Open-source context retrieval layer for AI agents to search across apps and databases in real time.
Airweave is an open-source context retrieval layer that sits between AI systems and data sources, enabling AI agents and RAG pipelines to retrieve relevant context from multiple apps and databases in a single request. It syncs data in real time and exposes it through a unified search interface, supporting semantic, keyword, hybrid, time-aware, and agentic search. With prebuilt connectors for over 50 data sources, it integrates seamlessly with frameworks like LangChain, Composio, and Pipedream.
Key Features
check_circleUnified search across multiple data sources
check_circleReal-time data sync
check_circlePrebuilt connectors for 50+ sources
check_circleSemantic, keyword, hybrid, time-aware, and agentic search
lightbulbAI agents query Airweave to retrieve up-to-date customer data from CRM and billing systems, enabling accurate support responses without manual data gathering.
lightbulbRAG pipelines use Airweave as a shared retrieval layer to ground LLM answers on real-time data from multiple enterprise databases, reducing hallucinations.
lightbulbEngineering teams integrate Airweave with LangChain to build agents that search across internal wikis, code repos, and issue trackers in one call.
lightbulbSales teams deploy AI assistants that pull contract details and pricing from connected apps via Airweave, speeding up proposal generation.
lightbulbData analysts sync data from various SaaS tools into Airweave collections, then query them using natural language to get instant insights.
lightbulbDevOps teams connect monitoring tools and logs to Airweave, allowing incident response agents to retrieve relevant context during outages.
context retrievalRAGAI agentssearchdata syncopen sourceconnectorsLangChainknowledge base
