Reducto is a document ingestion API that turns complex PDFs and scans into reliably structured data for AI systems.
Reducto focuses on ingestion accuracy for enterprise document AI. It parses layouts, tables, forms, and handwriting with state-of-the-art accuracy, returning structured chunks, metadata, and citations that downstream LLM applications can trust. Customers use it to build RAG pipelines where extraction errors are expensive — financial filings, medical records, legal documents — and its benchmarks on hard document sets are a major reason teams switch.
Reducto’s emphasis on citations matters for regulated use: extracted values link back to exact source locations, so analysts can verify claims without rereading entire documents. Benchmarks on hard public document sets have made it a reference point for ingestion quality in the RAG tooling space.
Reducto’s customers are mostly teams where a missed clause or misread number has consequences: diligence analysts, claims processors, compliance reviewers. The API’s reliability at that standard is why many RAG platforms build on it despite newer, cheaper entrants.
Reducto is priced by pages processed through usage-based plans; teams contact sales for onboarding and enterprise terms.
AI teams in finance, healthcare, and legal building document workflows where extraction precision directly affects outcomes.
Reducto offers trial access for evaluation; production use is usage-based paid.
Yes, Reducto is entirely API-first with SDKs for common languages.
Broad platforms cover many document types; Reducto competes purely on ingestion accuracy for the hardest parsing cases.
Yes, its OCR stack covers handwriting and scans in addition to born-digital documents.
Pricing is usage-based per page, with enterprise agreements for high-volume pipelines.
High-volume processing is a design goal; specifics are planned with enterprise customers.
Data handling follows customer agreements with configurable retention for sensitive workloads.
Yes, OCR and layout analysis handle scanned and photographed documents well.
Table extraction is a core strength, returning structured rows with cell fidelity.
Yes, OCR and layout analysis cover scans, photos, and born-digital documents with the same structured output quality.
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