Best AI visibility tools in 2026, comparedTen trackers compared on engines, standout features and starting price

The best AI visibility tools are Otterly.AI and Rankscale for a cheap first test and wide engine coverage, Omnipresence if you want the chain of searches that produced each response and the fix handed to your own agent, Scrunch, AthenaHQ, Goodie and Profound for mid-size and enterprise brands, and the Semrush and Ahrefs add-ons if you already pay for one of those suites. An AI visibility platform shows you whether the models your buyers ask recommend you, and every tool here does that job in a different way.

We judged these on five things: which AI engines your buyers actually use, what you get to see behind an answer, the sample size and whether the rate carries a confidence band, whether it separates a recommendation from a passing mention, and who does the work after the measurement. Prices and engine lists are what each vendor showed on its pricing page on 12 October 2026.

The best AI visibility tools at a glance

Focused trackers for most teams

These are the best AI visibility tools for most teams: published prices, the core engines, and a sample big enough to trust.

Otterly.AI

Best for: small budgets and a first test

Otterly.AI is the cheap, published-price way in, at $29 a month on its pricing page with no sales call. It’s for a small team running its first test of whether AI search mentions it at all.

Pros

• Published price, no sales call
• ChatGPT, Google AI Overviews, Perplexity and Copilot on every plan

Cons

• 15 prompts a month on Lite, a small sample
• Claude, Gemini and AI Mode are paid add-ons

Rankscale

Best for: wide engine coverage on credits

Rankscale goes wide on engines for a low entry price. Its pricing page lists Essentials from $17 a month billed yearly, Pro at $99 a month with 1,200 credits, up to Enterprise at $780.

One credit is roughly one check, and it covers ChatGPT, Gemini, Perplexity, Claude, DeepSeek, Mistral, Grok, Copilot, AI Mode and AI Overviews. That suits a team tracking engines most other tools don’t cover yet.

Pros

• The widest engine list here, including AI Mode and AI Overviews
• A real published price from $17 a month

Cons

• Credit maths: Claude and some engines cost more credits per check
• Price scales fast as you add prompts

Omnipresence

Best for: teams that work with their own agent

Omnipresence is the one that shows you the chain behind each answer. It tracks exactly four assistants, ChatGPT, Claude, Gemini and Perplexity, and for every prompt it records the fanout queries the assistant ran, the sources those queries pulled back, and pages retrieved but never cited.

The rate carries a Wilson confidence interval, control prompts stay unworked so a lift can be attributed, and it separates a recommendation from a passing mention. Plans start at $19 a month on Starter, $69 on Pro and $239 on Agency, billed annually, with a 7-day trial on Pro.

On Pro and up, two-way Model Context Protocol (MCP) hands the target and the method to your own agent, with a work log of what changed.

Pros

• The chain: fanout queries in run order, sources pulled back, retrieved-but-not-cited pages
• A rate with a confidence band, plus control prompts so the lift is attributable
• Two-way MCP on Pro and up, so your own agent can act on what it finds

Cons

• Four assistants only, no AI Overviews or AI Mode tracking
• You bring your own OpenRouter or OpenAI key and pay the model cost at list price
• Top-choice data is partial

Peec AI

Best for: focused daily tracking without a sales call

Peec AI is a focused daily tracker. Its pricing page lists four plans, Starter through Enterprise, but it doesn’t publish a USD price, so you have to start a plan or talk to them to find out.

It tracks ChatGPT, Perplexity and Gemini with an AI Mode tracker, and gives you role-based per-project permissions. It’s for a team that wants daily tracking without a demo.

Pros

• Daily tracking with role-based, per-project permissions
• An AI Mode tracker alongside the core engines

Cons

• Doesn’t publish standard pricing
• Fewer engines than the credit-based trackers above

For mid-size and enterprise brands

These are the best AI visibility tools for mid-size and enterprise brands: more engines, including AI Mode and AI Overviews, with the permissions and support a larger team needs.

Scrunch

Best for: mid-size and enterprise brands

Scrunch covers eight engines on a published price. Its pricing page lists Starter at $250 a month billed annually, with 350 custom prompts and three user licences, Growth at $417 a month, and Enterprise as custom.

The eight engines are ChatGPT, Claude, Gemini, Perplexity, Google AI Mode, Google AI Overviews, Meta AI and Copilot, with Grok listed as coming soon. That fits a brand that needs AI Mode and AI Overviews alongside the chat assistants.

Pros

• Eight engines including AI Mode, AI Overviews and Meta AI
• Published pricing with a clear prompt and seat allowance

Cons

• The entry price is high next to the focused trackers
• Grok isn’t available yet

AthenaHQ

Best for: teams that want many models early

AthenaHQ gets you a lot of models for nothing. Its plans page has a free tier with 300 credits and five models, then Starter at $295 a month with 3,600 credits and 11 or more models, adding AI Mode, Claude, Grok, DeepSeek, Meta AI and Mistral, with 17% off on annual billing.

One credit is one AI response. It’s for a team that wants to cover the long tail of models before committing.

Pros

• A real free plan with five models
• 11 or more models on Starter, more than most here

Cons

• Credit-based, so frequent tracking burns through the allowance
• Enterprise features need the custom plan

Goodie

Best for: teams that want an Answer Engine Optimization (AEO) strategist in the plan

Goodie bundles a human AEO strategist into the plan. Its pricing page lists Core at $399 a month with five models, 120 prompts and five seats plus the strategist, Pro at $999 a month with eight models, and Enterprise with up to 13 models.

