Truth, engineered

AI models are good at reading and reasoning, and every one of them gets things wrong with confidence. Ask one model to fact-check a document and you inherit its blind spots, its training-data cutoff, and its particular way of hallucinating. Publishers, researchers, and teams that publish at volume need more than one model's opinion.

So we treat verification as an engineering problem. Several models check each claim independently. Disagreement stays on the record. Every verdict keeps an audit trail back to the votes and sources behind it. And the price is quoted up front, per claim, before any work runs.

A panel of models from different providers checks every claim in your document. Each model answers on its own, from its own knowledge or with live web research and citations. A separate AI judge then weighs their votes, reasoning, and evidence into one consensus verdict with a calibrated confidence score. Our methodology page documents the full pipeline, its known limitations, and how to read the scores.

Fact Engineering is built by Fact Engineering Inc. Questions, feedback, or press: reach us at support@fact.engineering or through the contact form.