/Gemini's internal databases. They repeatedly query the assistants with a controlled prompt set and analyze the answers they return. That's actually preferable for your use case because you get the observable answer a prospective customer would see, rather than an inferred model opinion. Foglift Prism

If you tell me your company/category and whether you need an API or just a dashboard, I can narrow this to the 2–3 best options and compare pricing, assistant coverage, snippet export, sentiment accuracy, and API access.