Best AI Citation Tracking Tools 2026: 7 Tools Compared

By Minel Gunesoglu, founder of Is My Brand in AI · Last updated June 18, 2026

TL;DR: An AI citation tracking tool monitors whether AI engines (ChatGPT, Perplexity, Gemini, Google AI Overviews) name your brand in a generated answer. The category splits into four citation-depth tiers: URL cited, domain cited, brand mentioned, and retrieved-but-not-cited, and most tools only measure the top two. Profound leads on enterprise depth; Peec AI (€89/mo) suits in-house teams; Otterly ($29/mo) is the value pick. Start with the free manual check below before paying for any platform.

You came here because checking by hand stopped working. Opening ChatGPT, Perplexity, Gemini and Google AI Overviews to see whether they cite your pages is fine once; doing it weekly, several times per question, across a competitor set, is a job nobody has time for. A dedicated AI citation tracking tool automates that grind, but the category is young, prices run from free to enterprise custom, and most "best tools" lists are written by the vendor at number one. This page is the honest version: seven tools, what each actually tracks, approximate pricing, and the citation-depth distinction that decides which one you need. One scope note up front: this page is about cross-engine citation depth across every major AI surface. For ChatGPT-only brand monitoring see best ChatGPT brand monitoring tools, and for Gemini-specific tracking see our Gemini rank tracker comparison. For the wider platform landscape, the best GEO tools roundup is the parent comparison.

One disclosure that belongs right here: some links on this page may be affiliate links, and the rankings are by merit, not payouts. I name the editor's picks (Profound, Peec AI, Otterly) plainly so you can judge for yourself.

What Is AI Citation Tracking?

AI citation tracking is the practice of monitoring whether AI engines name your brand, and link to your source pages, inside the answers they generate. When someone asks ChatGPT, Perplexity, Gemini or a Google AI Overview a question, the engine writes one synthesized answer and attaches a handful of sources. AI citation tracking measures, on a schedule and across a set of buyer questions, how often you are that cited source, where you appear in the answer, and how you compare to rivals named alongside you. The unit of measurement is prompt-level, not keyword-level: for a given question, are you cited, in what form, and against whom.

The reason this became its own software category in 2026 is that AI answers increasingly sit between a buyer and your website. A prospect can get a complete recommendation inside an AI answer and never click a blue link, so your standing inside that answer, your citation rate and your share of voice in AI answers, is the thing that now decides whether you are considered at all. A citation rate is simply the percentage of tracked questions where the engine cites you; share of voice in AI answers is your slice of all brand citations for a topic. Both are invisible to classic analytics, which is exactly the gap these tools fill.

Brand Mention vs AI Citation: Why the Difference Decides Which Tool You Need

The single most common mistake buyers make in this category is treating "my brand got mentioned" and "my brand got cited" as the same result. They are not, and the difference changes which tool is worth your money. A brand mention is your name appearing in the prose of an answer ("tools like Acme and Globex are popular"). A cited source is your specific page or domain attached as the reference the engine points to, the link a reader can actually follow. Both matter, but they answer different questions: a mention tells you the model knows you exist; a citation tells you the model is sending attention, and potentially traffic, to your pages.

Here is what that gap looks like in practice (an illustrative scenario, not measured first-party data). Picture a project-management startup that runs its buyer questions through ChatGPT and is thrilled to find its name in answer after answer, dozens of appearances across a week of prompts. A mention counter would paint that dashboard bright green. But when the team reads the actual answers, not one of those appearances carries a source link back to its site. Every single appearance is a Tier-3 brand mention. The Tier-1 URL-cited rate is exactly zero. The model knows the company exists, recommends it by name, and sends it no traffic and no source credit whatsoever, while a rival whose page is linked collects every click the answer generates. The healthy-looking number was measuring the wrong thing.

This brand mention vs citation gap is why a cheap mention counter can quietly mislead you. A tool that only logs "named: yes/no" will show a healthy dashboard while you earn zero clickable citations, because being named in passing is not the same as being the source the answer is built on. The tools worth paying for separate the two and, ideally, show you the surrounding context so you can tell a flattering citation from a damaging one. When you compare the seven tools below, this is the first capability to interrogate: does it distinguish a mention from a citation, or does it blur them into a single number?

