"Where did this come from, and why should I believe it?"
Legal, regulatory, and audit work has a question generic AI cannot answer. Enkidu systems are built so that question always has a complete answer: every trust claim is an assurance case — claim, argument, evidence — bound to a policy with an explicit threshold; every evidence item carries a citation resolvable to a specific document; and every inference is recorded in a signed, hash-linked chain of custody that makes tampering visible and every result reproducible.
The central rule: determinism where it matters, reasoning where it helps. Scores, thresholds, and rubrics are code-enforced ground truth. The language model interprets, extracts, and drafts — it never assigns the verdict.
- Citation-enforced outputs — uncited claims are rejected
- Signed, tamper-evident chain of custody
- Replayable runs — any historical result reproducible
- On-premise, sealed from the internet — data sovereignty
- Human review before anything is released
Not a number someone typed.
A number a named, verifiable process produced.
The goal is not maximal trust but calibrated trust — reliance matched to demonstrated trustworthiness, because over-reliance and under-reliance are both failures. Every output is decision support: the final report is reviewed and released by an accountable human, and the question "who granted this agent the power it used?" is always answerable from the trace.
