How do I check if AI represents my brand accurately?

Q: Why do AI engines get brand facts wrong?

They pull from public sources that can be outdated or thin, then fill any gaps with plausible-sounding guesses. That produces old pricing, dropped features, wrong founding years, and even mangled brand names when a company is small or unusually named.

Q: Which prompts should I run to audit my brand?

Run plain factual questions across all five engines: what does the brand do, how much does it cost, who founded it and when, what are its main features, and where is it based. Answers differ by engine, so test ChatGPT, Perplexity, Gemini, Claude, and DeepSeek separately.

Q: How do I fix wrong information AI shows about my brand?

You cannot edit the model, but you can correct the sources it reads: your own site, Wikipedia and Wikidata, and review profiles like G2, Capterra, and Trustpilot. Make the correct fact appear consistently across them, then re-run your prompts a few weeks later.

Question

How do I check if AI represents my brand accurately?

Maciej Grabek · Accepted Answer

Ask each AI engine factual questions about your brand - what you do, what you cost, who founded you - then compare the answers to the truth. ChatGPT, Perplexity, Gemini, Claude, and DeepSeek all pull from public sources, so an outdated price or a wrong founding year on those sources shows up in their answers. Fix the sources and the answers follow. Why wrong facts are worse than no mention An engine that has never heard of you costs you a chance. An engine that states the wrong thing costs you a sale. Buyers act on the answer they get, and they anchor on it before they ever reach your site. If ChatGPT tells a prospect your plan starts at $49 when you moved to $99 last year, they arrive expecting a price you do not offer. If Gemini lists a feature you dropped, support fields the complaint. Wrong facts travel further than blank ones because the engine delivers them with the same confidence as the correct ones. Common failure modes: outdated pricing, features you no longer ship, the wrong founding year, the wrong headquarters, and positioning that puts you in the wrong category entirely. Run the factual prompts yourself You do not need a tool to start. Open each of the five engines and ask the same plain factual questions, one at a time: "What does [brand] do?" "How much does [brand] cost?" "Who founded [brand] and when?" "What are [brand]'s main features?" "Where is [brand] based?" Run every prompt across ChatGPT, Perplexity, Gemini, Claude, and DeepSeek. Answers vary by engine because they read different sources, so a fact that is right in one can be wrong in another. We run this on ourselves. Ask an engine "What is avisibli?" and you occasionally get the name back as "Visiblie" or "a visible AI," sometimes paired with a founding detail we never claimed. The brand is small and its name is unusual, so the engines fill the gaps with plausible-sounding guesses. That is exactly the failure mode you are auditing for. Compare the answers to the truth and log the gaps Write down what is actually true first, then read each answer against it. A small table keeps you honest: one row per claim, one column per engine, mark each cell right or wrong. Sort the wrong ones into four buckets, because each has a different fix: Outdated - old pricing, a former CEO, a stale plan name. The truth used to be on the web and the engine cached the old version. Dropped - a feature or product you retired that still shows up. Fabricated - a founding year, funding figure, or name spelling the engine invented to fill a gap. Positioning - it describes you as the wrong kind of company, or lumps you with the wrong competitors. Fix the sources, not the model You cannot edit ChatGPT's or Gemini's weights. You can edit what they read. The engines pull from your own site, from Wikipedia and Wikidata, and from review profiles like G2, Capterra, and Trustpilot, plus third-party listicles that rank for your category. Make the correct fact appear plainly and consistently across those sources. Put current pricing in crawlable text on your pricing page, not locked inside an image or a script. State your founding year and location in your About page and your Wikidata entry. Update stale review-site listings. When the same fact shows up the same way in several trusted places, the engines stop guessing. Re-run your prompts a few weeks after the changes are live, since engines refresh on their own schedule, not yours. Running these prompts by hand across five engines every few weeks gets tedious. avisibli automates the re-runs and flags when an engine's answer drifts from the facts you set, so you catch a wrong price or a mangled name without checking manually. avisibli is the GEO platform that publishes this answer library. Self-references are limited to topics where a tool-based answer is genuinely useful to readers.