Citation Depth: The 4-Tier Taxonomy That Separates Real Trackers from Mention Counters

Here is the framework no other roundup in this category gives you, and it is the one that should drive your purchase. "Being cited" is not a yes-or-no state. AI citations come in four distinct depths, and a tool is only as useful as the depths it can actually report. Sort every tool you consider against these four tiers.

Tier 1, URL cited. Your exact page is the named source link in the answer. This is the strongest result: the engine points readers to a specific URL of yours, and that page receives both the reader's visit and the source attribution. It is also the hardest depth to measure well, because the tool has to capture which page, not just which brand.

Tier 2, domain cited. Your brand or domain is named as a source, but no specific URL is attached, or the link points at your homepage rather than the relevant page. You are credited, but the engine has not pinned the answer to a particular piece of your content. Useful, weaker than a page-level citation, and a signal that you have brand authority the engine trusts even where individual pages are thin.

Tier 3, brand mentioned. Your name appears in the answer's prose with no link at all. The model knows you, but it is not sending anyone to your site. This is the depth most "mention tracking" tools stop at, and the easiest one to over-celebrate.

Tier 4, retrieved-but-not-cited. The hardest tier to see and the most strategically important. Your content was pulled in and shaped the answer, but you are invisible in the final output: no name, no link. The model learned from you and gave the credit to someone else. Few tools surface this at all, and the ones that touch it (Profound's prompt-and-retrieval panels are the clearest example) are the deepest in the category.

Two more signals sit on top of these tiers and matter just as much. First, position in the answer: being cited in the opening sentence is worth far more than being buried in a closing list, and a serious tracker reports where in the answer you land, not just whether you appear. Second, cross-engine divergence: you can be cited by ChatGPT and absent from Perplexity for the identical query, because the engines retrieve from different places. A tool that reports only one engine, or averages them into a single blurred score, hides exactly the divergence you need to act on. The comparison table below scores each tool on which of these four tiers it actually reports, because that, more than price, is what separates a real citation tracker from a mention counter.

How to Track AI Citations (Step-by-Step)

You do not need expensive software to start tracking AI citations; you need a repeatable method. The manual version is four steps. First, build a prompt set: the real buyer questions where you want to be cited ("best project management tool for agencies", "what is the cheapest CRM for startups"). Second, run each question across the engines that matter to you, ChatGPT, Perplexity, Gemini and Google AI Overviews, and record three things, not one: whether you are named, whether you are linked (and which page), and your position in the answer. Third, run each question several times rather than once, because the engines are non-deterministic and a single run is an anecdote, not data. Fourth, log it on a cadence (weekly is a sensible refresh cadence to start) so you can see movement instead of a one-off snapshot. That manual pass is your free baseline for step two; the paid tools below automate the whole loop.

The honest reason people graduate from manual to paid is the false positive and false negative problem. A zero-citation result can be a knowledge-cutoff or indexing lag rather than a true absence, especially for a brand launched in the last couple of months, and a "you're cited" result can be the model confusing you with another company that shares your name. A context excerpt, the actual sentence around your citation, is what lets you catch both, which is why the better tools show the surrounding text rather than a bare yes or no. Two surfaces deserve their own walk-through, because their citation mechanics differ enough to trip up a tracker that treats all engines the same.

"I got zero citations, now what?" A blank result is a starting point, not a dead end, and it usually has one of two causes, each with a clear next step. The first is knowledge-cutoff or index lag: if your brand launched recently or is rarely mentioned anywhere, the engines simply have not caught up yet, so wait roughly four to six weeks and re-check before concluding anything. The second is an entity-recognition gap: if your brand name is brand-new or generic enough that the model cannot tell it apart from ordinary words, the fix is to give the model something solid to anchor on, so establish a Wikipedia or Wikidata presence and add schema markup to your site so the engines can recognize you as a distinct entity. Re-test after each change rather than altering everything at once, so you learn which lever moved the needle.

