ActivePolicy sits between your AI systems and the real world, evaluating every action against policy before it executes.
ActivePolicy acts as a deterministic membrane between AI systems and execution. Every proposed action passes through policy evaluation before it can proceed.
This happens at runtime, not during training. The policy layer doesn't change your models—it governs what they're allowed to do.
Every action evaluation produces exactly one of four outcomes. No ambiguity. No drift. No surprises.
Action is within policy bounds. Proceeds immediately with full audit trail.
Action requires human confirmation. System waits for explicit approval.
Action routed to appropriate authority. Handled outside normal flow.
Action violates policy. Blocked with clear reason and authority citation.
Same action, same policy, same outcome. Every single time. No model drift affects policy decisions.
Every decision creates a cryptographically signed receipt. Full replay capability for compliance audits.
Policy evaluation happens before execution, not after. Prevention, not detection.
Works with any LLM, any framework, any infrastructure. No vendor lock-in.
CONDITIONAL outcomes require explicit human confirmation. No silent automation of critical decisions.
Every decision cites the policy authority. Clear accountability and governance.
Experience ActivePolicy's deterministic policy evaluation in our live demo.