Zero-Latency RAG: Retrieval-Augmented Generation on a Mesh
Traditional RAG hits a server. Zap's RAG queries every device in the room. Here's how distributed retrieval achieves sub-millisecond context injection.
Zap Team
Engineering
Retrieval-Augmented Generation (RAG) is the gold standard for grounding AI in facts. But typical RAG setups are slow. Zap's Mesh RAG brings retrieval times down to sub-milliseconds.
Distributed Retrieval
In a Zap mesh, every device acts as a "mini-search engine." When you ask a question:
•A query is broadcast to the mesh.
•Each device checks its local vector database.
•The most relevant context is sent back to the requesting node.
•The LLM synthesizes the answer instantly.
Why Mesh RAG Wins
Because the data doesn't have to travel to a server and wait for a database query, the AI feels like an extension of your own thought process — fast, fluid, and always accurate.