Google AI Overviews: How Citation Tracking Works

Google AI Overview citations work differently from chatbot citations, and tracking them reflects that. An AI Overview is the summary box at the top of an otherwise normal Google results page, and it leans heavily on what already ranks in classic Google Search, lifting a passage from a page that is already index-visible and attaching a link to it. So a page you optimized to rank organically has a real shot at becoming an AI Overview citation, which makes this the most measurable surface of the four. To track it, you watch which of your pages get pulled into the Overview box for your target queries and in what position. Google's own Search Console now reports impressions and clicks for AI features in Search, which maps to the AI Overviews surface, but it does not name your competitors or show the answer text, so it is complementary to a citation tracker rather than a replacement.

It is worth separating two Google surfaces that searchers often blur together, because the tools cover them differently. Classic AI Overviews are the summary box described above, and they pull from pages already ranking in Google's index. Google AI Mode is a distinct, separate surface: a conversational, multi-turn, web-grounded experience closer to a chatbot than to a results page, and it can return citations that classic AI Overviews never would for the same question. Most trackers in this comparison cover classic AI Overviews; coverage of AI Mode specifically is rarer, and where it exists it is usually an upgrade rather than base coverage (Otterly, for instance, sells AI Mode as a paid add-on). If AI Mode is where your buyers actually search, confirm a tool covers that surface by name, not just "Google", before you buy.

Perplexity Sources Panel: Tracking Your Source Appearances

Perplexity makes citation tracking unusually transparent because it shows its work. Every Perplexity answer carries a numbered Perplexity sources panel listing the exact pages it drew from, so tracking your citations there means monitoring whether your URLs appear in that panel, at what rank within it, and for which questions. This is the cleanest place to see Tier 1 URL-cited results in the wild, because the source link is explicit rather than buried in prose. The practical workflow is to run your buyer questions in Perplexity, read the sources panel, and record which of your pages made the list and which competitor pages outranked them, exactly the per-engine, page-level detail the stronger tools below capture automatically.

Best AI Citation Tracking Tools: Quick Comparison Table

The table below is the core of the page. The "Citation depth" column is the one to read first: it scores which of the four tiers (URL cited, domain cited, brand mentioned, retrieved-but-not-cited) each tool actually reports, because that, not the sticker price, decides whether a tool answers the question you are paying it to answer.

Pricing, engine coverage and citation-depth support are approximate and current as of June 2026; verify on each vendor's own site before you buy, because tiers in this category change fast and citation-depth claims in particular are easy to overstate. The Engines column shows a count for quick scanning; each tool's full engine list is in its section below. Where pricing is gated behind a demo (Bluefish AI, Brandlight, AirPulse), no public self-serve number exists, so any figure shown is a third-party estimate to confirm directly. Now the honest, tool-by-tool read, starting with the depth leader.

1. Profound — Best for Enterprises

Best for: enterprise brands that need the deepest citation analytics money can buy.

Profound is the depth leader in this category, and it is not especially close. It raised a $96M Series C at roughly a $1B valuation, announced February 24, 2026 and led by Lightspeed, and says it serves 700-plus enterprise customers, including more than 10% of the Fortune 500, making it the most-funded company in the space. What you pay for is citation data nobody else ships: URL-level citations, plus prompt-and-retrieval panel data that gets at the retrieved-but-not-cited tier almost no other tool can see, across 10-plus engines.

What it tracks: all four citation depths, including the rare retrieved-but-not-cited tier, with URL-level granularity, position-in-answer data, prompt-panel insight into the questions real users send AI engines, and competitor benchmarking, across the broadest engine set here.

Pricing

Sales-led and custom; there is no public self-serve number and every plan starts with a sales call. Budget for enterprise-tier pricing, not a credit-card subscription. Confirm scope and cost directly with their sales team (as of June 2026).

Pros and Cons

• Pros: Deepest citation analytics in the category, URL-level data, the clearest read on retrieved-but-not-cited content, broadest engine coverage, enterprise-grade reporting.
• Cons: No free tier and no self-serve pricing; every engagement is a sales conversation. Overkill, and overpriced, for a single small brand or a solo founder.

