Answers that do not mention Peec AI

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

Best fit: OtterlyAI

otterly.ai is probably the closest match to your specific use case.

It can:

• Track the prompts/questions you care about across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, and Copilot. Otterly Otterly AI
• Show which URLs and domains each AI answer cited, not just whether your brand was mentioned. Otterly Otterly AI
• Tell you which competitors and third-party sites are being cited instead of you. Otterly AI
• Track citation/visibility changes over time, which is useful for measuring whether your blog content is gaining AI visibility. Otterly
• Export citation data and access it programmatically through an API. Otterly

For an ecommerce blog, I'd set up prompts such as:

"What are the best [product category] for [use case]?"
"How do I choose a [product]?"
"Best [product category] brands for [customer type]"

Then look at a report like:

That gives you a competitive citation map: which websites are the AI systems trusting for your topics, and which of your pages need to become those sources.

Another option: Citations.io

citations.io is more narrowly focused on citation/AI visibility tracking. It tracks citations across ChatGPT, Gemini, Perplexity and Claude and explicitly shows who is being cited instead of you. Citations.io

One important distinction

There are actually two different things you may want to track:

1. "What websites is the chatbot citing?" → use an AI visibility/citation tracker such as OtterlyAI.
2. "Are AI crawlers actually visiting my blog?" → you want bot/server-log analytics. OtterlyAI now has Agent Analytics, which can identify AI crawlers and which pages they access. Otterly AI Otterly AI

The first is much more useful for your question because a crawler visiting your article doesn't necessarily mean the article gets cited in an answer.

If your goal is specifically "I want to see every domain ChatGPT/Perplexity/Gemini cite for my ecommerce topics, then find content opportunities to get my own blog cited instead", I'd start with OtterlyAI. Otterly

That gives you a competitive citation map: which websites are the AI systems trusting for your topics, and which of your pages need to become those sources.

Another option: Citations.io

citations.io is more narrowly focused on citation/AI visibility tracking. It tracks citations across ChatGPT, Gemini, Perplexity and Claude and explicitly shows who is being cited instead of you. citations.io

One important distinction

There are actually two different things you may want to track:

Yes. What you’re looking for is generally called AI search visibility / GEO (Generative Engine Optimization) tracking. These platforms run real queries against AI search products and record which websites/pages are cited, so you can see who is winning citations in your niche.

The two I’d look at first

• tryprofound.com — probably the closest match to what you described. Its citation tools show which sources AI engines pull from, how frequently they’re cited, which competitors are getting cited, and which publishers/authors are influential in your category. It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, Grok and others. Profound Profound
• otterly.ai — more accessible for a smaller publisher. You give it prompts such as “What happened in [your niche] this week?” and it monitors the answers daily, showing the URLs being cited, your competitors' citations, and changes over time. It covers ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. Otterly Otterly

Otterly currently advertises a free trial and pricing starting at $29/month. Otterly

But there's an important distinction for a news site

You don't really want to know “Does AI know my website exists?”

You want to answer:

“When someone asks an AI about stories in my niche, which publications does it cite—and what would make it cite mine instead?”

That's a much more useful dataset.

For example, suppose your site covers Kansas City local business news. You could track prompts like:

• “What are the latest restaurant openings in Kansas City?”
• “What happened in Kansas City business news this week?”
• “Which companies are expanding in Kansas City?”
• “Latest Kansas City development projects”
• “What happened with [specific company]?”
• “Kansas City news about [specific neighborhood]”

Then you could build a spreadsheet like:

That tells you where the citation opportunities actually are.

There's another signal that's especially interesting for a news publisher

AI crawlers can actually visit your website when answering a user's question. Otterly now has Agent Analytics, which analyzes server logs and distinguishes things such as search-index crawlers from on-demand fetchers like ChatGPT-User, Claude-User, and Perplexity-User. Otterly Otterly

That means you can potentially see something like:

ChatGPT-User → /story-about-company-X/

That's considerably more useful than simply seeing that GPTBot crawled your homepage.

If your goal is specifically “become a cited source”

I'd approach it as source acquisition rather than traditional SEO.

The interesting research question is:

What characteristics do the sources that AI cites repeatedly have that my site doesn't?

For a niche news publication, I'd investigate:

1. Original reporting — AI has a reason to cite you if you're the originating source.
2. Named reporters/authors — establish clear authorship and expertise.
3. Specific factual claims — dates, numbers, names, quotes, documents, etc.
4. Freshness — especially important for news.
5. Consistent topical authority — become the publication covering a narrow subject.
6. Indexability/crawlability — AI can't cite what it can't retrieve.
7. Third-party recognition — other reputable sites linking to and referencing your reporting.
8. Structured article metadata — clear publication dates, authors, headlines, organization information, etc.

And I'd pay particular attention to which individual articles get cited, rather than merely whether your domain gets mentioned.

The landscape is also changing rapidly: for example, recent research found a major decline in Reddit's share of ChatGPT citations in August 2026, illustrating that citation sources can shift substantially as AI search systems change. Business Insider Axios

If you tell me what your niche news site covers (and the domain, if you want), I can actually research your competitive citation landscape—which AI platforms matter, which publications currently get cited for your topics, and what I'd do to make your site one of those sources.

ChatGPT-User → /story-about-company-X/

That's considerably more useful than simply seeing that GPTBot crawled your homepage.

If your goal is specifically “become a cited source”

I'd approach it as source acquisition rather than traditional SEO.

The interesting research question is:

What characteristics do the sources that AI cites repeatedly have that my site doesn't?

For a niche news publication, I'd investigate:

1. Original reporting — AI has a reason to cite you if you're the originating source.
2. Named reporters/authors — establish clear authorship and expertise.
3. Specific factual claims — dates, numbers, names, quotes, documents, etc.
4. Freshness — especially important for news.
5. Consistent topical authority — become the publication covering a narrow subject.
6. Indexability/crawlability — AI can't cite what it can't retrieve.
7. Third-party recognition — other reputable sites linking to and referencing your reporting.
8. Structured article metadata — clear publication dates, authors, headlines, organization information, etc.

And I'd pay particular attention to which individual articles get cited, rather than merely whether your domain gets mentioned.

The landscape is also changing rapidly: for example, recent research found a major decline in Reddit's share of ChatGPT citations in August 2026, illustrating that citation sources can shift substantially as AI search systems change.

