See exactly how ChatGPT, Perplexity, Gemini, Claude, and Google AI Mode answer when buyers search your brand, your category, or your competitors. ~60s scan. Free. No signup. Then act on a P0/P1/P2 fix script ranked by impact.
Four signals power one score, measured across 20 prompts × 5 engines (100 observation points), re-scored weekly.
We query 5 AI engines on category prompts in real time. Stream the transcript as it scans. Reveal 3 walled insights instantly. The full forensic report is in the $299 Audit Plus.
We audit the engines your buyers actually use, weighted by real buyer share, not hype. Grok joins as its crypto query volume grows.
Real category prompts, intercepted across engines. The brands AI names, and where you land.
It's the most common objection. We hear it every week. The answer is honest: yes, but you'll get a screenshot, not a strategy.
ChatGPT, Perplexity, Google AI Mode all return different results based on where you're searching from. Running the prompt yourself from your office shows you your office's answer, not what a buyer in Singapore sees.
What you need isn't "did I show up?", it's "across 20 buyer-style prompts spanning discovery, comparison, trust, implementation, due diligence, what's my appearance rate?" That's a measurement, not a screenshot.
Knowing you're at 12% citation rate doesn't fix anything. Knowing the 3 specific moves that lift you to 28% in 90 days does. That requires comparing your results against the dataset of 3,646 events we've collected.
Two sample brands. Both at low single-digit citation rates at start. After implementing the audit's P0/P1 moves over 4–6 weeks, both moved into the top 4 most-cited brands for their category.
Source #1 on that answer: an article we placed. Crawl markers verified in raw responses.Read the case →
The forensics that move your citation rate, measured continuously, not once.
We map how every engine positions you across category prompts, pinpoint the queries you're losing, and hand you the moves that flip them.
Every rival's citation share, side by side over time. See who's gaining, who's slipping, and which answers are up for grabs.
P0/P1/P2 moves ordered by effort vs. projected score lift, so your team always knows the single highest-leverage thing to ship next.
20 buyer-style prompts across the full journey × 5 engines. Real coverage of how buyers actually ask, every cited URL captured, every miss flagged.
Each engine scores 0–100 = Mention 60% + Citation 20% + Authority 20%, measured across 20 buyer-style prompts × 5 engines = 100 observation points per audit. Engine scores are combined weighted by real buyer share. Plus modifiers for trust + typosquat. Every weight published.
| Component | Weight | What it measures |
|---|---|---|
| Mention | 60% | The brand is named when AI answers category prompts. The dominant signal. |
| Citation | 20% | Your own domain is cited as a source URL, not just named. |
| Authority | 20% | A blend of source credibility (are you named alongside high-trust outlets — Wikipedia, CoinGecko, tier-1 crypto media, mainstream finance — vs SEO blogs), entity footprint (Reddit, YouTube, Wikipedia, CoinGecko, GitHub), domain authority (backlink strength / domain rating), and technical readiness (AI-crawlable, schema-marked, fast). |
| Engine | Share | How it's probed |
|---|---|---|
| ChatGPT | 27% | Category prompts via Responses API + web_search |
| Gemini | 22% | Grounded responses via gemini-2.5-flash + google_search tool |
| Google AI Mode | 22% | References inside the AI Overview panel via DataForSEO SERP |
| Perplexity | 16% | Citations via Sonar model with web search enabled |
| Claude | 13% | Grounded responses with web search enabled |
If AI engines can't crawl, parse, and trust your site, none of the citation work lands. So I check the foundation first, on every scan, before a single prompt runs.
One critical block is holding the whole score down. Clear it and the projected score jumps to 91.
Not who you think you compete with, who the engines name when buyers ask. Same category prompts, all 5 engines, apples-to-apples. Here's the leaderboard for centralized exchanges. For a full worked example, see our study of which crypto exchange AI engines recommend, 1,000 measured observations.
We don't ask who you compete with. We measure who AI is already recommending instead of you, by how much, on which prompts.
Every answer that names your brand is scored for sentiment and tagged to a narrative theme. You see exactly which storylines the engines are repeating, and which ones are quietly working against you.
Tap a theme to filter the answer excerpts →
We tell you the median citeOS score for your vertical, so you know whether your number is winning or losing. The same 54 is dominant in one category and middle-of-the-pack in another.
You’re 12 above the exchange median, but 30 behind the leader.
Translation: you’ve cleared the table-stakes bar for a crypto exchange, but the category leader is cited roughly twice as often. The gap is closeable, and the assistant ranks exactly which fixes close it fastest.
Some category prompts have no clear winner in AI answers. No brand is consistently cited, the sources are weak, the door is open. Those are the cheapest citations to take, so we rank them by upside and hand you the list.
The assistant knows your whole audit, every engine, every cited source, your sector benchmark, and answers in plain language. Why you’re losing a prompt, what to fix first, who’s beating you and exactly where.
On the prompt “best low-fee crypto exchange”, Perplexity pulled its answer from a comparison article that ranks Kraken #1 and never mentions you. You have no indexed page targeting that query.
Your fastest win is the iGaming gateway cluster, you’re mentioned in 7 of 9 runs but cited as a source in only 2. One placement on an AI-readable outlet closes most of that gap.
Concierge re-audits you every week and a human writes the memo: what moved, why, and the one thing to ship next. Between memos, alerts ping you the moment your citation rate or sentiment shifts.
Perplexity picked up your new fee-comparison page on two buyer prompts, that’s the SoV bump. Gemini dropped you on “best exchange for beginners” after re-ranking to a competitor’s guide.
citeOS pings you the moment a citation appears or drops, or sentiment turns, so you never wait a week to find out.
Free entry, paid forensics, monthly recurring for ongoing measurement. Same engine across all tiers, depth + execution scale with price.
Founders + ops leads who want the intel without an operator.
Founding-member rate ($999 list), locked for 12 months. Teams who want a strategist embedded, without giving up creative control.
Category leaders who want it run end-to-end. Done-for-you.
Run the scan. See exactly which queries you're losing, why, and what 90 days of citeOS execution would shift.
Get my free AI audit →