The tools inside Fractl Agents are built on measurements, not vibes — and we publish the measurements. Every piece here ships with its data files, its pre-registrations, and its full corrections log, because we'd rather you checked us than believed us.
We measured every brand and every source in 11,573 AI answers across 15 industries, then joined it to what's inside the models' training data. Which sites AI trusts, why 73% of what it cites doesn't rank on Google's page one, how new brands win on live visibility instead of fame, and why getting featured on the sites AI cites — earned media — just became how you win an AI recommendation.
We built the detector ourselves, ran a census of 326 models, and trained our own rewriters on rented GPUs. Detecting AI writing is basically solved and the "sound more human" checklists are a myth — but the one-click "humanizer" promise runs into a real wall: you can evade detection, or keep the facts, not both. A field report on what's solved, what's snake oil, and why.
We read a real AI model's actual training data — the only model on earth where that's possible — and ran 6,000+ controlled retrieval experiments across nine models, including a company we invented. What memory buys, what a retrieved page buys, why mention-count "AI visibility" scores measure the English language, and why the newest models are becoming auditors that discount promotional content.