Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.
The open-source app everyone uses to manage agents at work
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
Graph-Native Infrastructure for Context and Accountable AI Systems
Open-source, high-performance AI gateway that works as your LLM gateway, MCP gateway and agent gateway. One OpenAI-compatible API for 10,000+ models, with failover, load balancing, semantic caching, virtual keys, budgets and MCP Code Mode. Works with any SDK or agent and adds under 200µs of overhead at 5k RPS.
Self-hosted TypeScript agent runtime with durable approvals and verifiable run records. Own it, approve it, audit it.
Self-hosted, open-source agent skill registry for enterprises. Publish & version skill packages, govern with RBAC and audit logs, deploy on-premise with Docker or Kubernetes.
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
LeanCTX is the Context Gateway for AI Systems. Select task-relevant context, apply supported controls, connect local knowledge and inspect recorded evidence. Open-source Engine: CLI, MCP, hooks and supported proxy paths.
The Enterprise Architecture Governance Harness — strategy, architecture, delivery, and assurance using AI coding assistants
The open-source governance layer for AI agents: write the rules declaratively, Bernstein enforces them and produces the verifiable, replayable record. Free, Apache-2.0. https://bernstein.run
Self-hosted AI API and MCP gateway for organizations: SSO and RBAC, per-user identity for MCP tool calls, PII redaction and tool-call guards, rate limits, budgets, cost accounting and audit logs.
不是问答机器人,而是能真正干活的数字分身。共享智能体,共享项目上下文,让项目所有成员一起协同工作。同时智能体会像人一样通过资料或者工作抽象和总结经验到项目上下文中
An execution-authority gateway for AI agents and APIs. It intercepts consequential HTTP actions, asks Decionis whether they are authorized, and forwards exactly the authorized request once on a single-use grant, holds it for a person, or refuses it, leaving chained evidence of each. Installs by Homebrew, Linux package, Docker or Helm.
Self-hosted AI Agents Platform for AI Native companies. Claude Code, Codex, Gemini, OpenCode agents. Apache 2.0.
A source-grounded course and architectural reference for engineers designing systems that must survive real traffic, partial failure, security review, and changing requirements, spanning enterprise system design, distributed systems, AI systems, cybersecurity, reliability, cloud, HPC, edge, and mission-critical infrastructure.
Agentic SDLC infrastructure. Define guardrails. Collect signals. Enforce continuously. Signed records of what your AI coding agents and CI/CD pipelines did, checked against policies as code, with the loop closed in CI/CD. AI sessions, SBOMs, VEX, SARIF and SLSA provenance, built on Sigstore and in-toto. Apache 2.0.
Python and TypeScript SDKs for verifiable evidence of AI agent actions. Signed receipts, policy enforcement, audit trails. Works with LangChain, CrewAI, MCP.
103 paste-ready declarative agents for Microsoft 365 Copilot. No coding. No Azure. Deploy in minutes.
The action firewall for AI agents. Enforce policy and human approval before risky tool calls, shell commands, workflows, and production changes, with auditable evidence.
Autonomous development for real products. Governed agents build from specs you approve, follow the rules you set, and nothing merges until another agent proves it. Your decisions, judgement and taste are the bar that work must clear. Declare your vision and let agents build it.
KSoR (Knowledge System of Record) is an open-source SDK for building governed, authoritative knowledge systems for humans and AI agents. It is a foundation of an AI-native knowledge platform.
开源劳动者AI研究与评测项目:建设劳动知识、公开评测基准与共同治理机制|Open worker-centered AI research and evaluation project.
AI Agent Identity and Access Management and Inference Firewall
A Geiger counter for AI agents — one read-only command that inventories every agent, MCP server, plugin, and AI extension on a machine
Govern consequential AI agent actions in Docker with deterministic policy, human approval, and signed Decision Dossiers.
This is the corresponding code for the O'Reilly book: Harness Engineering
OpenFlow — a visual builder for multi-agent AI workflows, built on the opencode engine
Open-source AI teammates for your company. The self-hosted agent layer: build, run and govern AI agents on your own servers, models and rules. RAG, skills, a real browser, 4,700+ MCP servers and an API, with budgets, approvals and an audit trail. Apache-2.0, built on Pydantic AI.
Universal AI Charter: plain-language governance principles and a public certification registry for AI models, built on disclosure instead of a development slowdown.
Agents can work. They cannot declare success. A governed coordination protocol for multi-agent AI work: eight contracts (task, resource, ownership, handoff, verification, evidence, approval, recovery) enforced in code, plus a reproducible conformance benchmark. Apache-2.0 code, CC BY 4.0 specification, zero dependencies, Node 18+.
make your ai track the progress of your project without drifting off
An open source, self-hosted, safety-focused AI workbench
AI 执行与监察体系(Agent Oversight Framework):分层治理规范 + L2 运行时监察参照实现——证据分级、自校正、边界诚实。A layered governance spec for AI agents, plus a runnable reference implementation of the L2 runtime-oversight layer. Docs CC BY-SA 4.0 / code Apache-2.0.
Este es mi acordeón para ayudarte a pasar la certificación AB-730 de Microsoft, Profesional en Negocios de IA. A pesar de que este acordeón te pueda ayudar te recomiendo que tu principal fuente sea Microsoft Learn.
A custom coding harness for TypeSafe AI's Jev: an LLM proposes, Jev answers narrow questions, code decides, every step leaves a receipt.
Structure-first operating process for AI coding agents: Blast / Mid / Inner build altitudes with clear ownership, then T1 structural, T2 bug/ops, T3 adversarial quality gates.