Airweave
Open-source context retrieval layer for AI agents
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What is Airweave?
Airweave is an open-source context retrieval layer that gives AI agents unified search across all your apps, databases, and documents. Instead of wiring each data source separately, Airweave connects directly to all existing tools and exposes their data through a single search interface. It continuously syncs information from connected sources and makes it available as a unified, searchable retrieval layer, allowing AI agents to retrieve current, source-grounded context at query time rather than relying on static embeddings or custom data pipelines that quickly fall out of date.
The platform offers powerful search capabilities including semantic, keyword, hybrid, time-aware, and agentic search with intent understanding and awareness of complex relationships. It features real-time data sync so agents always see current information with no stale snapshots, and comes with over 50 prebuilt connectors for apps, productivity tools, databases, and document stores. Airweave is framework-friendly and works with LangChain, Composio, Pipedream, or custom agent stacks, getting users from install to first answer in five minutes.
Airweave is designed for developers and teams building AI agents, RAG systems, or other AI-powered applications that need reliable access to information across multiple tools and data sources. Common use cases include internal knowledge assistants that pull information from Notion, Google Drive, and Slack; customer support agents accessing context from tickets, docs, and CRM systems; and multi-source context retrieval combining relevant context from structured and unstructured sources at query time.
The tool is open source under the MIT license and can be self-hosted locally on macOS, Linux, or WSL, or used via the hosted cloud platform. It provides Python and Node.js SDKs, a dashboard UI at localhost:8080 for local deployments, and REST API or MCP interface for agent integration. Airweave also publishes official agent skills for Cursor, Claude Code, Gemini CLI, and other environments.
Airweave pricing
Pricing model: Freemium
Developer Free: Perfect for personal agents and side projects, no credit card required. Includes 10 source connections, 50 queries/mo, 50K entities synced/mo, community support. Pro: $16/mo (monthly) or save 20% yearly. Includes 50 source connections, 500 queries/mo, 100K entities synced/mo, 2 team members, email support. Startup: $239/mo (monthly) or save 20% yearly. For fast-moving teams needing scale. Includes 1000 source connections, 5K queries/mo, 1M entities synced/mo, 10 team members, dedicated Slack support, dedicated onboarding. Enterprise: Custom pricing for organization custom needs. Includes unlimited source connections, custom usage limits, tailored onboarding, dedicated priority support. Optional add-ons: custom integrations, on-prem deployment, SSO, RBAC, SLAs.
Airweave pros
- Open source with MIT license for full transparency and control
- Over 50 prebuilt connectors for apps, databases, and document stores
- Real-time data sync with no stale snapshots or manual refreshing
- Unified search interface across all data sources in one query
- Multiple search strategies: semantic, keyword, hybrid, time-aware, agentic
- Framework friendly with LangChain, Composio, Pipedream integration
- Five minutes from install to first answer
- Python and Node.js SDKs available
- REST API and MCP server interface for agent integration
- Self-hosted or cloud deployment options
- Agent Skills for Cursor, Claude Code, Gemini CLI environments
- Collects data into searchable collections with single endpoint
- Handles authentication and automatic sync automatically
- Dashboard UI for connecting sources and configuring syncs
- Active community with Discord support and GitHub repository
Airweave cons
- Free tier limited to 50 queries per month
- Free tier only allows 10 source connections
- Pro plan at $16/mo may be expensive for individual developers
- Startup plan at $239/mo is pricey for small teams
- Self-hosting requires local macOS, Linux, or WSL environment
- Limited to 50K entities synced per month on free tier
- Only 2 team members included in Pro plan
- Enterprise features like SSO and RBAC require custom pricing
- Full list of supported sources only available in documentation
- No Windows native support mentioned for local deployment
- Email support only on Pro plan, no chat
- Custom integrations only available as paid add-on for Enterprise
- On-prem deployment only available as Enterprise add-on
- 500 queries per month may be insufficient for production agents
- Requires API key creation and dashboard setup before use
Frequently asked questions about Airweave
What is Airweave?
Airweave is a context retrieval layer that lets AI systems retrieve relevant context from apps and databases. It connects to data sources, syncs information, and exposes it through a unified search interface so AI systems can retrieve up-to-date, source-grounded context when needed.
Where does Airweave sit in the AI stack?
Airweave sits between AI systems and data sources. It acts as shared context retrieval infrastructure that AI agents and RAG pipelines can query to access information across multiple apps and databases.
How is Airweave different from traditional RAG setups?
Traditional RAG pipelines are often built per application and rely on static embeddings. Airweave provides a shared context retrieval layer that continuously syncs data from source systems and can be reused across multiple AI agents and applications.
Why use a unified context retrieval layer instead of connecting data sources individually?
Connecting data sources individually often leads to custom, brittle integrations that are hard to maintain. Airweave connects to apps and databases once and exposes them through a unified search interface that AI systems can reuse across agents and applications.
How does Airweave keep context up to date?
Airweave continuously syncs data from connected apps and databases and makes it available at query time. This allows AI systems to retrieve current, source-grounded context instead of relying on static embeddings that quickly fall out of date.
What applications and data sources can Airweave connect to?
Airweave connects to common enterprise apps, databases, and document stores, including CRMs, cloud drives, knowledge bases, and data warehouses. The full list of supported sources is available in the documentation.
Who is Airweave for?
Airweave is for developers and teams building AI agents, RAG systems, or other AI-powered applications that need reliable access to information across multiple tools and data sources. It is especially useful for those working on long-running AI agents, retrieval-augmented generation, or any context-heavy LLM application.
Is Airweave open source?
Yes. Airweave is open source and can be self-hosted or used via the hosted platform. This gives users full control over how data is synced, accessed, and used by AI systems. It is released under the MIT license and built in the open with community improvements.
How do I get started with Airweave?
The simplest way is through the hosted cloud platform at app.airweave.ai. You can also deploy locally on macOS, Linux, or WSL by cloning the repository and running ./start.sh. After setup, create a collection, add source connections for your apps/databases, and search your collection using the SDK or API.
What search strategies does Airweave support?
Airweave supports semantic search, keyword search, hybrid search, time-aware search, and agentic search with intent, context, and understanding of complex relationships and interdependencies. This allows agents to find the right answers across apps and formats.