“Is this action actually allowed to execute?”Current systems rely on trust, not verification. --- ## Slide 4: 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. --- ## Slide 5: The Core Failure Today’s assumption:
If a system says an action is valid, it is executed.This is: - not deterministic - not verifiable - not safe for autonomous systems --- ## Slide 6: 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 --- ## Slide 7: What Parmana Does - Deterministic authorization before execution - Cryptographic attestation of every decision - Independent verification without system access - Strict separation of AI and execution - Replay-safe enforcement --- ## Slide 8: Why Now AI systems are moving from intelligence → execution. But governance has not evolved. This creates a critical infrastructure gap. --- ## Slide 9: Market Every system where AI triggers real-world actions: - fintech - enterprise automation - healthcare systems - AI agent platforms - infrastructure automation --- ## Slide 10: Category Parmana defines a new category:
Execution Authority Verification Infrastructure for AI systems--- ## Slide 11: Before / After Before: AI → Execution (implicit trust) After: AI → Signals → Governance → Authorization Decision → Execution Runtime → Attestation --- ## Slide 12: Closing AI has intelligence. Humans define authority. Parmana enforces it.