Airweave

About

Airweave serves as an open-source, shared context retrieval infrastructure that sits between your various data sources and AI systems. It seamlessly connects to over 50 applications, tools, and databases, continuously syncing their data. This aggregated information is then exposed through a unified, LLM-friendly search interface, allowing AI agents to query Airweave to retrieve relevant, grounded, and up-to-date context from multiple sources in a single request. By handling authentication, ingestion, syncing, indexing, and retrieval, Airweave eliminates the need to build fragile pipelines for every agent or integration.

Key Features

• 5,752 GitHub stars
• Supports both cloud-hosted and self-hosted deployment (Docker required)
• Unified context retrieval layer for AI agents and RAG systems
• Exposes data through an LLM-friendly search interface (SDKs, REST API, native integrations)
• Python and TypeScript SDKs available for integration
• Connects to 50+ apps, databases, and documents with continuous data syncing and indexing

Use Cases

• Establishing shared retrieval infrastructure for multiple AI applications to reduce integration overhead
• Empowering AI agents with up-to-date, grounded context from enterprise data sources
• Building robust Retrieval Augmented Generation (RAG) systems across diverse data environments