Make AI Reliable Enough for Business-Critical Decisions
Executive teams wanting AI in high-stakes workflows — lending, HR, financial approvals — without increasing compliance or operational risk.
El problema
AI reliability for business-critical decisions requires three properties that probabilistic AI lacks on its own: determinism (same policy, same result), accountability (every decision attributed to an auditable actor), and reversibility (decisions can be replayed, contested, and corrected). Corules provides all three as infrastructure. The AI model provides reasoning capability. Corules provides enforcement integrity. Together, the system is reliable enough for consequential decisions.
Cómo lo resuelve Corules
Corules's policy runtime evaluates structured context against compiled CEL expressions — returning ALLOW, BLOCK, or ESCALATE with a reason and audit ID.
Ejemplo de política
// The three reliability properties in practice:
// 1. Determinism: same input + same policy → same outcome
// 2. Accountability: every decision has actor_id from signed claims
// 3. Reversibility: replay API returns identical result for any past decision
// No probabilistic component in the enforcement path.Frequently Asked Questions
What is the failure mode if Corules is unavailable?
Safe defaults: on any infrastructure failure, the response is ESCALATE (not ALLOW). The calling workflow routes to manual review. AI-assisted decisions never silently auto-approve on system failure.
How do I build confidence in a new policy before going live?
Run the policy against historical audit data in simulation mode. Compare outcomes against human decisions made during the same period. Build confidence before production deployment.