Yes. The category you’re looking for is usually called AI citation tracking, AI visibility tracking, Generative Engine Optimization (GEO), or Answer Engine Optimization (AEO). These tools monitor which websites/pages appear as sources in AI answers and help you identify opportunities to get your niche news site cited. Scrunch Centium

Some platforms to look at:

• scrunch.com — Tracks which URLs are cited by AI systems for tracked prompts and shows citation share, top cited domains, and competitors. Scrunch
• llmpulse.ai — Shows which domains/pages ChatGPT, Gemini, and Perplexity cite for your topics and helps find “citation gaps” where competitors are appearing instead of you. LLM Pulse
• citedspy.com — Focused on extracting cited URLs from AI answers and ranking which domains influence a market. CitedSpy
• centium.ai — Tracks source stacks behind AI answers across models and can show which sites are influencing answers in a niche. Centium
• indexly.ai — Tracks citation share, source rankings, and page-level citations across major AI engines. Indexly

For a niche news site, I’d use these tools less as “SEO rank trackers” and more as a PR/content intelligence system:

1. Pick 50–100 prompts your audience would ask AI:

• “What happened in [your niche] this week?”
• “Who are the top experts in [field]?”
• “What are the biggest developments in [industry]?”
• “Best sources for [topic] news”
• Track which publications are repeatedly cited.
• Study what those cited pages have in common:

• original reporting
• named experts
• data/primary documents
• clear dates and timestamps
• author bios
• structured pages
• Create content that fills gaps:

• original investigations
• weekly briefings
• databases
• explainers AI can easily summarize

A useful shortcut: Perplexity and AI systems with visible citations are also good manual research tools because you can ask the same niche questions repeatedly and see which publications keep appearing. xSeek

One important distinction: these tools show what AI systems cite in retrieved answers; they usually cannot reveal the complete private training dataset of a model. They’re measuring visible citations and retrieval behavior, not the entire corpus used to train a model. LLM Pulse

If you tell me your niche (e.g., crypto, local politics, biotech, sports, finance, gaming), I can suggest the citation strategy and the types of stories most likely to get pulled into AI answers.

Yes. The category you want is AI citation tracking / AI visibility tracking, but I’d prioritize tools that expose the actual cited URL, not just whether the brand was mentioned.

My top pick: indexly.ai

It looks particularly well matched to your use case because its “My Page Citations” feature tracks:

• Which specific pages/URLs on a client’s site are cited
• Citation counts by page
• Counts by AI engine
• Daily citation history
• Which pages have stopped being cited
• Filtering by engine or page path

It covers ChatGPT, Claude, Gemini, Perplexity and Grok. Indexly

That distinction is important: a lot of AI-visibility tools will tell you “Client X was mentioned 47 times”, but you're asking the more useful agency question: “Which of Client X's 800 URLs are actually being used as sources, and how often?”

Strong alternative: citations.io

Citations.io has a Citation Map showing every URL, domain and snippet cited for tracked prompts, plus an answer archive and visibility reporting across ChatGPT, Perplexity, Gemini and Claude. Citations Citations

I'd favor this if you're also trying to give clients a broader AI visibility report, rather than just page-level citation analytics.

Another interesting option: trendos.com

Trendos specifically focuses on the sources behind AI answers and says it shows which domains and pages are cited and how often each appears. Trendos

If you're doing this for multiple clients

I'd evaluate the tools on these five criteria:

For your exact use case, I'd start with Indexly. Its page-level citation view appears closest to “show me every page on this client's site that AI assistants reference, and tell me how often.” Indexly

One caveat: these products measure sampled AI responses to tracked prompts, not an omniscient log of every AI assistant response on the internet. Citation frequency should therefore be interpreted as frequency within the tool's monitored prompt set, not absolute global usage. This is an important distinction when reporting results to clients. Citations deepsmith.ai

If you tell me roughly how many client sites you manage (e.g. 10, 50, 500), I can narrow this down to the best agency-oriented option and likely pricing tier.

Yes. For your exact use case, I’d shortlist Indexly first, especially if you’re managing multiple client sites.

indexly.ai

Why Indexly fits

It specifically tracks page-level citations, rather than just whether a brand was mentioned:

• Which URLs on a client’s site are being cited by AI.
• Citation counts per URL, so you can see which pages are doing the work.
• Breakdowns by ChatGPT, Claude, Gemini, Perplexity, Grok and Google AI Overviews.
• Daily tracking and historical data, allowing you to measure citation frequency and changes over time.
• Citation share and competitor-source analysis.
• An API, which could be useful if you want to roll this into your own agency dashboard or reporting workflow. Indexly

For example, you could get something conceptually like:

That is much closer to the question “Which pages are AI assistants actually using?” than a generic AI visibility score.

Two alternatives worth testing

Citations.io is another strong option if you want a broader agency-oriented AI visibility platform. Its “Citation Map” records every URL/domain cited and provides an answer archive, competitive share-of-voice, and tracking across ChatGPT, Perplexity, Gemini and Claude. Citations.io

citations.io

OtterlyAI is worth considering if you care more about prompt-level monitoring and reporting. Its prompt analysis exposes the URLs used as citations and tracks brand visibility over time; it currently covers ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude. OtterlyAI OtterlyAI

help.otterly.ai

My pick

Indexly → best match for “which pages + how frequently.”
Citations.io → best if you want a fuller agency/client AI-visibility platform.
OtterlyAI → best if prompt tracking and broader AI-search coverage are more important.

One caveat: these tools generally measure citations generated in repeated/monitored AI queries, not a literal log of every time a real-world ChatGPT user happened to reference a page. So “40 citations” means 40 observed citations in the tool's monitoring methodology—not 40 total instances across all AI users.

If you tell me how many client sites you manage (e.g. 10, 50, 200) and whether you need white-label reporting, I can narrow this down to the best agency tool and compare pricing/features.

If your goal is specifically “Which domains are AI answer engines citing when people ask product-related questions in my store’s category?”, I’d use a dedicated AI-search/GEO visibility platform, rather than trying to infer it from Google Analytics.

My pick: OtterlyAI

otterly.ai is probably the best fit for what you described.

It can track prompts across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot, and Claude, then show the actual URLs/domains cited in the answers. Its citation reporting lets you filter by domain, URL, engine, prompt, and date. Otterly Otterly

For an ecommerce store, I'd structure it around queries such as:

• “best [product category]”
• “[product] alternatives”
• “best [product] for [use case]”
• “[product A] vs [product B]”
• “where to buy [product]”
• “most reliable [product category]”
• “best [product category] under $X”
• “[product category] for beginners”
• “what should I look for when buying [product]?”

Then look at Top Citation Domains rather than just whether your own brand appears.

That gives you a dataset roughly like:

That is much more actionable than a generic “AI visibility score.” Otterly specifically exposes every cited URL, its domain, citation count, and whether your brand is mentioned on that source. Otterly Otterly

The other one I'd seriously consider: Profound

tryprofound.com is arguably the stronger choice if you want to turn this into a more sophisticated enterprise AEO/GEO program.

Its Citation Intelligence specifically provides Top Citation Domains, Top Citation Pages, citation share, citation categories, and citation relationships, and lets you break the data down by platform, topic, and prompt. Profound Profound Knowledge Base

One feature I particularly like for ecommerce is the ability to classify sources as owned, competitor, earned media, social, institutional, etc. That lets you answer not merely:

“Who is AI citing?”

but:

“Are AI engines getting their product information from retailers, publishers, Reddit, competitors, manufacturers, review sites, or our own product pages?”

That's the strategic question I'd care about.

What I'd choose

Small/mid-sized ecommerce team → OtterlyAI.
It's more directly oriented around prompt monitoring + citation/domain tracking, and it also has shopping analytics for seeing which products and retailers ChatGPT surfaces. Otterly

Larger SEO/content team → Profound.
I'd favor it if you want deeper analysis of citation share, source categories, competitive gaps, and content/outreach workflows. Profound Profound

One important distinction

Don't just track your domain's citations.

Build a dataset of all domains cited for commercial/product-intent prompts, because the really valuable insight is often:

“AI engines cite these 30 domains repeatedly when answering questions in our category, but our brand appears on only 4 of them.”

