A fully managed Retrieval-Augmented Generation (RAG) service that automates the entire pipeline—ingestion, chunking, embedding, retrieval and reranking.
Features:
Diverse sources
Connect to data in S3, Dropbox, and local file system.
Chunking strategies
Smart defaults out of the box, deep control when you need it. Pick semantic for topical shifts, hierarchical for precise retrieval with broader grounding, section-based for structured docs, or fixed-length for sheer speed - then evaluate, adjust, and re-index until retrieval lands.
Hybrid search and advanced reranking
Enhance retrieval accuracy with sophisticated search techniques that combine keyword and semantic results. Enable bge-reranker-v2-m3 to re-score results with cross-encoder precision. Add a reranking step to your retrieval pipeline. Higher precision on the top results, $0.010 per 1M tokens.
New embedding models
Additional open-source models (e5-large-v2, bge-m3) are now available, offering high-precision English retrieval and versatile support for long-form, multilingual documents.
Model Context Protocol (MCP) Support
Turn your Knowledge Bases into a plug-and-play retrieval tool for any MCP-compatible agent framework.