Jarvis – governed AI control plane with receipts, rollback, and agent guardrails (github.com)

Jarvis has been introduced as a governance layer designed to enhance control over AI-driven systems, ensuring that the speed of AI execution does not surpass human oversight. By instituting a structured framework that includes controlled execution, mandatory validation for changes, and comprehensive audit trails, Jarvis addresses the growing concerns around AI’s authority and the potential for unchecked decision-making. This governance approach treats AI as a tool rather than a decision-maker, emphasizing safety and accountability in its operations. Significantly, Jarvis employs features such as risk classification, snapshot rollback capabilities, and cryptographic approvals to minimize the risks associated with rapid AI changes. Each action within the system is rigorously documented and validated, which not only enhances traceability but also prevents potential errors from propagating unnoticed. With validated subsystems already in place, Jarvis establishes a robust foundation for AI governance, aiming to restore control, visibility, and accountability at the execution layer—ultimately safeguarding human authority in the age of rapidly evolving AI capabilities.