Zero blind trust. One hundred percent auditability.
Hallucinations are the most expensive problem of enterprise AI. An isolated model may deliver claims that look correct and are not. In critical contexts —legal, financial, industrial, medical— that is unacceptable.
IRIS does not solve this with a bigger model. It solves it with architecture: every conclusion passes through three internal review layers before reaching the user.
The three layers
Factual verification
Each factual claim is checked against primary sources and against the structured knowledge base of IRIS. If a claim cannot be checked, it is marked unverified. Verification does not rewrite the answer; it annotates it.
Adversarial challenge
An independent adversarial process searches for logical flaws, internal inconsistencies and contradictions with previous context. While verification checks against the external world, this layer checks internal coherence. A response can be factually correct yet logically inconsistent with earlier decisions. That is the failure this layer detects.
Direction and consolidation
The final layer decides whether the answer ships. It receives the analysis of the two previous layers and decides: approve, reject or deliberate again. Output always arrives with explicit confidence.