AtlasProof by Proofence

AtlasProof by Proofence gives teams a place to check AI outputs before they ship. Instead of copying answers between tools and hoping they hold up, users submit content to the workspace and get back a structured verdict: a trust score, the evidence behind it, and a clear explanation of why the result reads as reliable or questionable. The workspace is built for everyday use, so verification becomes a habit rather than an afterthought.

Each review is organized around evidence. AtlasProof shows the sources that support or challenge a claim, highlights where a model may have overreached, and separates well-grounded statements from confident-sounding guesses. Reviewers can drill into any part of a result, leave notes, and resolve disagreements together, keeping the reasoning in one shared place rather than scattered across chats and documents.

When the engine flags a case as low-confidence or high-stakes, AtlasProof routes it into a human review queue with the context already assembled. Reviewers see what was checked, what the evidence said, and where uncertainty remains, so they can make a call quickly and consistently. Decisions and their rationale are retained, giving teams a reviewable trail of how questions were settled.

For developers, the same capabilities are available through an API, so verification can run inside existing products and pipelines. Teams can start in the workspace, then move proven checks into automated flows without changing how results are scored or explained. Throughout, AtlasProof relies on Proofence Engine, so what happens in the workspace matches what happens in code.