AI Search Console: An AI Citation Tracking Tool for ChatGPT, Claude, Gemini and Perplexity

Google Search Console tells you how a page ranks and how much organic traffic it pulls. It has nothing to say about what happens when someone asks ChatGPT to recommend a tool in your category and your brand never comes up. That is the specific gap AI Search Console is built to close. It is an AI citation tracking tool that measures how often a brand gets mentioned, cited, or recommended inside real answers from ChatGPT, Claude, Gemini and Perplexity, tracked down to the level of individual prompts rather than a single dashboard score.

The product launched on Product Hunt from the team behind search-console.ai, and its pitch rests on a fair point: most teams trying to measure "AI visibility" right now are still doing it by hand, typing prompts into four different chat windows and screenshotting whatever comes back. That doesn't scale past a handful of checks a week, and it produces no trend line, no history, and nothing a client will accept as a report.

What an AI citation tracking tool actually measures

AI Search Console runs a set of real prompts, the kind a buyer would actually type, across the four engines on a schedule, then tracks several things per prompt:

• A visibility score for the brand across tracked prompts, plus movement over time
• Mentions and position inside each AI answer, not just whether the brand appears
• Competitor rankings: which brands the AI prefers and how often
• Source and citation analysis: which domains, pages, and content types the model pulled from to build the answer
• Full AI answer history, so a specific response can be revisited later with its citations intact
• Export to client-ready PDF reports covering prompts, citations, and competitor gaps

The source and citation layer is the part worth paying attention to. It doesn't just say a brand was mentioned, it shows what fed the answer, whether that's a Reddit thread, a comparison page, a review site, or the brand's own docs. For a team deciding where to put content effort next, that is a more useful data point than a single visibility percentage.

The free badge on Product Hunt is misleading

The Product Hunt listing tags this as free, which isn't quite right on the product site itself. What's free is the trial, no card required. After that it runs on three paid tiers: Starter at $45 a month (60 credits a day, one project), Pro at $195 a month (360 credits a day, two projects, marked the most popular tier), and Business at $495 a month (960 credits a day, five projects, aimed at agencies). Usage is metered by credits rather than a flat prompt count, so how many prompts a plan actually supports depends on how those credits get consumed. Anyone evaluating this should run the trial against their own prompt list before picking a tier, since the jump from Starter to Pro is large enough to matter for a small team's budget.

Where the traction actually stands

Worth being straightforward about this. AI Search Console is a young product. As of this writing it has 521 upvotes on Product Hunt and ranked #3 product of the day on its July 30, 2026 launch, with 687 followers and zero reviews posted. That is a genuinely strong initial reception, better than most tools in the same GEO tools category manage, but a good launch day says nothing about retention, support quality, or whether the citation data holds up against manual spot-checks over months of real use. There is no independent user feedback yet to confirm the accuracy claims. Treat the launch numbers as a sign the idea resonated, not as proof the product delivers as advertised.

Who this is genuinely for

This fits an SEO or GEO team, in-house or agency, that already accepts AI answer engines are a real referral and reputation channel and wants a repeatable number instead of a monthly manual check. The client-ready reporting is clearly built for agencies managing several brand accounts who need to show a client something better than a slide of screenshots. It also suits any team trying to work out why a competitor keeps showing up in ChatGPT answers and they don't, since the source analysis points at the actual pages feeding that answer.

It is not for a solo site or small blog with low citation volume. Product Hunt's own comment thread on the launch raises this directly: with too few prompts returning any mention at all, there isn't enough signal for a trend to mean anything. It is also not the right pick for a team wanting broad, general SEO guidance rather than a narrow AI-citation instrument; AIOS Guide's ai-for-seo guide covers that wider ground. Anyone weighing multilingual coverage should confirm it directly with the team before buying, since that came up as an open question in the launch thread rather than a documented feature.

How someone would actually use it

In practice the workflow is: set up a brand and its competitors as a project, load in the prompts a real buyer would type, actual questions rather than keywords, and let the tool run them against the four engines on a schedule. From there, the visibility score and mention trend become the number to watch weekly or monthly, the source analysis becomes the content brief since it shows which page types actually get cited, and the PDF export becomes what goes in front of a client or a boss instead of a folder of screenshots.

For any team already spending time manually checking what ChatGPT or Perplexity says about their brand, this replaces that motion with something that compounds into a trend line instead of a one-off snapshot.

Source: AI Search Console on Product Hunt (producthunt.com/products/ai-search-console) and search-console.ai.