A cloud native Identity Aware Proxy and Access Control Decision service

Python SDK for AI agent governance - audit trails, policy enforcement, quantum-safe signatures. Works with LangChain, CrewAI, MCP.

Data policy IN, dynamic view OUT: PACE is the Policy As Code Engine. It helps you to programatically create and apply a data policy to a processing platform like Databricks, Snowflake or BigQuery (or plain 'ol Postgres, even!) with definitions imported from Collibra, Datahub, ODD and the like.

Deterministic governance for AI coding agents. Cedar-based policy engine that intercepts every agent action and evaluates it against deterministic rules before execution.

VERITAS OS is an AI agent governance runtime for decision control, policy enforcement, approval workflows, audit trails, and replayable evidence before real-world actions.

Agent Identity Protocol - Zero-trust security layer for AI agents. Policy enforcement proxy for MCP with Human-in-the-Loop approval, DLP scanning, and audit logging.

Encrypted vault, ZK settlement archiving, x402 payment receipts, Agent Passport binding, and Solana anchoring for OpenClaw and agent runtimes. Drop-in stack — compression, privacy, payments, identity.

MIDAS is an open platform for governing execution authority at decision surfaces across agents, AI systems, and enterprise workflows.

Deterministic Linux runtime enforcement with eBPF LSM: block file/network operations before syscalls complete.

A CLI tool for managing GitHub Actions workflows

Deterministic execution authorization for AI agents

Headless, OpenAI-compatible AI gateway in Go. Multi-tenant auth, tracing, cost tracking, rate limits, and optional PII redaction. Single binary, self-hosted, audit-ready by design.

System-level security for LLM agents: fine-grained policy enforcement on tool calls to defend against indirect prompt injection

Stop Claude Code from doing irreversible damage. Policy-gated execution + receipts so you can ship agents without sweating production.

The open standard for runtime agent control — declarative hooks, policy enforcement, and observability across AI agent frameworks.

MoralStack is a governance and safety layer for LLM applications. It analyzes user requests before generation, evaluates risk and intent, and decides whether the AI should answer normally, answer safely, or refuse. The goal is to make AI systems more auditable, controllable, and reliable in sensitive or regulated contexts.

Core Rust library for Lens sandbox policy enforcement, networking, DNS, proxying, and boundary credential exchange.

governance architecture for trustless execution

Cordon provides the guardrails for corporate teams adopting code generation tools.

Ensuring data usage control on real-time analytics in the FIWARE context