Shared retrieval layer
Lets AI systems query one retrieval layer instead of wiring separate search logic into each app or agent.
Airweave è un livello open source per il recupero del contesto destinato ad agenti AI e sistemi RAG. Collega app e database, sincronizza i dati in tempo reale e offre un recupero fondato tramite una ricerca unificata.
Airweave is an open-source context retrieval layer for AI agents and RAG systems. It sits between data sources and AI systems so applications can retrieve relevant context from connected apps, tools, and databases instead of relying on isolated retrieval logic.
The product is designed to make grounded answers easier to generate on demand. The homepage shows a workflow where users create a searchable collection, connect sources, sync data, and then query that collection through an LLM-friendly interface. Airweave also publishes Academy articles about context engineering and information retrieval, suggesting the product is aimed at teams building retrieval infrastructure for AI systems.
Lets AI systems query one retrieval layer instead of wiring separate search logic into each app or agent.
Supports semantic, keyword, hybrid, time-aware, and agentic search so agents can match both literal terms and user intent.
Keeps connected data current with real-time syncing rather than static snapshots or manual refreshes.
Connects apps, tools, docs, and databases, then exposes them through a unified search interface for AI systems.
Provides an SDK-based workflow for creating a collection, attaching a source connection, and querying retrieved context.
Build agents that answer questions using live context from connected apps and databases instead of static prompt data.
Create retrieval infrastructure for RAG pipelines that need a shared layer for searching across multiple sources.
Search synced code, issue trackers, or workspace data to enrich alerts and troubleshooting workflows, as shown in Airweave's own internal usage example.
Query several connected systems through one interface when the same agent needs context from different tools in a single request.
Airweave is a context retrieval layer for AI agents and RAG systems. It connects to apps, tools, and databases, syncs their data in real time, and exposes it through a unified search interface.
The homepage shows a Python SDK example and installation commands for `airweave-sdk`, and it links readers to the quickstart documentation at `docs.airweave.ai/quickstart`.
The product description and examples show Airweave being used to retrieve context from apps and databases, including a synced GitHub codebase and a Linear workspace.
The source material supports a shared retrieval workflow for AI agents and RAG pipelines, but it does not publish pricing details on the site; the `/pricing` page currently returns a 404.
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