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Frameworks and engines for sequencing multi-step tasks, tool execution, and model interactions to resolve complex queries.
Distinguishing note: Focuses on the orchestration of agentic workflows and multi-step reasoning rather than generic model inference or chat interfaces.
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Quivr is a retrieval-augmented generation platform designed to transform raw documents into searchable knowledge bases. It functions as a centralized environment where users can ingest files, index them into vector databases, and interact with language models to receive contextually relevant, data-backed responses. The platform distinguishes itself through an agentic workflow orchestrator that sequences retrieval tasks, tool execution, and model interactions to resolve complex, multi-step queries. This engine is entirely configuration-driven, allowing users to define document ingestion, chunk
A configuration-driven engine that sequences retrieval tasks, tool execution, and language model interactions to resolve complex and multi-step user queries.