It fits a team that wants someone to turn the measurement into page work, and a score alone isn’t that.

Pros

• An AEO strategist included with the plan
• Up to 13 models on Enterprise

Cons

• The most expensive entry on this list
• Strategist support is plan-gated, so Core gets less of it

Profound

Best for: enterprise brands already in procurement

Profound is built for enterprise procurement. Its pricing page offers a free 7-day trial with 50 prompts a day on ChatGPT, Gemini and AI Overviews, then Enterprise at a custom price, with up to nine answer engines on Enterprise.

It’s for a brand that needs a vendor in a formal procurement process and has the budget for a custom deal.

Pros

• A free trial to test the fit before a sales conversation
• Up to nine answer engines on Enterprise

Cons

• No published standard price
• The trial is engine-limited

If you already pay for an SEO suite

These are the best AI visibility tools inside an SEO suite you may already pay for.

Semrush AI Visibility Toolkit

Best for: teams already paying for the wider suite

The Semrush AI Visibility Toolkit is a standalone toolkit priced at $99 a month per domain, billed annually, on its own pricing tab. It tracks ChatGPT, Google AI, Gemini and Perplexity.

It’s for a team already inside Semrush that wants AI visibility without a second login.

Pros

• A standalone toolkit with its own price, not bundled into a bigger plan
• Four core engines tracked

Cons

• Per-domain pricing adds up fast for agencies with many clients
• Standalone is visibility-only, without Semrush’s other toolsets

Ahrefs Brand Radar

Best for: researching competitor visibility alongside your own

Ahrefs Brand Radar researches any brand across hundreds of millions of prompts, yours or a competitor’s. Its pricing page shows the main offering from $199 a month in USD, with Custom Prompt packages in USD too: Basic at $50, Growth at $100 and Scale at $250 a month.

It tracks AI Overviews, AI Mode, Perplexity, Copilot, Gemini, ChatGPT and Claude. It’s for a team already in Ahrefs that wants to research competitor AI visibility alongside its own.

Pros

• Research any brand across 476M+ prompts, yours or a competitor’s
• Custom Prompt packages in USD from $50 a month

Cons

• Claude checks consume 8 checks per update, so the allowance burns faster on Claude-heavy tracking
• Per-check overage on the custom-prompt tiers can add up

How to choose an AI visibility tool

The first question is which engines your buyers actually use. A B2B brand’s buyers may live in ChatGPT and Perplexity, so four assistants is enough. A consumer brand may need AI Overviews and AI Mode, which narrows the list to the tools that track them.

Then look at the sample. A rate is prompts times assistants times runs, and one probe is basically a coin flip. A tool that gives you a percentage with no confidence band is handing you a weak number, because the same prompt run twice can come back different.

Ask how many prompts you get for the price and whether the rate carries a confidence interval. Recommended versus only mentioned matters more than it sounds. A tool that counts mentions is doing something different from one that tells you whether you were put forward as a choice.

A mention is a name in passing. A recommendation is a buyer being sent your way. Most tools report a mention rate, and fewer separate the two.

What you see behind the answer is where the tools really split. Some hand you a score. Others show you the chain, the fanout queries the assistant ran and the sources it pulled back, including pages it read but never cited.

Those pages are the lever, because the model picks from what it retrieves. Our 10x refresh study points the same way: 98 posts refreshed with nothing published, citations up 10x in 91 days, and 41 cited pages had no Google impressions, so Google rank and AI citation barely line up.

The last question is who does the work after the measurement. A score on its own doesn’t tell you what to change, and some tools stop at the number.

Omnipresence hands the target and the method to your own agent over MCP, with a work log, so the fix ships. That’s the difference between a scoreboard and a plan.

FAQ

How do you track your brand in AI search?

You run a set of prompts against the assistants your buyers use, record whether each answer recommends you, and repeat on a schedule to get a rate. The prompt is the unit, not the keyword, because one buyer question can fire several searches before the model answers.

A tool that runs the prompts for you, stores the full answers, and reports the rate with a confidence band is doing the tracking. A tool that scrapes a single answer is a one-off check.

Are AI visibility tools and LLM visibility tools the same thing?

Yes, mostly. The two terms point at the same job: seeing whether a language model recommends you when a buyer asks. They swap because the assistants are all large language models (LLMs).

The one thing to check is which engines a tool actually covers, since some track only the chat assistants and some add AI Overviews and AI Mode.

What’s the best AI rank tracker?

It depends on which engines you need. For the chat assistants, a focused tracker like Otterly or Rankscale covers the core set. For AI Overviews and AI Mode, pick a tool that tracks those specifically.

AI Overviews, AI Mode and per-engine tracking are their own topic, because the engines retrieve and cite differently.

Can these tools check my visibility in AI search?

Yes, the visibility trackers here check how often AI search recommends you. That’s different from an AI content detector, which checks whether text was written by AI. If you want to know whether a model cites your page, you want a visibility tool, not a detector.

How accurate are AI visibility metrics?

Accuracy is a methodology question, not a brand. Three things decide it: the sample size, because one probe is basically a coin flip and a rate from a handful of prompts is noise; whether the rate carries a confidence band, so you know how tight the number is; and whether control prompts stay unworked, so a lift can be attributed to what you changed rather than to the model shifting on its own.