Azure Document Intelligence is a solid cloud OCR primitive for teams already standardized on Azure, offering reliable deterministic extraction with strong procurement integration. Reducto is the complete agentic document platform for AI teams who need stronger performance on complex documents, accurate figure and checkbox extraction, and a full document workflow that extends far beyond OCR primitives.
Last updated: May 20, 2026
Book a demo with Reducto
Reducto consistently delivers high accuracy and reliable extraction where other systems fail, from the common scenarios (handwriting, complex tables) to the specialized ones (strikethroughs, redlines, advanced chart extraction).
Read and extract critical data out of documents, then fill out forms and create net-new documents all within Reducto.
Reducto provides flexible, pay-as-you-go pricing for small stage startups all the way to custom volume discounts for growing teams and enterprises. Plans start as low as $0.015/page parse and even lower at higher volume.
Reducto is built by a team of researchers and engineers advancing the frontier of document intelligence in both academic and production settings.
Azure Document Intelligence offers reliable deterministic OCR with strong Azure procurement advantages and competitive latency on standard documents. Reducto wins when extraction complexity, checkbox and handwriting accuracy, spatial citations, and a complete end-to-end document platform matter more than cloud consolidation.
| Reducto | Azure Document Intelligence | |
|---|---|---|
| Parsing accuracy on complex layouts | Multi-pass Agentic OCR combining computer vision, OCR, and VLM. Up to 99-100% accuracy on complex real-world documents including multi-column layouts, mixed-content pages, and scanned documents. | Reliable on standard document layouts with competitive latency. Accuracy degrades on complex multi-column layouts, overlapping content regions, and documents with highly irregular structure. |
| Figure and chart extraction | Purpose-built figure and chart extraction. Converts charts to structured tabular data and returns figure captions and associated labels as structured output. | Figure and chart extraction is not supported in the general layout model. Azure Document Intelligence treats figures as unstructured image regions without structured data extraction. |
| Checkbox extraction | Accurate checkbox detection and state extraction across scanned forms, digital PDFs, and mixed-format documents. Returns checkbox state and spatial position. | Checkbox extraction is a documented weakness. Pre-built form models cover some scenarios, but accuracy on varied checkbox styles, scanned forms, and mixed-format documents is inconsistent. |
| Handwriting recognition | Strong handwriting recognition built into the standard parse pipeline. Handles mixed handwritten and printed text on the same page without a separate model or routing step. | Handwriting recognition is a documented weak point. Performance is poor on cursive and informal handwriting, and mixed handwriting and print on the same page is unreliable. |
| Spatial citations and sub-page regions | Every extracted field is linked to its exact bounding-box position in the source document. Citations are accessible via API and viewable in Reducto Studio for audit and verification. | No spatial sub-page citations for extracted values. Element-level bounding boxes are returned in the raw API response but are not surfaced as first-class extraction citations. |
| Multilingual support | 100+ languages including mixed-language documents. Language detection is automatic within the standard pipeline. | 100+ languages supported. Strong multilingual coverage, particularly for European languages, is a genuine strength for Azure-based teams. |
| Table extraction | 0.90 table similarity score on RD-TableBench. Agentic table pass reconstructs merged cells, multi-level headers, rotated text, and tables with missing or faint borders. | Table extraction is available in the layout model. Solid performance on standard tables. Accuracy degrades on complex layouts with merged cells, irregular column structures, or multi-level headers. |
| Document editing | Edit API writes data back into documents. Fills PDF form fields and DOCX controls using natural-language instructions. Supports scanned forms and digital PDFs. | Not available. Azure Document Intelligence is read-only. There is no API for writing or editing document content. |
| Platform breadth | Full platform: Parse, Classify, Split, Extract, and Edit in one API. MCP server, CLI, and HITL workflow orchestration included. Reducto Studio provides a visual pipeline environment. | OCR and structured extraction only, with pre-built models for common document types. Classification, editing, workflow orchestration, and agent tooling require additional Azure services and custom integration. |
| Pricing model | Pay-as-you-go from $0.015/page with 15,000 free credits to start. Single pricing model regardless of document type. Volume discounts on Growth tier and above. | Per-page pricing at approximately $0.03/page for layout analysis. Free tier available for up to 500 pages per month. Strong fit for teams with existing Azure enterprise agreements. |
| Ease of use and developer experience | Python, Node.js, and Go SDKs. Reducto Studio for visual pipeline building and citation inspection. Single unified API regardless of document type or content mix. | Azure SDK integration for teams already on Azure. Pre-built models reduce setup time for common document types. Model selection and routing decisions add overhead for mixed document workflows. |
| Enterprise deployment | Cloud (multi-tenant), hybrid VPC, full VPC (AWS, GCP, Azure), on-premises, and fully air-gapped. SOC 2 Type II, HIPAA compliant with BAA available. | Azure-only deployment. Strong procurement advantage for teams with existing Azure enterprise agreements. SOC 2, HIPAA, and FedRAMP certifications available within the Azure compliance framework. |
Reducto's multi-pass system utilizes both OCR and vision language models for unmatched accuracy and reliability.
Reducto first uses layout-aware models to break down the document visually, capturing regions, tables, figures, and text.
Like a human editor, our Agentic model can detect minor mistakes and correct them, ensuring accuracy even in the most detailed cases.
Vision-language models then interpret each region in context—linking labels to values, understanding tables, and classifying segments.
Hands-on forward deployed support and tailored SLAs to meet your enterprise needs.
Run Reducto entirely within your own infrastructure—ideal for strict security, compliance, and data residency requirements.
Battle-tested infrastructure you can trust in production and at scale.
Enterprise-grade security, certified for sensitive and regulated data. View our security policies here.
