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.
Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI
Next-generation AI Agent Optimization Platform: Cozeloop addresses challenges in AI agent development by providing full-lifecycle management capabilities from development, debugging, and evaluation to monitoring.
ZenML 🙏: One AI Platform from Pipelines to Agents. https://zenml.io.
Evaluation and Tracking for LLM Experiments and AI Agents
AI agent to automatically check grammar and spelling on documentation files
oly turns long-running and interactive CLI workflows into persistent, supervised sessions for humans and AI agents. Close the terminal, keep the process alive, get notified when input is needed, and jump back in from anywhere.
Geniusrise: Framework for building geniuses
A radically simple, reliable, and high performance template to enable you to quickly get set up building multi-agent applications
Learn AI, ML, and NLP with interactive Jupyter Notebook tutorials.
The open-source AI agent control plane: MCP firewall, model gateway with budgets, human approvals, runtime observability, and audit trails
The open-source MultiAgentOps evaluation and verification harness for any industry business workflow.
🧱 CrewNews is an AI news generator that delivers an unbiased version of the news for a given topic, using Streamlit for the GUI, Llama 3.1 as the LLM (inferenced via the AIML API), CrewAI for building AI agents, AgentOps for testing AI agents, and Exa & Firecrawl as tools
Operational patterns for AI agents and infrastructure from solo to enterprise scale. Applies DevOps + SRE principles to the intersection: infrastructure FOR AI + AI FOR infrastructure. Alpha framework extracting meta-patterns from mission critical environments.
Observable diagnostics, failure attribution, metrics, and no-key replay for multi-agent runtimes.
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