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Prove Before Act

Make AI agents prove before they act

Prove Before Act introduces a critical accountability framework for autonomous agents. Key features include: • Pre-execution commitment of agent's rationale • Cryptographic proof anchoring the declared 'WHY' • Linking recorded 'WHAT' after execution • Independent, verifiable sequence of actions • Secure, private data handling This system addresses the challenge of verifying agent actions by requiring a declared decision basis ('WHY') to be committed and cryptographically proven before an action is taken. After execution, the actual outcome ('WHAT') is linked to this proof. This creates an independently verifiable chain of events, ensuring transparency and accountability without exposing sensitive private data. The process focuses on verifying the sequence of commitment and outcome, rather than judging the correctness of the action itself, giving operators control over enforcement. The framework is an open standard with SDKs available for MCP, REST, Python, and JavaScript, making integration straightforward for developers. The reference implementation, xProof, offers a practical way to integrate this pattern into existing agent systems. It is ideal for scenarios involving financial transactions, infrastructure deployments, legal commitments, and agent delegations, where verifiable evidence of an agent's decision-making process is paramount. Designed for developers and organizations deploying autonomous agents who need to establish trust and auditability in their agent's operations. It provides a robust mechanism to understand and trace agent behavior, enhancing operational security and compliance.
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