AI Observability & Evaluation
Open-source observability for AI agents. Find where your agents fail, dispatch your coding agent to fix it, and verify the fix against real traces.
AI observability platform for production LLM and agent systems.
Evaluation and Tracking for LLM Experiments and AI Agents
Laminar - open-source observability platform purpose-built for AI agents. YC S24.
Open-source observability & evaluation platform for AI agents and coding agents. Trace LLMs, tools, prompts, costs & agent workflows with OpenTelemetry.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
企业级 AI 资源纳管平台，提供统一 AI网关、Token调度能力，纳管 OpenAI、Azure、Claude、DeepSeek 等主流模型，并支持 MCP 工具与 Skill 的集中注册分发。具备内外双轨定价、成本归因、统一身份认证、安全审计与效能报表，帮助企业精准控制成本、量化 ROI，高效治理 AI 资产。
TraceRoot - open-source observability and self-improving layer for AI agents. YC S25
Self-hosted AI Agents Platform supporting Claude Code, Codex, Gemini agents. Apache 2.0.
Safe local execution layer for AI agent tools. Build and test-run MCP tools (no pass, no run), serve them from a built-in MCP server, and use them in Agentic Chat with RAG, human-in-the-loop approval, and built-in observability. Cross-platform desktop app powered by Spring AI.
The Applied AI Field Guide: fieldwork, value, engineering, and operations for AI that works beyond the demo.
Real-time cost observability for Model Context Protocol (MCP) tool calls. Wraps any MCP server, attributes spend per tool/project/customer. Free tier 25K calls/mo. EU-hosted
Agent and LLM API performance monitoring via network packet probe. Measures performance of OpenClaw, Claude, Codex, DeepAgents and more — deployed on the provider side, no SDK changes required.
Small Language Model Inference, Fine-Tuning and Observability.
A comprehensive solution for monitoring your AI models in production
AxonFlow: Runtime control layer for production AI
AI runtime inventory: discover shadow AI, trace LLM calls
A Python client to interact with Arize API
Agent skills for Arize — datasets, experiments, and traces via the ax CLI
To associate your repository with the ai-observability topic, visit your repo's landing page and select "manage topics."