Reducto vs Azure Document Intelligence | Compared

Reducto leads independent benchmark on structured extraction with Deep Extract

Helping everyone from startups to Fortune 10 enterprises unlock their data.

Dimension	Reducto	Azure Document Intelligence
Category	Full platform: parse, extract, split, classify, and edit in one API.	Cloud OCR service with prebuilt models and custom model training.
Parsing accuracy	Yes: Up to 99–100% zero-shot accuracy on complex documents.	Partial: Reliable on standard layouts; degrades on multi-column and irregular structure.
Extraction paradigm	Yes: Zero-shot schema extraction with per-field citations; no model training.	Yes: Prebuilt models for invoices, receipts, IDs; custom training for other formats.
Table extraction	Yes: 0.90 on RD-TableBench; merged cells, multi-level headers, borderless tables.	Partial: Solid on standard tables; degrades on merged cells and multi-level headers.
Handwriting & checkboxes	Yes: Handwriting and checkbox extraction in the standard parse pipeline.	Partial: Cursive handwriting unreliable; checkbox accuracy inconsistent across form styles.
Deployment & compliance	Yes: SOC 2 Type II, HIPAA, zero data retention; VPC to air-gapped.	Yes: Azure-only; SOC 2, HIPAA, FedRAMP within Azure compliance framework.
Platform breadth	Yes: Parse, Extract, Split, Classify, Edit; MCP server, CLI, SDKs, Studio.	Partial: OCR and extraction only; classification and editing need other Azure services.
Pricing	From $0.015/page pay-as-you-go; 15,000 free credits.	~$0.03/page layout analysis, per page per model; 500 free pages/month.

Parse one of your hardest documents in Studio and compare the output side by side.

Your documents vary in format or layout, and training and maintaining a custom model per document type doesn't scale.
Accuracy on complex content (dense tables, handwriting, checkboxes, charts, multi-column scans) gates your downstream LLM output.
You need deployment flexibility: VPC on any cloud, on-prem, or air-gapped, with SOC 2 Type II, HIPAA, and zero data retention.
Your workflow extends beyond OCR into classification, splitting, extraction with per-field citations, or writing data back into documents.
You're feeding LLM or agent pipelines and want structured, citation-linked output instead of raw OCR plus post-processing code.

Your organization is standardized on Azure and an existing Microsoft enterprise agreement makes procurement effectively free.
Your documents are uniform, common types (invoices, receipts, IDs) that prebuilt models already cover well.
You have fixed document formats that rarely change, where training a custom model once is a reasonable one-time cost.
You need FedRAMP or other certifications that Azure's compliance framework provides out of the box.