Those 30 domains become your AI influence map—potential review sites, comparison publishers, Reddit communities, retailers, manufacturers, editorial sites, etc.

If you tell me what you sell + roughly how many product categories/SKUs you have, I can also suggest the exact prompt taxonomy and dashboard/KPIs I'd use to map your AI citation landscape.

If your goal is specifically “which domains are AI answer engines citing when shoppers ask product/category questions?”, I’d use a dedicated AI-search visibility platform rather than trying to infer it from Google Search Console or traditional SEO tools.

My picks

1. Profound — best for serious ecommerce/competitive analysis

This is probably my first choice if you're building an actual AI citation map.

Profound lets you track prompts across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot and others, then see the specific URLs and domains cited, citation share, competitors, and source categories. www.tryprofound.com

For an online store, I'd structure it around prompts like:

• “best running shoes for flat feet”
• “best [product category] under $100”
• “[product type] for beginners”
• “[competitor] vs [your product]”
• “best [product category] for [use case]”
• “where should I buy [product]?”
• “[product] alternatives”
• “best brands for [category]”

Then build a dataset like:

The particularly useful thing is that Profound exposes Top Citation Domains, Top Citation Pages, Citation Share, and citation relationships, so you can identify not just who cites you, but which third-party sites are influencing AI answers in your category. help.tryprofound.com

2. OtterlyAI — best simpler/leaner option

OtterlyAI is worth looking at if you want something more straightforward. It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude and Copilot, and specifically exposes every cited URL, citation frequency, domain, competitors, and whether your brand appears on the cited page. otterly.ai

It also has AI Shopping Analytics, which is particularly relevant for a store: it tracks products/retailers surfaced when buyers ask shopping questions. otterly.ai

What I'd actually build

Don't just track your domain's citations. That's too narrow.

I'd create an AI Citation Landscape with four layers:

Layer 1 — Buyer prompts
500–2,000 natural-language shopping questions across your important categories.

Layer 2 — Answer engines
ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Claude, Copilot, etc.

Layer 3 — Citation domains
For every answer, extract:

engine → prompt → cited URL → domain → page type → brand mentioned → competitor mentioned

Layer 4 — Opportunity scoring

Then rank domains by something like:

Opportunity = citation frequency × relevance × competitor presence × your absence

That gives you a much more actionable output than “our brand has 18% AI visibility.”

For example:

Reddit — 127 citations
43% of relevant answers
Your brand mentioned in only 8%
Competitor A mentioned in 31%
→ High-priority influence source

That tells your SEO/content/PR team where AI is getting its product knowledge, and therefore where you need to improve your own content or earn third-party coverage.

One important distinction

I'd separate “AI cites my store” from “AI cites a site that influences whether my store gets recommended.”

The second one is arguably more valuable.

If AI consistently cites Wirecutter, Reddit, specialist review sites, retailers, forums, etc. for your product category, those domains become your AI influence graph. Profound's citation categorization is designed for exactly this kind of analysis, including owned, competitor, earned media, social, institutional and other sources. help.tryprofound.com

So my short answer: start with Profound if you want the deepest mapping; use OtterlyAI if you want a simpler, more approachable implementation. For a product-heavy ecommerce site, I'd lean Profound + your own warehouse/dashboard once you know the dimensions you care about.

Yes. For a small marketing agency, I’d shortlist these:

• otterly.ai — probably the best starting point if you want broad engine coverage. It tracks ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude, including mentions, citations, competitors, and share of voice. Otterly
• scoutllm.ai — particularly agency-friendly: client workspaces, daily visibility/SOV tracking, competitor tracking, city-level markets, alerts, and white-label reports. Scout LLM Scout LLM
• citegauge.com — attractive for a smaller agency because its Agency plan is listed at $149/month for 10 client workspaces and 250 prompts, with white-label reporting. It covers ChatGPT, Claude, Gemini, and Perplexity. CiteGauge
• rankscope.ai — worth considering if you want something relatively inexpensive but with an explicit agency tier; its Agency plan is listed at $399/month for 400 prompts, tracking ChatGPT, AI Overviews, Perplexity, and Google AI Mode. RankScope
• citemetrix.com — interesting if you need a larger multi-client operation: unlimited domains/clients on its agency track, white-label reporting, and nine AI platforms including ChatGPT, Claude, Gemini, Perplexity, Grok, Copilot, DeepSeek and Google AI Overview. Agency pricing starts at $299/month. CiteMetrix

My pick

For a small agency with, say, 5–20 clients, I'd start with OtterlyAI or Scout LLM.

If your primary deliverable is “Here's our client's AI share of voice vs. competitors, and here's exactly which websites/models are citing them”, OtterlyAI looks particularly strong because it explicitly breaks SOV down by prompt, engine, and market and tracks the actual cited URLs. Otterly

If white-label client reporting and agency workspaces are more important, I'd trial Scout LLM or CiteGauge. Scout LLM CiteGauge

One important distinction: don't buy a tool merely because it says it tracks "AI visibility." For your use case, I'd require (1) citation-level data, (2) competitor SOV, (3) separate results by model/engine, (4) historical trends, and (5) multi-client/white-label reporting.

If you tell me roughly how many clients and prompts you need to monitor, I can narrow this to the 2–3 best options and compare their current pricing/features.

For a small marketing agency managing multiple clients, I’d shortlist these:

🥇 My pick: OtterlyAI

OtterlyAI AI Search Analytics

Otterly is particularly well aligned with what you're asking for: it runs the same prompt set across multiple AI engines, then measures brand mentions, citations, sentiment, average position and share of voice against named competitors. It currently supports ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, Copilot and Claude. otterly.ai

For an agency, the useful distinction is that you can report things like:

Client A — AI Share of Voice: 27%
ChatGPT: 31%
Gemini: 24%
Perplexity: 38%
Claude: 19%
Competitor 1: 34%
Competitor 2: 22%

It also tracks the actual URLs being cited, which is important because you can turn the measurement into an SEO/content/PR action plan rather than merely telling the client "your AI visibility went up." otterly.ai

If you want the most models

Zumi AI Search Intelligence

Zumi currently advertises monitoring across up to nine engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, Google AI Overviews, Google AI Mode and DeepSeek. It also explicitly measures visibility and competitor share of voice. www.zumihq.com

That's attractive if your agency wants to say, "We monitor your brand everywhere buyers might encounter an AI answer," rather than limiting reporting to the four or five major assistants.

If you're building this into an agency reporting stack

CitationBench

CitationBench is worth looking at because it specifically describes an agency multi-workspace architecture, where one master API key can manage separate client workspaces and schedule daily AI citation checks. It currently covers ChatGPT, Claude and Perplexity. www.zumihq.comwww.citationbench.comcitations.io

That could be particularly useful if you're already building client dashboards in Looker Studio, AgencyAnalytics, Databox, etc., and want to pull the AI-visibility data into your existing reporting rather than giving clients another dashboard.

Budget option

Citations.io

Citations.io is unusually inexpensive for a small agency: it advertises plans starting at $29/month, with ChatGPT, Gemini, Perplexity and Claude monitoring, competitor share-of-voice, citation sources and a monthly implementation pack. citations.io

I'd test it against Otterly on 2–3 real clients before standardizing on it, though.

