New Whitepaper: The Decision Evidence Layer

We published a new whitepaper: The Decision Evidence Layer: Privacy-Safe, Verifiable Signals That Gate AI Agent Actions.

What It Covers

1. The failure mode. Agents do not fail quietly; they fail with confidence. Three real shapes (marketing, customer success, product) of agents acting on weak inputs.
2. Enterprise constraints. Why privacy, procurement, and auditability requirements break traditional analytics and voice tools, and what defensible artifacts security teams actually need.
3. The five principles. Minimize, Prove, Scope, Gate, Trace: the discipline that keeps the layer defensible end-to-end.
4. Architecture. Five stages from Capture (transient only) through Audit (end-to-end traceability), with the evidence schema (Quote, Emotion Tag, Theme, Confidence, Provenance).
5. Privacy by design and security posture. Data minimization, purpose limitation, retention controls, consent traceability, encryption, RBAC, key management, tamper-evident logs.
6. The Evidence Pack. A procurement-ready artifact bundle every deployment ships by default: sample bundle in JSON, policy scope, retention configuration, model manifest, and an example audit trace.
7. Business outcomes and KPIs. What changes in 30 days, plus four KPIs to publish on day one (time to insight, percent gated, audit pass rate, lift vs. baseline).
8. A 12-point DEL adoption checklist to run before authorizing an agent to act on customer signal.

Why It Matters

AI agents will not fail because they lack intelligence. They will fail because they lack evidence at the moment of action. The DEL introduces a new operating standard: no decisions without proof, no automation without traceability, no insights without provenance. Companion blog post: Agents Don't Fail Quietly. They Fail Confidently.

Download

Download the PDF on the Whitepapers page. No form required.