“Was this action actually allowed to execute?”Today’s systems rely on trust, not verification. --- ## The gap - AI systems generate actions but cannot enforce authority - Workflow systems execute actions but do not verify authorization - Audit systems log actions but do not prevent invalid execution There is no pre-execution authority layer. --- ## The solution Parmana introduces a missing infrastructure layer: AI → Signals → Governance → Authorization Decision → Execution Runtime → Attestation It ensures: - AI generates signals, not execution - Governance determines authorization - Execution only happens if approved - Every decision is cryptographically verifiable --- ## What changes with Parmana ### Before AI → Execution (implicit trust) ### After AI → Signals → Governance → Authorization Decision → Execution Runtime → Attestation --- ## Core capabilities - Deterministic authorization before execution - Cryptographic proof of every decision - Independent verification without system access - Strict separation between AI and execution - Replay-safe execution enforcement --- ## Why it matters As AI systems become autonomous, execution risk increases. Parmana ensures: - AI cannot execute actions directly - every action is explicitly authorized - every decision is verifiable - every execution is traceable --- ## Who it is for Systems where AI triggers real-world actions: - fintech systems - enterprise automation - AI agent platforms - infrastructure systems - healthcare workflows --- ## Category Parmana defines a new infrastructure category:
Execution Authority Verification for AI systems--- ## Final statement AI generates actions. Humans define authority. Parmana enforces it.