Open-source context retrieval layer for AI agents and RAG systems.

Airweave.Demo.mp4

What is Airweave?

Airweave connects to your apps, tools, and databases, continuously syncs their data, and exposes it through a unified, LLM-friendly search interface. AI agents query Airweave to retrieve relevant, grounded, up-to-date context from multiple sources in a single request.

Where it fits

Airweave sits between your data sources and AI systems as shared retrieval infrastructure. It handles authentication, ingestion, syncing, indexing, and retrieval so you don't have to rebuild fragile pipelines for every agent or integration.

How it works

1. Connect your apps, databases, and documents (50+ integrations)
2. Airweave syncs, indexes, and exposes your data through a unified retrieval layer
3. Agents query Airweave via our SDKs, REST API, MCP, or native integrations with popular agent frameworks
4. Agents retrieve relevant, grounded context on demand

Quickstart

Cloud-hosted: app.airweave.ai

Self-hosted

git clone https://github.com/airweave-ai/airweave.git
cd airweave
./start.sh

→ http://localhost:8080

Requires Docker and docker-compose

Supported Integrations

SDKs

pip install airweave-sdk        # Python
npm install @airweave/sdk       # TypeScript

from airweave import AirweaveSDK

client = AirweaveSDK(api_key="YOUR_API_KEY")
results = client.collections.search(
    readable_id="my-collection",
    query="Find recent failed payments"
)

Tech Stack

• Frontend: React/TypeScript with ShadCN
• Backend: FastAPI (Python)
• Databases: PostgreSQL (metadata), Vespa (vectors)
• Workers: Temporal (orchestration), Redis (pub/sub)
• Deployment: Docker Compose (dev), Kubernetes (prod)

Contributing

We welcome contributions! See our Contributing Guide.

License

MIT License

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