Free AI Visibility and Answer Engine Monitoring Tools

Yes, you can monitor your brand in AI answer engines for free, within limits. You have three real options: self-host an open-source project for multi-engine tracking, use a free tier of a paid tool (usually one engine), or check the engines by hand. Each swaps the subscription for your own time or infrastructure. Free site audits cover a fourth job: telling you whether the engines can reach and recognise you in the first place.

Answer engine monitoring and AI visibility tracking are the same job under two names: watching whether ChatGPT, Claude, Perplexity, Gemini, and Google's AI Overviews mention and cite your brand. Below is every free and free-tier option, what it covers, and where each one stops.

Key takeaways

Free tools vary more than paid ones, so a few things decide whether one fits.

Here is every way to track your brand in AI answers without a subscription, from a self-hosted open-source project to a one-off audit. The table shows what each option covers before the sections below go deeper.

AI products and prices change fast, so confirm current details with each vendor before you rely on them.

The closest thing to free ongoing tracking is a project you run yourself. OneGlanse and GEO/AEO Tracker are both MIT-licensed, cover several engines, and charge no licence fee, so the only bill is your own infrastructure and the model API usage. The trade is upkeep: you own the engine coverage, the parsing, and keeping it working as the APIs change, and most of these projects are maintained by one person.

For the developer-focused view of this category, including what each project covers and how actively it is maintained, see our roundup of open-source AI visibility tools.

Recall is a paid, managed platform, but its site audit is free and needs no account. It checks the things you can establish from your own site: whether AI crawlers are allowed to fetch your pages, whether an engine has enough to tell which company you are, and whether your pages carry enough substance to be answered with.

That covers three of the four reasons a brand goes missing from AI answers, and it is worth running first, because two of them are fixed on your own site in an afternoon. The fourth reason, that the engines are reading sources which never mention you, can only be established by measuring the answers themselves, and that is the part that costs money: every answer collected is a paid API call, whoever runs it.

Some paid tools include a genuinely free tier, but they cap it tightly. AirOps has a free tier that tracks ChatGPT only; broader engine coverage moves you to a paid plan. It is a fair way to watch a single engine without any setup, but a one-engine read misses where a lot of your buyers actually ask, since Perplexity, Gemini, and Google's AI Overviews go untracked.

Most other well-known tools offer a free trial rather than a free tier. Profound, Peec AI, Scrunch, Otterly, and AthenaHQ let you try the product for a limited window, then bill you. Two SEO suites price their AI modules openly: Ahrefs Brand Radar starts at $129 per month and the Semrush AI Toolkit at $139.95 per month, both alongside their core subscriptions. Read the fine print, because a free trial ends, and a free tier in this category usually means one engine and a small prompt allowance.

Not every free tool tracks mentions over time. Some audit your site once and hand back a score. HubSpot's AEO Grader is free and checks your content structure, schema markup, and AI readability, then returns recommendations for making pages easier for answer engines to quote.

A grader answers a different question than a monitor. It tells you whether your pages are built to be cited, not whether ChatGPT or Perplexity actually cite them right now. Run one to fix the on-page basics, then use a monitor to see whether the fixes move your visibility. The two are complements, not substitutes.

You can measure answer engine visibility with no tool at all. Open each engine, ask the questions your buyers ask, in both the base model and its search mode where that exists, and record whether the answer names or links to you. Note the competitors it names instead. If you sell project-management software, for instance, ask "What are the best project-management tools?" and "What is a good Asana alternative?", then check whether your brand shows up and which sources the engine cites. Repeat on a schedule, because the same prompt returns different answers between runs.

Manual checking works for a one-off read or a very small brand. It breaks down as you add engines and prompts. There is no history, no competitor share of voice over time, and the checking itself eats the hours you could spend fixing the gaps it surfaces. For a repeatable version of this loop, see how to track your brand in AI search.

If you write code, you can script the loop. Send your prompt set to the model APIs, directly or through a router like OpenRouter, parse each answer for your brand name and any links to your domain, and log the results over time. A first version is not hard to stand up.

The cost shows up later, in maintenance. You own the engine coverage, the parsing rules, the storage, and the reporting, and you keep all of it working as the models and their APIs change. Self-hosting an existing open-source project gives you the same loop already built, which is why most teams that want a free monitor start there instead of from scratch. Whichever route you take, store the full answer text rather than a yes or no, or you will not be able to explain later why a number moved.

Free splits into two very different things, and the gap matters. A free tier is hosted and easy to start, but narrow: with AirOps you get one engine, ChatGPT, and you upgrade to see the rest. An open-source tool you self-host is the opposite. It asks for setup, then gives you every engine the project supports at no software cost, with the model API bill landing on you instead of a vendor.

So the honest summary is this. Nothing here is genuinely $0 once you are tracking answers on a schedule, because collecting an answer costs money whoever does it. Self-hosting an open-source project removes the licence fee, not the bill. Free tiers are fine for watching a single engine. Graders and site audits fix your pages once. Manual checks cover the occasional spot-check. If you want breadth and history without running anything yourself, that is what the paid tools sell, and you can weigh them in our best AEO tools roundup.

Profound and Peec AI are among the most searched paid answer engine tools, and both run as subscriptions rather than free products. If you want their core job, tracking mentions and citations across engines with competitor benchmarking, without the subscription, the closest route is a self-hosted open-source project. You give up breadth and take on upkeep, and you still pay the model API usage directly.

There is no free tier of Profound or Peec AI to fall back on; both offer time-limited trials. So a genuine free alternative is not a cheaper hosted plan, it is a self-hosted open-source tool, or the manual and DIY methods above for lighter needs. See the wider AI visibility software hub to compare where each paid and free option fits.

You can stand up a free monitoring routine in an afternoon.

Free options hold up until they don't, and the limit is almost always scale. The signals to change: more engines than a free tier covers, more prompts than you can check by hand, a need for history and competitor share of voice, or simply not wanting to run infrastructure yourself.

At that point you have two moves. Self-host an open-source tool and stay free but hands-on, or pay for a managed tool and buy back the time. Either beats guessing in a channel that increasingly decides how buyers find you. To compare the paid options, see the best AI visibility tools roundup.