Bottom line: If I were running a 5–20-person agency today, I'd trial Otterly first, Zumi second if nine-model coverage is important, and CitationBench if API/multi-client automation is the priority.

One important caveat: don't compare vendors solely on the number of "models." Prompt methodology, geographic personalization, sampling frequency, citation extraction, competitor definitions, and whether share-of-voice is calculated per-answer or per-citation can materially change the numbers. AI search visibility is volatile enough that methodology matters a lot. Recent reporting, for example, found ChatGPT's Reddit citation share moving substantially over just a few weeks. www.axios.com

If you tell me roughly how many clients and prompts per client you need to monitor (e.g. 10 clients × 50 prompts), I can narrow this down to the cheapest 2–3 options and compare their agency pricing/features.

If your goal is specifically “which papers, university-press pages, and competing domains are actually being cited by ChatGPT/Perplexity/etc., so we can improve discoverability,” I’d separate this from traditional scholarly citation analysis.

My shortlist

• tryprofound.com — best for a serious university-press program. It tracks citations at the URL level across a broad set of AI engines, including ChatGPT, Perplexity, Gemini, Claude, Copilot and Google AI surfaces. That granularity is particularly useful for a press because you can distinguish which individual book/article/landing page gets retrieved rather than merely whether the press's domain is mentioned. Nick Lafferty
• semrush.com — best if your press already uses Semrush. It monitors which domains are cited for specified prompts and combines AI visibility with conventional SEO data. Semrush says its dataset includes hundreds of millions of AI-search prompts, making it useful for competitive benchmarking as well as monitoring your own domain. Semrush Semrush
• otterly.ai — best lower-cost starting point. It tracks a fixed set of prompts and identifies citations across ChatGPT, Perplexity, Gemini, Google AI Overviews and Copilot. Current published comparisons put it around $29/month at the entry level. Distribution.studio Semrush
• getintel.ai — particularly interesting if your question is literally “what sources did the AI cite?” Its distinguishing feature is storing the cited URLs from individual runs rather than reducing everything to a visibility score. It currently covers ChatGPT, Perplexity, Gemini and Google AI Overviews, with Claude on a higher tier. GetIntel
• scite.ai — complementary, not a replacement. For an academic press, Scite is excellent for the other side of the problem: how individual papers are being cited in scholarly literature and whether subsequent research supports or contradicts them. It also integrates with ChatGPT/Claude and provides an API. scite.ai scite.ai

What I'd buy for a university press

I'd probably start with Profound + Scite, rather than trying to make one product do both jobs.

Think of the two datasets as:

Scite:

“How influential/referenced is this scholarship within the scholarly ecosystem?”

Profound (or Semrush/Otterly):

“When someone asks an AI a question related to this scholarship, which sources does the AI actually retrieve and cite?”

That distinction matters. A book can have excellent conventional scholarly citations but be essentially invisible to AI search—and conversely, an ordinary web page can become a disproportionately important AI source.

There's also substantial volatility between AI systems: one 2026 analysis found only about 11% of cited domains overlapped between ChatGPT and Perplexity, while another Semrush analysis found only 25.6% overlap between different ChatGPT reasoning modes for the same prompts. Distribution.studio Semrush So I would not buy a tool that only measures “ChatGPT visibility.”

The metrics I'd want the press dashboard to contain

For each title/paper, track:

• AI citation rate: percentage of relevant prompts where the work/page is cited.
• Citation position: first source, middle of source list, etc.
• Citation URL: the exact page being retrieved.
• Citation type: book page, journal article, repository, review, Wikipedia, library record, news article, etc.
• Competing sources: which other papers/books/domains are being cited instead.
• Prompt/topic: e.g. “history of X,” “scholars studying Y,” “best books on Z.”
• Engine: ChatGPT, Perplexity, Gemini, Claude, Google AI.
• Change over time: whether a title is becoming more or less discoverable.
• Uncited opportunities: queries where competing scholarship is cited but your press's material isn't.
• Third-party citations: places such as university pages, reviews, bibliographies and institutional repositories that may be acting as the bridge through which AI discovers your book.

That last category is especially valuable for a press. Don't optimize only the publisher's own domain. If AI systems repeatedly cite a university repository, review, scholarly society page, or Wikipedia entry instead of your book page, that tells you something about the discovery path of the scholarship.

One important caveat: these products generally sample controlled prompts and observe the resulting citations; there isn't a universal feed containing every question every ChatGPT user asks. CiteFlow So I'd treat the resulting numbers as trend/benchmark measurements, not absolute counts of “all AI citations.”

If you tell me roughly how many titles your press publishes per year and whether you want an institutional/enterprise system or something a one-person marketing team can run, I can narrow this to 2–3 products and compare price, AI engines, URL-level citation data, API/export capability, and suitability for academic publishing.

The metrics I'd want the press dashboard to contain

Yes. There’s now a growing category specifically for this: AI citation / AI visibility monitoring. These tools repeatedly query AI assistants and tell you when your domain—or, importantly, a specific page on your domain—is cited.

A few worth looking at:

• Indexly — probably closest to what you're describing. It tracks citations at the individual URL/page level, showing which of your blog posts were cited by ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI Overviews, with daily counts. indexly.ai
• CiteWatch — tracks citations across ChatGPT, Gemini, Claude, Copilot, and Perplexity. It also has citation/traffic attribution. cite.watch
• Citescope AI — specifically lets you monitor multiple URLs and see which AI engines cite each one. www.citescopeai.com
• Surva.ai — has a "My Citations" view where you can add specific blog posts/guides/pages and monitor whether AI platforms link to them, plus citation alerts. www.surva.ai
• Citations.io — more oriented toward overall AI visibility, but provides a live citation feed and shows which sources AI assistants are using. citations.io

One important distinction

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

1. "Did an AI assistant cite my URL?"

Example: ChatGPT answers a question and links directly to yourblog.com/my-article.
→ Indexly, Citescope, and Surva look particularly relevant.

2. "Did an AI assistant crawl/read my page?"

Example: GPTBot or PerplexityBot visits your article, but the article isn't necessarily shown to a user.
→ Tools such as Robot-Speed AI Visibility focus more on crawler logs as well as citations. www.robot-speed.com

If your goal is specifically "send me an alert whenever ChatGPT/Perplexity/etc. starts citing one of my blog posts," I'd start with Indexly or Surva.ai. They're closer to a true citation inbox than a general SEO/GEO dashboard.

If you tell me roughly how many pages you have (e.g. 50, 500, 10,000), I can compare the best options—including pricing and which ones can actually send email/Slack alerts when a new citation appears.

If you mean “which exact passages on my site are being used/quoted by ChatGPT, Gemini, Perplexity, Google AI Overviews, etc.?”, there’s an important distinction:

• Most AI-visibility tools can tell you which URL was cited.
• Far fewer can reliably tell you which paragraph/sentence from that URL contributed to the answer.
• AI systems generally don't expose a clean “this paragraph was quoted” attribution, so paragraph-level analysis often has to be inferred by comparing the AI answer against the cited page.

Best options right now

1. scrunch.com — probably the closest fit

Scrunch tracks the cited URL, the prompt, the AI answer, and which pages contributed to the answer. Its Citations and Prompt Monitoring features let you drill down from domain → URL → prompt → actual AI response. Scrunch Help Center Scrunch

That makes it particularly useful if your workflow is:

“AI cited /guides/best-x → show me the answer it generated → determine which portions of my page appear to have supplied the information.”

