Cinchor: accountability layer for AI agents with bound-before and prove-after
Cinchor is a primitive that enforces policy on AI agents before they act and provides cryptographic proof of actions afterward. It allows teams to give agents real capabilities (e.g., moving money, shipping changes) while maintaining auditability and preventing out-of-policy actions. The system mints scoped capabilities (spend cap, allowlist, expiry) and checks every action against them, refusing violations before execution; actions are hashed, signed, and anchored append-only for later verification.
Related
Runeward: Sandbox AI agents with policy gates
Runeward is a sandboxing tool for AI agents that enforces policy gates to restrict agent actions. It uses LLMs to interpret and enforce user-defined policies, solving the problem of unsafe or unintended agent behavior for developers building autonomous AI systems.
Attestor: open-source zero-trust boundary for autonomous AI agents
Attestor is an open-source execution boundary that enforces zero-trust security for autonomous AI agents. It uses LLMs to define and enforce policies that restrict agent actions, preventing unauthorized access or data leaks. This solves the problem of safely deploying autonomous agents in production environments.
Ripple: open-source local-first authorization for AI coding agents
Ripple is an open-source, local-first authorization layer that restricts AI coding agents to only modify files they are explicitly permitted to change. It solves the problem of AI agents making unauthorized or unintended modifications across a codebase, giving developers control and trust in agentic coding workflows.
Human approval inbox for AI agents
Impri is a human-in-the-loop approval system for AI agents. It provides a shared inbox where agents submit drafts (emails, posts, replies) and a human must approve or reject before the action is taken. It solves the problem of developers repeatedly building the same approval UI and cron infrastructure for agentic workflows.
Agent action verification service comparing before/after states
Witnessed is a service that independently verifies whether an AI agent's actions actually took effect in the real world. It compares the state before and after an action to catch silent failures where the agent reports success but the intended change did not occur. This helps developers building production agents avoid incorrect assumptions and cascading errors.