Proof-of-behavior enforcement for AI agents. Declare behavioral constraints, enforce at runtime, produce SHA-256 hash-chained audit trails. Supports covenants (permit/forbid/require), real-time verification, and cross-agent trust handshakes.
Deterministic policy enforcement for AI agent tool calls. It evaluates every tool call against user-defined rules before execution, with no LLM in the authorization path.
A runtime gate for coding agents. Blocks the tool calls that wreck a repo (force-push main, rm -rf, secret exfiltration, CI wipe) and lets normal build and commit work through. Machine-checked git-branch core (z3); the rest is high-precision heuristics. Tested on 3,790 real CI commands, 0 false blocks.
Enables formal verification of LLM outputs against compliance ontologies using Z3 SMT solver. Validates that AI-generated content adheres to regulatory requirements like HIPAA or mortgage compliance rules.
Enables deterministic verification for AI assistants by executing Python code that uses symbolic engines like SymPy and Z3 for math, logic, and code analysis.
Runtime policy enforcement for AI agents. Evaluate every agent action against your organization's policies before execution, with observe and enforce modes.