Who It's For

Enterprise brands operating at scale that need URL-level citation depth and can absorb custom pricing. If you are one person checking a handful of prompts, this is more tool than you need.

2. Peec AI — Best for In-House Teams

Best for: in-house marketing teams and agencies that want serious multi-engine citation tracking without enterprise pricing.

Peec AI is the tool I would point most in-house teams to first. The Berlin startup raised a $21M Series A in November 2025, led by Singular, and it built a clean, focused product that runs your prompts daily across ChatGPT, Perplexity and Google AI Overviews (with Claude and Grok as paid add-ons) and reports citation presence, position and sentiment without burying you in features you will not use. It is also one of the few vendors publishing original research on how citations behave. Peec AI's listicle-rank study, which analyzed roughly 200,000 AI responses across 8 engines and is published on SSRN, found that ranking #1 in a cited listicle drives up to +16.5 percentage points of visibility for B2B SaaS brands, and, notably, that once you appear in a cited list, exact position matters less in that category. The practical takeaway: getting into the cited list is the hard part; obsessing over moving from #3 to #1 inside it is often the wrong fight.

What it tracks: daily multi-engine citation visibility, position within the answer, brand mention vs cited-source distinction, sentiment, and share of voice against named rivals.

Pricing

From roughly €75-89/mo for the entry tier (TechCrunch lists a €75/mo plan for 25 prompts), with unlimited seats on every plan (rare, and a real saving for a growing team) and daily refresh. Higher tiers add more prompts, projects and engines. Verify current pricing on the vendor's site (as of June 2026).

Pros and Cons

• Pros: Fast onboarding, daily refresh cadence, unlimited seats, position and sentiment built in, transparent self-serve pricing, original published citation research.
• Cons: It is a tracker first; it shows you where you stand better than it tells you exactly what to do next, and top engines cost extra on top of the base.

Who It's For

In-house marketers and agencies that want strong multi-engine citation tracking and shared seats without a sales call. The pragmatic default for most serious teams.

3. Otterly — Best Value

Best for: solo marketers and small teams who want real automated citation tracking without an enterprise contract.

Otterly is the most approachable paid entry into AI citation tracking and the editor's value pick. It was named to Gartner's "Cool Vendors in AI for Marketing" list in October 2025, and its Lite plan starts at $29/mo (about $25/mo billed annually) for 15 prompts, by far the gentlest on-ramp in this comparison. It tracks citation presence, average position and a share-of-voice metric across Google AI Overviews, ChatGPT, Perplexity and Copilot, refreshed on roughly weekly cycles.

What it tracks: citation presence, position in the answer, share of voice in AI answers, and sentiment across its core engines, with scheduled reports that flag when results move.

Pricing

From $29/mo (Lite, 15 prompts, about $25/mo billed annually) up to higher tiers for more prompts. Note that Gemini and Google AI Mode are a paid add-on rather than base coverage, so the headline price does not include every engine. Verify current pricing on the vendor's site (as of June 2026).

Pros and Cons

• Pros: Cheapest real starting price, simple to use, 14-day trial with no card, share-of-voice and position built in, scheduled reports.
• Cons: Weekly-ish refresh rather than daily, low prompt counts on the cheap tier, and Gemini and Google AI Mode as paid add-ons, so the cheap sticker narrows once you add the surfaces you want.

Who It's For

Solo marketers, SMBs and freelancers graduating from a free one-time check to light ongoing citation tracking without spending much.

4. Bluefish AI — Citation Sources + Favorability in One View

Best for: enterprise teams that want citation-source tracking combined with how favorably AI engines describe them.

Bluefish AI is an enterprise GEO and AI-marketing platform that watches the sources behind AI citations alongside three signals most trackers skip: visibility, favorability and accuracy. It covers a broad engine set, ChatGPT, Perplexity, Gemini, Google AI Overviews, Claude and Copilot, and its angle is showing not just whether you are cited but whether the answer represents you fairly and correctly. (For context, it reportedly raised a $20M Series A in August 2025, led by NEA.) Pricing is gated: there is no public self-serve number, so you book a demo to get a quote.

