Enables users to build and manage a complete retrieval-augmented generation pipeline through conversation, including file ingestion, collection management, hybrid search, reranking, citations, and a guided setup wizard.
Automated RAG pipeline optimization and serving. It interviews users, builds and evaluates candidate configurations on their data, and registers the best ones as a fleet queryable via MCP.
Enables Claude to inspect, configure, run, and modify individual RAG/agent pipeline stages (retrieve, rerank, generate, eval) as structured typed tool calls, and execute the full pipeline end to end.
Creates deterministic, auditable vector databases from any content source with deployable RAG applications. Supports multiple embedding providers and vector databases with fine-grained pipeline control or project-based workflows.
Enables document Q&A and knowledge retrieval through hybrid semantic and keyword search, with tools for document ingestion, chunking, summarization, PII redaction, and RAGAS-based evaluation.
