We build and promote open-source tools for model training, tuning, and inference. We are also collaborating to simplify, automate, and optimize the deployment and execution of large-scale AI workloads on Kubernetes.
We are currently driving advancements and learning examples for MCP (Model Context Protocol), agents, Llama Stack, and domain-specific example applications.
Trust & Safety
The Open Agent Lab is a collaborative community of open source AI projects and domain-specific work groups that seek to make AI Agents successful in the real world through fast experimentation and distillation of learning into usable reference architectures and implementations, and build out of new tools to enable development and deployment.
Applications and Tools
A "living guide" for building AI-enabled applications, this guide provides an introduction to several established design patterns for building AI systems and products, with contributions from different experts in the AI Alliance. Several common patterns, like RAG (retrieval-augmented generation), are explored from different angles, and emerging patterns, like GraphRAG (using a graph network as a source of RAG content) and agents.
The AI Alliance application and tools working group has conducted a comprehensive study on best practices for advancing domain-specific Q&A using retrieval-augmented generation (RAG) techniques. The findings of this research, provide insights and recommendations for maximizing the capabilities of Q&A AI in specialized domains.