Airweave
A context retrieval layer connecting AI systems to synced app and database data.
Linked from airweave.ai · checked 1 Nov
- Tool type
- AI context retrieval infrastructure
- Made for
- Developers and teams building AI agents, RAG systems, or AI applications
- Runs on
- Hosted cloud or self-hosted deployment
- Quickstart documents local deployment on macOS, Linux, or WSL; Python and Node.js SDKs are available.
What it does
Airweave is an AI retrieval infrastructure service for developers and teams building agents, retrieval-augmented generation (RAG) systems, and AI applications. Users create a searchable collection, connect apps or databases with credentials, and let Airweave sync their data. An agent or application then searches the collection in natural language through an SDK or API and receives relevant results from connected sources. The service offers semantic, keyword, hybrid, time-aware, and agentic search.
Airweave can be used through its hosted cloud platform or self-hosted; the documented local deployment targets macOS, Linux, or WSL. Python and Node.js SDKs are documented, with an API key needed for client access. Its published Developer plan is free and includes monthly query and synced-entity limits; paid plans add capacity and team members. Consider the plan’s connection, query, entity, and team limits, and that source connections require appropriate credentials. The site also describes on-prem deployment as an Enterprise option.
What it can do
- Create searchable collections of connected data sources
- Connect apps, documents, databases, and data warehouses through prebuilt connectors
- Sync connected-source data
- Search across sources using semantic, keyword, hybrid, time-aware, and agentic methods
- Return relevant search results through a unified interface
- Integrate with LangChain, Composio, Pipedream, or a custom agent stack
Works with
- LangChain
- Composio
- Pipedream
- Python
- Node.js
Before you choose
- Connected sources require authentication credentials; availability depends on the supported connectors.
- Published plans have limits on source connections, monthly queries, synced entities, and team members.
- Self-hosting requires deploying and operating the service; the quickstart documents local setup rather than all possible deployment environments.
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Get started
The site links to the hosted app sign-up; API use requires an API key.
- Choose the hosted cloud platform or deploy locally using the documented repository instructions.
- Install the Python or Node.js SDK and create an API key from the Airweave dashboard.
- Create a collection, add a source connection with its credentials, and search the collection.
Plans and prices
Developer includes ten connections, 50 queries/month and 50K synced entities/month. Pro has 50 connections, 500 queries, 100K entities and two members; Startup has 1,000 connections, 5K queries, 1M entities and ten members. Monthly prices are displayed as $20/$299, versus yearly monthly equivalents $16/$239. Enterprise is quoted; self-hosting carries operating costs.
- 10 source connections
- 50 queries per month
- 50K entities synced per month
- Community support
- 50 source connections
- 500 queries per month
- 100K entities synced per month
- 2 team members
- Email support
- 1,000 source connections
- 5K queries per month
- 1M entities synced per month
- 10 team members
- Dedicated Slack support
- Dedicated onboarding
- Custom usage limits
- On-prem deployment available as an add-on
- SSO/RBAC/SLA options
Source: airweave.ai, checked 1 Nov 2026. Prices can change; check before you buy.
Sources for this overview
Product pages, documentation, and pricing checked 1 Nov 2026. Each source supports part of the overview; availability and prices can change.
- Airweave | Context Retrieval Layer for AI ↗airweave.ai
- Quickstart | Airweave ↗docs.airweave.ai
- How we use Airweave to improve Airweave ↗airweave.ai
- Contact | Airweave ↗airweave.ai
- Airweave | Context Retrieval Layer for AI ↗airweave.ai
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Last checked 1 Nov 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.