Airweave is an open-source context retrieval layer that lets AI systems query, unify, and retrieve relevant information from multiple apps, databases, and other data sources.
Airweave is an open-source context retrieval layer designed to connect AI systems with the right data at the right time. It acts as an intermediary between large language models and underlying apps, databases, and services, enabling AI to retrieve relevant, up-to-date context without tightly coupling model logic to specific data sources. Its primary purpose is to provide a unified, consistent way to query and assemble context across heterogeneous systems for more accurate and grounded AI responses.
Airweave offers a shared retrieval API that abstracts away the complexity of working with multiple backends, such as SQL/NoSQL databases, internal tools, and third-party applications. It supports flexible retrieval strategies, including semantic search, structured queries, and hybrid approaches, allowing developers to tailor context assembly to their use case. The tool is designed to be composable and extensible, making it easier to plug in new data sources or swap out vector stores and retrieval engines without rewriting application logic. Because it is open source, teams can self-host, audit, and customize the retrieval layer to meet security, compliance, and performance requirements.
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