However, I would not interpret Scrunch as giving you a definitive sentence-level attribution such as “paragraph 7 was quoted 14 times.”

2. tryprofound.com — strongest for citation intelligence

Profound gives you citation-level visibility across ChatGPT, Perplexity, Google AI Overviews and other answer engines, including the specific URLs being cited, citation frequency, prompts, platforms and watched pages. Profound Profound Knowledge Base

It's excellent for answering:

“Which pages of my site are AI systems using?”

But again, its public documentation focuses on page/URL-level citations, rather than identifying the exact paragraph or sentence that was extracted. Profound Knowledge Base

3. otterly.ai — good lower-cost visibility layer

Otterly tracks AI answers and the URLs cited by ChatGPT, Perplexity, Google AI Overviews, Gemini, Copilot and Claude. Otterly Otterly

It's useful for establishing which pages are getting cited, but it isn't really a paragraph-level “content provenance” tool.

If your actual goal is paragraph-level attribution

I'd approach it as a two-stage system:

AI visibility tool → cited URLs → retrieve page → semantic matching against AI answer

For example:

Your website
    ↓
Scrunch / Profound / Otterly
    ↓
AI answer + cited URL
    ↓
Fetch cited webpage
    ↓
Split page into paragraphs/sentences
    ↓
Semantic similarity / phrase matching
    ↓
"These 3 passages most likely contributed to the AI answer"

That can produce a much more useful report such as:

If this is specifically what you're trying to build, I wouldn't choose a tool solely on “AI citation tracking.” I'd look for one that gives you the raw AI responses + cited URLs, because those are the ingredients needed to calculate paragraph-level attribution yourself.

Of the three, Scrunch looks like the best starting point for this particular use case, because its documentation explicitly describes drilling into the actual prompt-level AI answers and the sources used to shape them. Scrunch Scrunch

If you tell me whether you want this for your own site, a SaaS product, or an agency managing many sites, I can also compare the current tools specifically on sentence/paragraph-level attribution, APIs, exports, and price.

If by “which specific paragraphs/snippets from my site are being quoted” you mean not just which URL is cited, but the actual passage that appears to have been used in the AI answer, that’s a more specialized capability.

Best options

• otterly.ai — probably the closest fit. It captures AI answers across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot and Claude, and tracks the specific URLs cited. It also has content-audit functionality. Otterly Otterly
• help.ahrefs.com — excellent for finding which pages on your site are cited and in which AI answers. Its distinction between “Cited” and “Found in” is particularly useful. Ahrefs Help Center Ahrefs Help Center
• semrush.com — tracks cited pages and the prompts/AI responses driving visibility, but is more focused on visibility and competitive analysis than passage-level attribution. Semrush

The important distinction

Most AI-visibility tools can tell you:

Prompt: “What are the best X tools?”
AI answer: …
Your cited page: yoursite.com/guide

Far fewer can reliably tell you:

Your page: /guide
Likely source passage: Paragraph 7, “X is particularly effective because…”
AI output: “X is particularly effective because…”

That's essentially passage-level citation/provenance analysis, and I wouldn't assume a tool provides it just because it advertises “citation tracking.”

If that exact paragraph/snippet-level analysis is what you're after, I can research the current 2026 tools specifically for that capability and tell you which ones actually do it, how accurate they are, and whether they can analyze your entire site rather than just tracked prompts.

Yes. What you’re describing is a little more specific than ordinary AI visibility tracking: you want to see the query → search/retrieval path → sources considered → cited URL → final AI answer.

The tools I’d look at are:

• findmecited.com — closest match to your description. Its “Search Trail” is specifically designed to show, where the provider exposes it, the queries the AI ran, URLs it considered, and whether your domain appeared. That lets you distinguish “AI never found my content” from “AI found it but chose someone else.” Find me Cited
• citedspy.com — strong if your priority is exact cited URLs. It captures cited URLs for each answer and lets you see which sources repeatedly influence answers in your market. CitedSpy
• citescopeai.com — shows the query, answer, and sources used by AI, with tracking across ChatGPT, Perplexity, Gemini, Claude and Google AI Overviews. Citescope AI
• citationradar.ai — good for seeing which questions you win/lose, which competitor pages are driving citations, and the resulting gaps across multiple AI engines. Citation Radar
• tryprofound.com — the heavier enterprise option. It focuses on systematic prompt monitoring and source-level citation intelligence rather than just checking whether your brand was mentioned. Bloomiro

My pick for your exact use case

If your question is:

“Someone asks an AI assistant X. How did it get from X to my page, and why did it cite—or not cite—me?”

I'd start with Find Me Cited, because the Search Trail concept is unusually close to that exact question. Find me Cited

If instead you want to build a content/SEO analytics workflow, I'd look at CitedSpy or CiteScope because they emphasize the query-to-citation data you can analyze repeatedly. CitedSpy Citescope AI

One important caveat: you generally cannot see the model's private internal chain-of-thought. What these products can expose is the observable retrieval/search trail—queries, retrieved URLs, citations, and answers—when the underlying AI provider makes those signals available. Find Me Cited explicitly makes that distinction. Find me Cited

If you tell me whether you're trying to monitor your own website, a client's websites, or build a product around this, I can narrow this to the 2–3 best options and compare their actual data/API capabilities.

If you mean “track how often our content/brand is cited by AI, where we rank versus competitors, and compare that across multiple models”, there are several good options. For an enterprise content team, I’d shortlist these:

My pick: Profound

Profound is probably the closest match to what you're describing.

It tracks visibility, citation share, cited URLs, competitor citations, and rankings across AI answer engines. Its citation analysis can show which pages and third-party sources are being cited, while its visibility scoring lets you benchmark your brand against competitors by platform, topic, and prompt. Profound Profound

For an enterprise content organization, the particularly useful pieces are:

• Citation frequency: how often your pages/domains are cited.
• Citation share: your share of citations versus competitors.
• Per-model analysis: see differences between ChatGPT, Claude, Gemini, Perplexity, etc.
• Prompt-level tracking: identify the questions where competitors get cited but you don't.
• Page-level monitoring: see which individual URLs gain or lose citations.
• Content workflow: turn citation gaps into content briefs and optimization work.
• Enterprise controls: SSO, RBAC, SOC 2 Type II, and multi-asset configurations. Profound

One important distinction: AI “rank” isn't quite the same thing as Google rank. These platforms generally measure things such as brand position/prominence within generated answers, share of voice, and citation share rather than a single deterministic SERP position. That's actually more useful for content teams trying to understand why an AI answer chooses one source over another.

Two alternatives I'd seriously evaluate

Searchable is interesting if you're building an AI-search operation across many brands, markets, and stakeholders. It combines mentions, citations, sentiment, source attribution, competitor share-of-voice and citation share, with enterprise integrations such as Looker Studio, REST API, MCP, GA4 and GSC. Searchable

Zumi is worth looking at if broad model coverage is important. It currently advertises monitoring across nine engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, Google AI Overviews, Google AI Mode and DeepSeek, with citation ranking and competitive share-of-voice metrics. Zumi

Citations.io is a more focused option: its dashboard centers on four engines—ChatGPT, Gemini, Perplexity and Claude—with a visibility score, citation map, competitive SOV, and answer archive. Its enterprise offering adds multi-brand workspaces, SSO/audit logs and managed prompt research. Citations Citations

What I'd use for an enterprise content team

If your goal is content planning and proving ROI, I'd rank them:

1. Profound — best all-around enterprise content/AEO platform.
2. Searchable — particularly compelling for multi-brand/global organizations and integrations.
3. Zumi — strongest if maximum model coverage is the priority.
4. Citations.io — simpler, focused citation intelligence.

