AI for claims processing. Deployed in 48 hours.

AI is used in claims management for document extraction, policy validation, fraud and risk scoring, adjuster routing, adjudication support, and audit-trail logging. The model reads the claim file, cross-checks coverage against the policy, flags pattern and timing anomalies for SIU, routes by severity, cites the policy clause behind every reserve, and timestamps each decision step. The result is faster cycle time, fewer denials in dispute, and an audit trail the examiner can replay.

Hallucinations get prevented by retrieving before generating. The model pulls the actual policy clause, endorsement, or claim file passage and grounds its output in that source. Every AI decision cites the page region it came from, so a reviewer can verify the citation in one click. If the model can't find a grounded source, the claim routes to a human instead of guessing. Validation runs at the source, so policy-language mismatches surface before adjudication.

The audit trail is replayable in real time. Every input, model version, prompt, retrieved source, and decision step is timestamped and source-tagged as the claim moves. When a regulator or examiner asks why, the operator opens the claim's audit view, sees the policy clauses cited, the AI decision rationale, and the human reviewers who signed off. NAIC Model Bulletin disclosure requirements are met by the architecture, not by a binder.

Adjusters keep authority and gain capacity. AI handles the document reading, policy lookup, and rule checks, then surfaces the inputs and citations the adjuster needs to make the call. Industry research from Wisedocs found only 16% of adjusters trust AI without seeing the source. Truzer is built so they see every source. Capacity goes up because the rote work is gone, and authority stays with the adjuster who signs the decision.