What it tracks: citation sources plus visibility, favorability and accuracy across six major engines; confirm during the demo whether it reports URL-level (Tier 1) citations or stops at domain and mention level on your plan.

Pricing

Gated behind a demo; pricing is sales-led with no public self-serve number, so request a quote and scope directly (as of June 2026).

Pros and Cons

• Pros: Broad six-engine coverage, citation-source tracking, plus favorability and accuracy signals beyond a bare citation count, enterprise-oriented.
• Cons: No public pricing and no self-serve tier; you commit to a demo to learn the cost, and exact citation-depth reporting should be confirmed for your plan.

Who It's For

Enterprise teams that want citation sources plus a read on accuracy and favorability and can work with sales-led, demo-gated pricing.

5. Brandlight — Citation Tracking With Sentiment

Best for: brands that want citation monitoring with sentiment, especially flagging citations that frame them negatively.

Brandlight focuses on citation monitoring with a sentiment layer, so you see not just whether AI engines cite you but how they characterize you, and it specifically flags negative-sentiment citations. It covers ChatGPT, Gemini, Perplexity, Copilot and Grok. For brands whose name is reputation-sensitive, that flagging is the differentiator: a citation that frames you badly is one you want surfaced, not just counted. Pricing is gated behind a demo on the site (third-party listings report roughly $199-750/mo, which you should confirm directly rather than treat as official).

What it tracks: citations and sentiment across five engines, with negative-sentiment citations flagged; confirm whether it reaches URL-level (Tier 1) citation depth on your plan.

Pricing

Gated behind a demo; third-party listings report roughly $199-$750/mo, but there is no public self-serve price, so confirm directly (as of June 2026).

Pros and Cons

• Pros: Sentiment built into citation monitoring with negative-citation flagging, useful for reputation-sensitive brands, five-engine coverage including Grok.
• Cons: Pricing is gated and only estimable from third-party listings; citation-depth granularity should be confirmed for your plan.

Who It's For

Reputation-conscious brands that want to know not only whether they are cited but how they are described, and want negative citations flagged early.

6. AirPulse — AI-Native Mention + Citation Tracking

Best for: teams wanting AI-native brand mention and citation tracking across major LLMs, with a free way to test first.

AirPulse is built AI-first to track brand mentions and citations across the major large language models, covering ChatGPT, Claude, Perplexity, Gemini and Copilot. Built by the team behind Airmeet and SOC 2 Type II certified, it is aimed at teams that want monitoring designed for generative answers rather than retrofitted from a social-listening tool. A useful detail for buyers: it offers a free, no-card analysis plus a demo, so you can see your own data before any conversation about budget. Paid tiers exist but are not publicly priced.

What it tracks: brand mentions and citations across five major LLMs; confirm whether it reaches URL-level (Tier 1) citation depth on your chosen plan.

Pricing

A free no-card analysis is available to start; paid tiers are gated and not publicly priced, so confirm scope and cost directly (as of June 2026).

Pros and Cons

• Pros: AI-native design focused on the LLM answer surface, five-engine coverage, SOC 2 Type II certification, a genuinely free no-card analysis to start.
• Cons: Paid pricing is not public; exact citation-depth reporting on paid tiers should be confirmed directly.

Who It's For

Teams wanting an LLM-focused, AI-native mention-and-citation tracker who want to see their own data free before discussing a paid plan.

7. HubSpot AI Search Grader — For the HubSpot Ecosystem

Best for: teams already in HubSpot who want a free starting grade and answer-engine monitoring inside a familiar platform.

HubSpot's relevant offering here is not its CRM generally but its specific answer-engine monitoring features plus the free AI Search Grader. The AI Search Grader is a genuinely useful free entry point: you enter your brand and it returns a read on how AI engines (ChatGPT-led) represent you, including share of voice and sentiment, with no cost to start. For teams already living in HubSpot's marketing tools, folding answer-engine monitoring into that ecosystem reduces the number of separate logins. Treat the free grader as a one-time snapshot rather than continuous, scheduled tracking.

What it tracks: brand presence and mentions in AI answers via the free AI Search Grader, with deeper answer-engine monitoring available inside HubSpot's paid marketing tooling.