If you tell me roughly how many brands/domains, markets, and prompts you need to track, I can also compare their pricing, prompt limits, model coverage, API/reporting, and enterprise features and tell you which is the best fit.

Zumi is worth looking at if broad model coverage is important. It currently advertises monitoring across nine engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, Google AI Overviews, Google AI Mode and DeepSeek, with citation ranking and competitive share-of-voice metrics. zumihq.com

Citations.io is a more focused option: its dashboard centers on four engines—ChatGPT, Gemini, Perplexity and Claude—with a visibility score, citation map, competitive SOV, and answer archive. Its enterprise offering adds multi-brand workspaces, SSO/audit logs and managed prompt research.

What I'd use for an enterprise content team

If your goal is content planning and proving ROI, I'd rank them:

If you mean AI-search/GEO visibility—i.e., “How often is our content cited by ChatGPT, Claude, Gemini, Perplexity, etc., and what position/rank does our citation have?”—there are several platforms now doing this.

Best fits for an enterprise content team

My first look would be searchable.com if you're specifically building an enterprise content operation. It is designed around multi-model telemetry and explicitly tracks mentions, citations, sentiment and source attribution across ChatGPT, Gemini, Perplexity, Claude and Google AI, with competitor share-of-voice and citation-share analysis. It also has SSO, project permissions, API/MCP and Looker integrations. Searchable

citations.io is particularly interesting if the core KPI is citation performance. Its Citation Map records the URLs/domains AI engines cite, including rank, sentiment and freshness, while its Visibility Score and Competitive SOV let you measure performance across prompts and competitors. Its enterprise offering includes multi-brand workspaces, SSO and audit logs. Citations Citations

zumihq.com is worth considering if broad model coverage matters. It says it monitors nine engines, including ChatGPT, Gemini, Perplexity, Claude, Copilot, Grok, AI Overviews, AI Mode and DeepSeek, and ranks the citations appearing in answers. Zumi

rankscale.ai is another strong option if you want traditional search and AI search together; it claims 17+ AI engines and tracks AI rankings alongside Google AI Overviews/AI Mode. Rankscale.ai

What I'd evaluate in a demo

Don't just ask whether they “track citations.” Ask whether they can give you these five metrics by prompt × model × URL × competitor × date:

1. Citation rate — % of relevant answers citing your domain.
2. Citation frequency — raw number of citations over time.
3. Citation rank/position — e.g. your source is #1 vs. #7 in the cited sources.
4. Citation share of voice — your citations vs. competitors.
5. Page-level attribution — exactly which content URLs are earning citations.

The last one is especially important for a content team: you want to go from “we lost AI visibility” → “our competitor's article is cited 4× more often on these 12 prompts” → “here's what we need to change.”

One caveat: AI “rank” isn't equivalent to Google SERP rank. Different models can return different answers, and some don't expose a stable ordered citation list. So I'd prioritize vendors that preserve the actual answer/citation evidence and methodology, rather than giving you a single opaque “AI visibility score.”

If you tell me your content team size, number of brands/domains, and which models matter (e.g. ChatGPT + Gemini + Perplexity), I can narrow this to the top 2–3 platforms and compare pricing, integrations, API access, and reporting.

rankscale.ai is another strong option if you want traditional search and AI search together; it claims 17+ AI engines and tracks AI rankings alongside Google AI Overviews/AI Mode.

What I'd evaluate in a demo

Don't just ask whether they “track citations.” Ask whether they can give you these five metrics by prompt × model × URL × competitor × date:

For your specific use case—seeing how AI citation patterns change by language and geography—I’d shortlist these:

• citenso.com — probably the closest match. It explicitly supports 27 languages and 30+ countries, with geo-targeted prompts and citation/visibility analytics across ChatGPT, Claude, Gemini, and Perplexity. Citenso Citenso
• donguri.ai — strong if you want standardized country-by-country comparisons, with local-language prompts across 20+ countries and citation share/mention metrics. donguri
• useomnia.com — tracks prompts in any country and language and preserves full AI responses, including citations, which is useful for figuring out why one market cites different sources from another. Omnia
• rankscale.ai — better if your emphasis is citation-source analysis: domains/URLs, citation volume, categories, and regional filtering. Rankscale.ai

My pick

For a multilingual brand optimizing content, I'd start with Citenso if its supported languages/countries match your markets. The key capability isn't merely “AI visibility”; you want a matrix like:

Market × language × AI engine × prompt × cited source × competitor

That lets you discover patterns such as “Our English content gets cited in the US, but German-language answers cite local publishers instead” and then build content specifically for that citation ecosystem.

If you tell me your target countries/languages and industry, I can narrow this to the 2–3 tools that best fit and compare their coverage/features.

For your use case, I’d shortlist Profound and OtterlyAI.

Best fit: Profound

Profound looks strongest if geographic + language segmentation is the core requirement. Its Answer Engine Insights supports 30+ languages and 150+ regions, and lets you analyze visibility, citations, platforms, sentiment, and share of voice. Its regional view can break visibility down by country, including a world heat map. www.tryprofound.com

That means you could build something like:

English / US → citation sources → competitors → content gaps
French / France → citation sources → competitors → content gaps
German / Germany → citation sources → competitors → content gaps
Japanese / Japan → citation sources → competitors → content gaps

It also lets you filter prompts by region, topic, persona, and tags, which is useful for comparing the same intent across markets. www.tryprofound.com

Strong alternative: OtterlyAI

OtterlyAI is particularly attractive if you want detailed citation-level analysis. It currently supports 65+ countries and languages and tracks citations across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude. help.otterly.ai

Its Citations report can be filtered by engine and country, while citation details show which prompts and engines produced a citation and whether your brand was mentioned. help.otterly.ai

What I'd choose

For a multilingual brand, I wouldn't optimize around a single global "AI visibility score." I'd create a market × language × AI engine × prompt-intent matrix, then compare:

• citation rate
• brand mention rate
• share of voice
• citation domains/pages
• competitor citations
• sentiment/positioning
• prompts where you're cited in one language but not another

That will tell you whether, for example, your Spanish content is genuinely weaker—or whether Spanish-language AI answers simply rely on a different ecosystem of publishers and sources.

If you tell me which languages/markets your brand targets, I can also recommend the best tool and a concrete measurement framework for your situation.

