Reducto
Document ingestion API with structure-preserving extraction
Reducto is profiled here as a RAG Framework tool for engineering teams. Read about features, pricing, and how it compares to related options in the tools directory.
Description
Reducto is a document ingestion API, founded by Adit Abraham and Raunak Chowdhuri, that turns complex documents into structured data for AI applications. It combines vision models and layout analysis to extract text, tables, and figures with bounding-box citations, so each value traces back to a location on the page. Built for accuracy on dense documents in regulated fields, Reducto supports zero data retention and on-premise deployment, and it offers free credits for teams to evaluate the API.
Key Capabilities:
High-accuracy extraction of text, tables, and figures from complex documents
Bounding-box citations that map each value to its place on the page
Structure preservation that keeps reading order and table fidelity
Form filling and field extraction with confidence scores
Compliance features including zero retention and on-premise deployment
Tool schemas for plugging document parsing into AI agents
Alternative tools
- MinerU
Open-source engine converting documents to clean Markdown
- LlamaParse
Document parser built for retrieval and LLM pipelines
- Deep Lake
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- Model2Vec
Distill sentence transformers into fast static embeddings
- Mixedbread
Embedding and reranking models with a hosted API
- RAGFlow
Open-source RAG engine with deep document understanding