Reducto

The API is structured around document parsing jobs: submit a document, receive structured extraction results including text chunks with layout metadata, tables as structured arrays, and figure references. The layout-aware chunking is the key differentiator — it respects page structure, headers, and columns rather than treating the document as a flat text stream. That produces chunks that contain coherent semantic units rather than arbitrary text fragments.

Reliability for document parsing has correctness stakes that differ from most API categories — a parsing failure may silently produce incomplete extraction rather than an obvious error. Teams should validate extraction completeness on a representative sample of their document corpus before relying on Reducto for production RAG pipelines. The processing pipeline is asynchronous for longer documents, requiring polling or webhook handling.

Reducto is an AI-native document parsing API designed specifically for the extraction workflows that RAG pipelines need — layout-aware chunking that respects document structure, table extraction that produces structured data rather than raw text, and figure recognition for multimodal content. Those capabilities matter significantly for agents that need to process PDFs and documents as knowledge inputs, because naive text extraction from complex documents produces poor retrieval quality.

Authentication uses API keys with straightforward integration. The simplicity of the auth model reflects the product's focus on being easy to integrate into document processing pipelines. Teams should treat document content as sensitive data in transit and ensure API key management follows standard credential hygiene.

Documentation covers the core extraction use cases clearly with concrete examples of API requests and expected output formats. The chunking and table extraction behavior is explained enough to set expectations appropriately. Teams new to document parsing for RAG will find the conceptual framing useful alongside the API reference.