If your main requirement is “show me how often my domain has been cited by AI assistants, and how that has changed over time,” I’d shortlist these:

Best fit: indexly.ai

Indexly looks like the strongest match for your specific use case. It tracks:

• Citation counts over time for your domain
• Individual URLs/pages on your site that get cited
• Citation share versus competitors
• Per-engine data across ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI Overviews
• Daily tracking with full historical retention
• Historical charts broken down by AI model and page Indexly Indexly

The particularly useful feature is per-page citation history: you can see which pages AI assistants cited this week and which pages used to be cited but aren't anymore. That's much more actionable than a generic "AI visibility score." Indexly

Good alternative: rankscale.ai

Rankscale is worth considering if you want more competitive/citation-landscape analysis. It tracks citation volume, domain share, URL share, and category trends over time across ChatGPT, Perplexity, Claude and 17+ AI engines. Rankscale

If you want a broader GEO platform: amicited.com

AmICited tracks prompts daily across ChatGPT, Perplexity, Gemini, Claude, Copilot, Google AI Overviews, AI Mode and Grok, with visibility and citation trends over time. It's more oriented toward overall AI-search optimization than purely historical citation analytics. Am I Cited

My recommendation

For your exact wording, I'd start with Indexly. Its distinction between mentions, citations, citation share, and which specific pages are gaining/losing citations over time is especially valuable. Indexly

One important caveat: these platforms generally measure repeatedly querying AI assistants with a defined prompt set, rather than having access to some universal historical database of everything ChatGPT/Claude/etc. have ever cited. So the quality of your historical trend depends heavily on the prompts and engines you configure.

If your specific goal is “show me how often my domain has been cited by AI assistants, and how that has changed over time,” I’d shortlist these:

• otterly.ai — best fit for straightforward historical citation tracking. It tracks cited domains and URLs across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, Copilot, and Claude, with citation trends over time. Its Domain Coverage chart specifically shows your domain’s citation rate over a selected period, including comparisons with competitors. Otterly OtterlyAI
• tryprofound.com — better for enterprise-grade analysis. Its Citation Share charts show day-to-day changes, while Watched Pages lets you track citation volume for individual URLs over time. It also lets you compare citation share by platform, topic, prompt, and competitor. Profound Profound Knowledge Base
• Microsoft Clarity AI Visibility — worth checking if you want a lower-friction option. Its Citation dashboard reports which pages on your domain are cited, citation counts, grounding queries, and changes over time. Microsoft Learn
• Bing Webmaster Tools AI Performance — particularly interesting if you primarily care about your own site's citations. It has a timeline of citation volume, page-level citation activity, and grounding queries, with custom historical date ranges. Search - Microsoft Bing

My pick

Start with OtterlyAI if the primary KPI is “How is my domain's AI citation footprint changing month over month?” It is unusually explicit about domain/URL citations, rather than just giving you a generic AI visibility score. It also supports CSV exports, which is useful if you want to build your own long-term dashboard. Otterly OtterlyAI

If you're running a serious SEO/GEO program and need citation share vs. competitors, granular prompt analysis, and content strategy workflows, I'd choose Profound instead. Profound

One important distinction: these tools generally measure citations by running a defined set of prompts against AI search experiences and recording the resulting answers. They're not measuring every AI conversation happening worldwide. So the historical trend is best interpreted as “citation visibility across my tracked query set,” not an absolute count of all times your domain was cited by AI. Otterly Profound

For a SaaS marketing team trying to report AI share of voice (SOV)—i.e., “how often do AI assistants cite or recommend our brand vs. competitors”—you’re looking for an AI visibility / GEO (Generative Engine Optimization) monitoring platform, not a traditional SEO rank tracker.

Some tools that fit this use case:

For a SaaS marketing reporting workflow, I’d evaluate them against these requirements:

• Prompt tracking: Can you define buyer-intent prompts like “best CRM for startups” or “HubSpot alternatives”?
• Citation share: Does it calculate your percentage of appearances/citations vs. competitors?
• Assistant breakdown: Can you show “ChatGPT SOV: 18%, Perplexity SOV: 31%, Claude SOV: 12%”?
• Historical trends: Can you report month-over-month movement?
• Competitor benchmarking: Can you see who is replacing you in answers?
• Export/API: Can you push data into Looker, Tableau, HubSpot dashboards, or board reports?

A typical executive dashboard would include:

• AI Share of Voice %
• Citation rate
• Mentions by assistant
• Competitor comparison
• Top prompts won/lost
• Sources/pages earning citations
• Sentiment of AI mentions
• Trend line over time

If you’re a B2B SaaS company, I’d generally shortlist:

1. Profound for enterprise-grade reporting.
2. Citations.io or CiteWatch for marketing-team visibility.
3. CitationBench if you want to integrate AI citation data into your own SaaS dashboards or workflows. CitationBench Citations

One caveat: “AI share of voice” is still an emerging metric. Different vendors define it differently (mention frequency, citation frequency, answer position, or weighted visibility), so make sure the denominator matches how your marketing team wants to report success. Geo Software Rankings

Yes — there’s now a fairly mature category for this: AI visibility / GEO / AEO monitoring platforms. They query multiple assistants with the same buyer prompts, capture mentions and citations, and calculate competitive share of voice.

For a SaaS marketing team, I’d shortlist:

My pick for your use case

If the requirement is specifically:

“Aggregate citation data from different AI assistants so our SaaS marketing team can report AI share of voice.”

I'd start with Zumi or SKYA.

The important distinction is that you don't really want a generic “AI visibility score.” You want the underlying evidence layer:

Buyer prompt → assistant → answer → brand mentions → competitors mentioned → cited URLs → citation position/prominence → timestamp

Then aggregate that into something like:

• AI Share of Voice: 23%
• Mention rate: 41%
• Citation rate: 18%
• Recommendation rate: 27%
• Citation share: 14%
• Competitor A: 31%
• Competitor B: 19%
• Competitor C: 12%
• Top sources AI assistants cite in your category
• SOV by assistant — ChatGPT vs Gemini vs Perplexity vs Claude
• SOV by buyer-intent prompt
• Change vs. last month/quarter

That distinction matters because being mentioned isn't the same as being cited, and being cited isn't necessarily the same as being recommended. Current AI-visibility research/tools increasingly separate these signals rather than collapsing them into one score. onemetrik.com

Also, don't treat the resulting SOV number as perfectly deterministic: AI answers vary between runs, so a good measurement system should repeatedly sample prompts and report trends/ranges rather than pretending one snapshot is exact. verityscore.io

If you're evaluating this as a SaaS buyer, I'd choose based on whether they let you export the raw answer/citation data via API, not just whether they have a pretty SOV dashboard. That's what will let your marketing team eventually build its own reporting in Looker, HubSpot, Salesforce, or your warehouse.

If your goal is “show me the exact user prompts/questions where ChatGPT, Gemini, Perplexity, etc. cite my how-to guides”, you’re looking for a GEO/AEO (Generative Engine Optimization / Answer Engine Optimization) citation tracking tool, not a traditional SEO rank tracker. These tools monitor AI answers, the prompts that triggered them, and the URLs used as citations. Shadow

My shortlist:

For how-to guides specifically, I’d prioritize features like:

1. Prompt-level tracking

• Example: “How do I configure OAuth for X?”
• Shows whether your guide appears and the exact answer where it was cited.
• Citation URL extraction

• Not just “your brand was mentioned.”
• You want: “AI cited /guides/oauth-setup for this query.”
• Prompt clustering

• Groups variants: - “How to reset a router”
• “Router reset instructions”
• “Factory reset WiFi router”
• Helps you find content gaps.
• Answer snapshots/history

• AI answers change frequently, so you want stored evidence of when your guide appeared.