Pricing

The AI Search Grader is free; deeper monitoring lives within HubSpot's Marketing Hub subscription tiers. Verify current Marketing Hub pricing on HubSpot's site (as of June 2026).

Pros and Cons

• Pros: A genuinely free AI Search Grader to start, integration with the wider HubSpot stack, share-of-voice and sentiment in the free grade.
• Cons: The free grader is a snapshot, not scheduled tracking; deeper monitoring assumes you are (or become) a HubSpot customer, and citation depth is lighter than the AI-native specialists.

Who It's For

Teams already in the HubSpot ecosystem, and anyone wanting a free one-time grade before deciding whether to pay for a dedicated tracker.

Profound vs Peec AI: Head-to-Head

These two come up most often when a buyer is choosing between "the deepest data" and "the best team value", so they deserve a direct Profound vs Peec AI comparison. The honest split is depth versus accessibility. Profound wins on raw citation depth: URL-level citations, prompt-and-retrieval panels that get at the retrieved-but-not-cited tier, 10-plus engines, and competitor data nobody else ships. If you are an enterprise that needs to know not just whether you are cited but which exact pages, and which content shaped answers you were left out of, Profound is the tool, and you will pay enterprise, sales-led pricing for it.

Peec AI wins on accessibility and team economics. At roughly €75-89/mo with unlimited seats and a daily refresh across ChatGPT, Perplexity and Google AI Overviews, it gives an in-house team or agency genuine multi-engine citation tracking, position data, and share of voice without a sales call or a per-seat multiplier. It does not reach Profound's retrieved-but-not-cited depth, and its base engine list is narrower, but for the large majority of teams that is capacity they would never fill. The decision rule: choose Profound if URL-level depth and the retrieved-but-not-cited tier are the reason you are buying and budget is not the constraint; choose Peec AI if you want strong, daily, multi-engine citation tracking your whole team can use at a transparent price. Most readers should start with Peec AI and only move up to Profound when they have hit its ceiling.

Free vs Paid AI Citation Trackers: When to Upgrade

The free-vs-paid question has an honest threshold, and it is worth naming rather than papering over. The free manual method above genuinely covers you up to a point: when you are proving the problem exists, sanity-checking after a content push, or watching a handful of prompts occasionally. Below that ceiling, paying for a platform is buying capacity you cannot fill. It is also worth saying that none of this is niche frustration; practitioners in SEO communities like r/SEO and r/marketing keep surfacing the same two complaints this page is built around, that one manual check is not tracking because the engines are non-deterministic, and that entry-tier sticker prices quietly hide single-engine limits. If those two annoyances brought you here, you are in good company. Three buyer tensions decide when you cross the line.

First, "my manual check showed my brand once, so I'm covered." Not quite, because the engines are non-deterministic: ask the same question twice and the brands cited can differ, so one run is an anecdote, not a measurement. Once you need to run many prompts several times each, weekly, across more than one engine, doing it by hand stops being realistic, and that time ceiling, not a missing feature, is what a paid tracker buys you.

Second, "I already track links, so I'm set." AI citations are orthogonal to your link profile. You can rank #1 in classic search and never be cited in an AI answer, and a brand with almost no inbound links can be named because of a strong Wikipedia entry or entity authority the model trusts. Link-tracking tools measure the connections between websites; citation trackers measure whether AI answers point to you. Different question, different tool, and tracking one tells you nothing reliable about the other.

Third, the sticker-price trap. Entry tiers in this category are often single-engine or single-surface, so the real cost to cover all four engines (ChatGPT, Perplexity, Gemini, Google AI Overviews) frequently runs 1.5 to 3 times the headline number once add-ons are stacked. Otterly's Gemini and AI Mode add-on is the clearest example. Always add the surfaces you actually came for to the base price before you compare two tools.

One more distinction decides whether a tool even measures what you care about: AI search monitoring vs LLM monitoring. Some tools query the model directly (an LLM monitoring approach, closer to what the base model "knows"), while others trigger a live web-search-grounded answer (AI search monitoring, closer to what a user with browsing on actually sees). The same brand can be cited in one mode and absent in the other for the same question, so confirm which mode a tracker uses, and ideally that it covers both, before you trust its citation rate. For tools that cover visibility beyond citation tracking specifically, our best AI search visibility tools roundup is the wider view, and the AI search visibility overview frames why measuring every engine together beats optimizing one in isolation.

