Free AI Brand Audit
Free AI Brand Audit: See What ChatGPT, Claude & Gemini Say About Your Brand
Run the same audit methodology we've used on 5,829 brands. Enter your brand name and see how AI models actually describe you — for free.
What the Audit Checks
Your BAI score measures three dimensions — and each one tells you something different about how AI sees your brand.
Answer Presence
Does AI mention you at all? When someone asks ChatGPT "what are the best [your category] companies," do you show up? Our directory data shows that 7.5% of brands (439 out of 5,829) score 0-19 — functionally invisible to AI. They don't have a quality problem. They have an existence problem.
Message Pull-Through
Does AI describe you accurately? This is where it gets painful. Among brands that DO appear in AI responses, 60% are misrepresented — wrong category, outdated positioning, competitor confusion. AI might mention you, but if it calls your cybersecurity company an "IT staffing agency," that's arguably worse than not being mentioned at all.
Owned Citations
Does AI link back to your sources? When AI retrieves information about your brand, does it pull from your website, or from a three-year-old TechCrunch article that describes a product you've since pivoted away from? Owned citations matter because they create a feedback loop — the more AI models cite your authoritative sources, the more accurate their future responses become.
Where 5,829 brands fall on the BAI scale:
How to Interpret Your Results
Your audit result places you in one of four archetypes — a framework we developed after scoring 5,829 brands and identifying the distinct failure patterns.
AI knows who you are, describes you accurately, and recommends you in the right contexts. Your job: maintain it. AI brand perception isn't static — we track 8,008 score changes per week. Incumbents can become Misreads fast if they stop paying attention.
AI knows you exist and mostly gets the broad strokes right, but you're not the first recommendation. Your job: close the gap between how you describe yourself and how AI describes you. The fix is usually about source authority.
This is the scariest archetype because you don't know you have a problem. AI simply doesn't mention you. At all. Your job: get discovered. This usually means fixing technical discoverability — robots.txt, llms.txt, structured data.
AI mentions you, but gets it wrong. Wrong category, wrong product description, confused with a competitor. This is the highest-urgency archetype. Average remediation time: 3-6 weeks depending on the fix type.
What Each AI Model Gets Right and Wrong
Different AI models have different versions of your brand. ChatGPT might describe you correctly while Claude thinks you're in a completely different industry. We know this because we see the server-side data.
OpenAI
10,816 req/weekGPTBot (8,159 training), OAI-SearchBot (1,691 search), ChatGPT-User (515 live browsing). The largest consumer of brand data in our directory.
Anthropic (Claude)
4,669 req/weekClaudeBot handles the bulk (4,235), plus Claude-User traffic (335) — real people asking Claude about brands.
Amazon
4,366 req/weekAmzn-SearchBot and Amazonbot. Powers Alexa, Rufus, and Amazon's AI assistants for product recommendations.
Perplexity
1,699 req/weekEvery request is likely answering a real user query — Perplexity is a pure search-and-answer engine.
A brand might score well on ChatGPT (which retrieved your updated profile) but poorly on Claude (which is working from older parametric data). A complete audit tests across models because they each have different "versions" of your brand. See the full methodology →
Why Manual Auditing Misses Things
The most common advice is "go to ChatGPT and ask about your brand." That's step 1 of 10 — testing a single query on a single model gives you a misleading picture. Our audit methodology tests five distinct query categories:
Direct identity queries
"What is [brand]?"
Tests whether AI has basic parametric knowledge of you.
Category placement queries
"What are the best [category] companies?"
Tests whether AI includes you in the competitive set where buyers are looking.
Buyer intent queries
"I need a [solution] for [use case]."
Tests whether AI recommends you when a real purchase decision is happening.
Sentiment probes
"What are the strengths and weaknesses of [brand]?"
Tests what narrative AI has internalized about you.
Competitor displacement
"Is [brand] better than [competitor]?"
Tests whether AI positions you correctly relative to alternatives.
Testing one query on one model is like checking your credit score with one bureau. You need the full picture. See the full audit framework →
Real Results
Hal9, an AI app debugging platform, used Optimly to audit and fix their AI brand representation. The result: 16x increase in qualified traffic in 60 days. The fix wasn't magic — it was systematic. We identified that AI models were miscategorizing them, corrected the structured data, aligned their authoritative sources, and monitored the score recovery through delta tracking.
Read the full case study →9
Brands self-claimed profiles with zero outbound sales
40,981
Worker requests processed per week
8,008
BAI score changes tracked in real-time
Ready to see what AI actually says about your brand?
Want the full methodology? Read our guide: How to Check What AI Says About Your Brand →