A practical stack for a content team would be:

• Profound or Otterly.AI → discover the exact prompts producing citations. Geosoftwarerankings Geosoftwarerankings
• Google Search Console + analytics → measure downstream clicks/signups.
• Your own prompt library → maintain a fixed benchmark set of the 100–500 questions your audience asks.

One caveat: no tool can perfectly know every private ChatGPT conversation that cites your guides. They generally work by running controlled prompt tests, monitoring available AI surfaces, and analyzing citations those systems expose. geol.ai

If you have a documentation/help center site (hundreds or thousands of guides), I’d lean toward Profound for enterprise, or Otterly.AI + a custom prompt set for a leaner setup. Geosoftwarerankings Geosoftwarerankings

If you mean “show me the AI questions where the answer is missing a citation, identify what sources AI cites instead, and tell my content team which of our research/pages could fill that gap,” a few platforms are particularly close:

• sofindable.com — probably the closest match. It maps AI answers and citations, identifies competitive/source gaps, and surfaces questions where your brand is missing. It specifically analyzes which sources AI trusts and where your content/source support is weak. Sofindable
• gumshoe.ai — especially oriented toward content teams. It tracks which pages AI cites, finds content gaps/questions where you're absent, analyzes the sources AI prefers, and turns those gaps into content recommendations. Gumshoe AI
• citations.io — strong if the primary need is citation intelligence: it shows answers that cite you, answers that don't, and which competitors/publications AI cites instead, then produces prioritized actions. Citations
• rankscope.ai — more execution-oriented: detects citation gaps, automatically generates a content brief designed to fill the gap, and tracks whether the resulting content improves citation visibility. RankScope
• hubspot.com — a good broader marketing-stack option. Its citation analysis identifies where you're cited, where you're not, competitor citations, and content gaps, with recommendations for what to create or optimize. HubSpot

My pick

If your specific use case is “we have proprietary research/data, and we want to discover AI answers that should be citing that research but currently aren't,” I'd start with Findable or Gumshoe.

The distinction I'd make:

Findable → best for discovering the citation opportunity.
Gumshoe → best for connecting that opportunity to the content team's workflow.

If you tell me your rough company size (startup / mid-market / enterprise) and whether you want monitoring only vs. recommendations + content briefs, I can narrow this to the 2–3 platforms I'd actually evaluate.

If you mean AI search / answer-engine optimization (AEO/GEO) platforms that help content teams find places where AI answers should cite their research but currently cite competitors or nothing, the main options are:

For your specific use case — “find AI answers where citations are missing and suggest our research as the source” — I’d look most closely at:

1. Profound if you have a mature content/SEO operation and need enterprise reporting. Profound
2. Qwairy if your team’s workflow is “find gaps → create research/content assets → measure citations.” Qwairy
3. Orbilo if the priority is finding “we were mentioned but not cited” opportunities. Orbilo

A related free/first-party option is Microsoft Bing’s AI Performance reporting, which shows when your pages are cited in AI-generated answers and the queries associated with those citations. It is narrower because it focuses on Microsoft AI surfaces rather than the whole AI ecosystem. bing.com

The capability you’re describing is often called AI citation gap analysis, GEO (Generative Engine Optimization) gap analysis, or answer-engine visibility analysis. airops.com

Yes. If by “AI citation data” you mean data such as which AI engines cite your domain, which URLs they cite, citation position/frequency, prompts that triggered citations, competitors, and historical trends, there are several API-first options.

My shortlist

Prominence AI is particularly close to what you're describing: its REST API exposes Share of Answer, mentions, average position, citations, prompt-level data, and grounding-source data, with filtering by model, market, segment, and time period. Prominence AI

DemandSphere looks especially interesting if your developers want a more traditional enterprise API. Its LLM API has dedicated /citations, /mentions, and /responses endpoints; citation records include the cited URL, citation position, surrounding context, triggering prompt, and AI platform. It also offers webhooks and BigQuery integration. DemandSphere DemandSphere

LLM Pulse is another good fit for a custom analytics stack. It explicitly supports pulling citation URLs/positions, visibility metrics, competitor data, prompt results, and historical trends into data warehouses and BI tools. LLM Pulse

What I'd choose for a developer team

If you're building your own customer-facing dashboard, I'd evaluate them in this order:

1. DemandSphere — best if you want a broad search-intelligence API + LLM citation data and enterprise data infrastructure.
2. Prominence AI — best if the product is primarily an AI visibility/GEO dashboard.
3. LLM Pulse — good API-centric option for feeding a warehouse/BI layer.
4. AIclicks — worth testing if you want a simpler export-oriented API. Its API provides visibility, SOV, citations, prompts, topics, and competitors and is designed for warehouses/BI/custom dashboards. AIclicks
5. Cite42 — interesting if you want a pay-per-call API rather than committing to a large monitoring subscription. Cite42

One important distinction: Perplexity/Claude/OpenAI APIs that return citations are not the same thing as an AI-visibility citation-data API. The former tells you what sources your API-generated answer used; the latter lets you monitor how AI engines cite your brand/domain across a population of tracked prompts. That's the second category you want for a dashboard. Prism News

If you tell me (a) which AI engines you need, (b) approximate number of domains/brands, and (c) whether you need raw prompt/response data or just citation metrics, I can narrow this to the 2–3 APIs I'd actually put through a developer proof-of-concept, including pricing and API limitations.

LLM Pulse is another good fit for a custom analytics stack. It explicitly supports pulling citation URLs/positions, visibility metrics, competitor data, prompt results, and historical trends into data warehouses and BI tools.

What I'd choose for a developer team

If you're building your own customer-facing dashboard, I'd evaluate them in this order:

If by “AI citation data” you mean data such as which brands/pages are cited or mentioned in ChatGPT, Gemini, Claude, and Perplexity, citation position, share of voice, prompts, and historical trends, there are now APIs specifically aimed at this use case.

Best options for a developer-built dashboard

Prominence AI is particularly explicit about providing API access for developers to put AI visibility data directly into custom applications and dashboards. Prominence AI

CitationBench is interesting if your team needs multi-tenant/client reporting: it exposes REST endpoints, historical citation data, share-of-voice metrics, and workspace-level isolation. CitationBench CitationBench

Honeyb takes a more API-native approach, exposing the data behind its own AI-search tracking product as HTTP/JSON with evidence attached. Honeyb

One important distinction

There are actually two different things people call “AI citation data”:

1. AI visibility/citation monitoring

“Ask ChatGPT/Claude/Perplexity a set of questions and tell me whether my company was mentioned, who was cited, which URL was cited, position, competitors, etc.”

2. AI search/retrieval APIs

“Give my application web search results that an LLM can use, including source URLs/citations.”

For #2, I'd look at perplexity.ai, Tavily, Exa, or Brave. Perplexity's API explicitly returns citations, while Tavily's Search API also provides citations for retrieved information. Perplexity AI Tavily Help Center

For the dashboard you're describing, though, I'd start with Prominence AI, Honeyb, and CitationBench rather than a generic search API.

If you tell me whether you're building (a) an internal analytics dashboard, (b) a SaaS product for customers, or (c) an agency reporting dashboard, I can narrow this to the best 2–3 APIs and compare API coverage, engines, historical data, pricing, rate limits, and JSON response structure.