Frequently Asked Questions

What is AI citation tracking? AI citation tracking is monitoring whether AI engines (ChatGPT, Perplexity, Gemini and Google AI Overviews) name your brand and link to your pages inside the answers they generate. It works at the prompt level: for a set of buyer questions, run on a schedule and ideally several times each, it measures whether you are cited, in what form (a clickable source versus a passing mention), where you appear in the answer, and how you compare to rivals. The point is to make visible the standing inside AI answers that classic analytics cannot see.

What is the difference between AI citation tracking and link tracking? They measure different things. Link tracking watches which websites link to yours, a signal in classic search ranking. AI citation tracking watches whether AI-generated answers cite you as a source. The two are orthogonal: you can rank #1 with a strong link profile and still never be cited by ChatGPT, and a brand with few inbound links can be cited because of strong entity authority or a Wikipedia entry. If your goal is to understand your presence inside AI answers, a link-tracking tool will not tell you; you need a citation tracker.

How do I track AI citations? Two ways, depending on volume. Free: build a prompt set of buyer questions, run each across ChatGPT, Perplexity, Gemini and Google AI Overviews several times, and record whether you are named, whether you are linked and which page, and your position in the answer — that manual pass is your free baseline. Paid: a tool like Peec AI (€89/mo) or Otterly ($29/mo) automates that loop across engines on a schedule and flags movement. Because the engines are non-deterministic, any reliable method checks each prompt multiple times rather than once.

How do I track AI Overview citations? Watch which of your pages get pulled into Google's AI Overview box for your target queries, and in what position, since AI Overviews lean on pages that already rank in classic Google Search. Google's Search Console reports impressions and clicks for AI features in Search, which maps to the AI Overviews surface, but it does not name competitors or show the answer text, so pair it with a citation tracker (Otterly, Peec AI and Profound all cover Google AI Overviews) to see who is cited alongside you and which exact pages win the citation.

How do I track citations and mentions on Perplexity? Perplexity makes this the most transparent surface because every answer shows a numbered sources panel listing the exact pages it used. Run your buyer questions in Perplexity, read the Perplexity sources panel, and record which of your URLs appear, at what rank within the panel, and which competitor pages outrank them, that is your page-level (Tier 1) citation data. To automate it across many prompts, the AI-native trackers here (Otterly, Peec AI, Profound) all cover Perplexity citations and log the source-panel appearances for you on a schedule.

Which tools track AI search citations? The dedicated AI-native trackers do it best: Profound (deepest, enterprise, URL-level and retrieved-but-not-cited), Peec AI (in-house teams, €89/mo, daily), and Otterly (best value, $29/mo) are the core picks, with Bluefish AI, Brandlight, AirPulse and HubSpot's AI Search Grader as further options to verify. Social-listening platforms like Mentionlytics, Brand24, and Meltwater track web, news, and social mentions but do not monitor citations inside AI answers, so they fall outside this comparison.

Is there a free AI citation tracker? There is no full-featured free monitoring platform; ongoing scheduled, multi-engine tracking costs money to run. But free routes exist: the manual method above (run your own prompts across the engines and record who is cited), HubSpot's free AI Search Grader, AirPulse's free no-card analysis, and no-card trials from Otterly and Peec AI. The honest sequence is to start free to prove the gap, then pay for a tracker only once the volume makes doing it by hand impractical.

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This guide is part of our series on AI search visibility. Written by Minel Gunesoglu, founder of Is My Brand in AI · more about us. Some links above may be affiliate links; rankings are based on merit. Funding figures (Profound, Peec AI, Bluefish AI) and the Peec AI listicle-rank study are attributed to their reported sources; pricing is approximate and was current as of June 2026, and gated pricing (Bluefish AI, Brandlight, AirPulse) should be confirmed directly with each vendor. Reviewed June 18, 2026. Connect on LinkedIn.