Your AEO Lab
See how ChatGPT, Claude, and Perplexity fetch, read, and cite your site. Then fix it at the engineering layer.
Rendered


AI search cannot fetch this page.
So it cannot recommend you as the answer.
# 9 words parsed. No product, price or claim text reached the model.
This diff is not a one-time read. Crawlers change, your site changes — we re-fetch and track it continuously.
Bull AI Labs rebuilt how every AI engine sees Freeletics. Within a quarter we went from being absent in answer surfaces to being the cited choice for our category.

Don't be bullish. Open your LLM lab.
An agency audit lands in your inbox. The recommendations sit in an engineering backlog for months. Your visibility depends on renting mentions - Reddit threads, listicles, other people's pages.
Your first verified fix ships within 24 hours of the audit. We re-probe it on the next live fetch. Your own pages become the source AI engines read - you stop renting visibility and start owning it.
Own the source. Don't rent it.
Answer share moved from 15% to 68% on tracked high-intent queries during the engagement.
Every cell is a real prompt on a real engine.
Googlebot renders your JavaScript. AI crawlers don't. Run any URL through the two-fetch diff and see exactly what ChatGPT, Claude, and Perplexity can - and can't - read on your site.






Six product surfaces, one operating picture. Diagnose the crawl gap, score every engine, ship the fixes, measure the lift.
Two-fetch diff
Catch invisible content before it costs you citations.
Engine × Signal Matrix
Every cell is a citation opportunity, scored continuously.
Sprint board
Bi-weekly cadence, scoped to revenue impact, reviewable as pull requests.
Citation map
ChatGPT, Claude, Perplexity, Gemini, AI Overviews, Copilot. Per-prompt, per-engine, weekly.
ChatGPT
Perplexity
GeminiFrontier signals
MCP-readiness, agentic commerce surface, .well-known endpoints. Tracked before competitors know they exist.
The platform
Bull AI Labs holds a point of view on every protocol surface that will determine AI citation — from chunk architecture to the MCP layer where agents will invoke instead of browse. 51 signals graded across the surfaces we measure today; MCP coverage is POV, not shipped probing.
Across every surface above — rendering, entity, edge, community, reviews, agents.
Shipped as code, not slide decks. Two-week cycles, measured outcomes.
Citation share tracked weekly across every major AI surface in the market.



Your brand becomes the cited choice across every major engine - measured, not assumed.
Explore Your AEO LabFree - domain only - no signup. First read in about two minutes.
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