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Public engineering proof / Applied AI · OpenAI optional

Controlled AI Decision Pipeline

Combines evidence-grounded model recommendations with deterministic authority rules and human approval.

Problem

Model output can be uncertain, malformed, or weakly supported. A product needs clear limits on what a model can recommend and what requires human review.

System

Typed evidence snapshots and schema-constrained output feed deterministic policy. Evidence quality and confidence are modeled separately; the system records provenance, applies safe-action allowlists, and gates consequential actions on approval.

Architecture

  1. Canonical evidence
  2. Constrained model output
  3. Evidence and confidence checks
  4. Deterministic policy
  5. Approval gate
  6. Auditable outcome

Demonstrated capabilities

  • • Schema-constrained and evidence-grounded outputs
  • • Evidence quality, confidence, and provenance modeling
  • • Deterministic authority policy and safe-action allowlists
  • • Human approval and explicit non-actionable failure states

Commercial applications

  • • AI-assisted product features
  • • Operator copilots
  • • Decision support
  • • Human-in-the-loop review workflows

Related VantaBlade Product Systems

Where this pattern appears in integrated product evidence.

These relationships indicate a shared engineering pattern. This repository does not reproduce the complete product or imply code identity.