Unstructured built one of the earlier document processing libraries, and many teams started there as a foundation for their LLM pipelines. Reducto is the complete agentic document platform built for teams who have outgrown a parsing library and need accuracy, compliance, and a full document workflow in one place. Many of Reducto's current enterprise customers made that exact migration.
Last updated: May 20, 2026
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Reducto is the stronger choice for AI teams that need production-grade accuracy, enterprise compliance, and a complete document platform beyond parsing. Many teams who used Unstructured as an early foundation have migrated to Reducto as their workloads scaled and document complexity increased.
| Reducto | Unstructured | |
|---|---|---|
| Product category | Agentic document platform. Covers the full document lifecycle: parse, classify, split, extract, edit, generate, redact, and orchestrate in one API. | Document processing library. Converts files into structured text and elements for LLM pipelines. Product stops at extraction and ingestion. |
| Extraction quality on complex documents | Up to 99-100% accuracy on real-world documents with complex layouts. Zero-shot performance on tables, charts, figures, handwriting, and scans without template setup or model retraining. | Reliable on common document layouts. Accuracy is mixed on complex document types, and many early Reducto customers migrated specifically because of quality gaps on long-tail and high-complexity documents. |
| 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 quality is a known weak point. No documented agentic reconstruction pass for complex table layouts. |
| Spatial citations and sub-page regions | Every extracted field is linked to its exact position in the source document via bounding-box citations. Citations are viewable in Reducto Studio and accessible via API for downstream audit and verification. | No spatial citations. Extracted elements do not carry sub-page bounding-box coordinates linking values back to their source position. |
| Parsing approach | Vision-first, multi-pass pipeline combining computer vision, OCR, VLM, and Agentic OCR. Each pass targets accuracy on a specific content type: text, tables, figures, handwriting. | Combines OCR with LLMs via a single enrichment pass. Open-source foundation with community-contributed model support. |
| Agentic extraction (Deep Extract) | Deep Extract runs an iterative self-correction loop: the model verifies output against the source document and re-extracts until a quality threshold is met. Verification criteria are configurable (for example, line items must sum to the stated total). | Not available. Unstructured applies a single enrichment pass. No iterative extraction loop or self-correction mechanism is documented. |
| Document editing and form filling | Edit API writes data back into documents. Fills PDF form fields and DOCX controls using natural-language instructions with no pre-defined coordinates required. Supports scanned forms and digital PDFs. | Not available. Unstructured is read-only. There is no API endpoint for writing or editing document content. |
| Document splitting | Split API segments documents into named logical sections using natural-language category descriptions (for example, Disclosures, Financial Statements). Deep Split mode adds iterative refinement for multi-document packets. | Not available as a standalone document-section capability. Chunking strategies (by character, by title, by page) operate post-parse at the chunk level. |
| Processing speed and scalability | Optimized production pipelines with autoscaling. Handles spiky, bursty workloads without manual provisioning. Dynamic and dedicated worker options available. | Notably slower in benchmarks: 51 seconds for 1 page, 141 seconds for 50 pages. No documented autoscaling architecture for production bursts. |
| Multilingual support | 100+ languages including mixed-language documents. Language detection is automatic. | Multilingual support via community-contributed OCR engines. Coverage and accuracy vary by language and document type. |
| Platform breadth | 30+ file types. Full suite of endpoints: Parse, Classify, Split, Extract, Edit. Agent-ready tooling including MCP server, CLI, and workflow orchestration with human-in-the-loop (HITL) support. | 65+ file types including audio and video. Focused on parsing and ingestion. No editing, form filling, or workflow orchestration endpoints in the core library. |
| Enterprise compliance | SOC 2 Type II, HIPAA compliant (BAA available). Zero data retention on Growth and above (24-hour auto-delete). EU and AU regional data residency endpoints available. | SOC 2 Type II, HIPAA compliant, ISO 27001, GDPR. Zero data retention listed. No documented regional data residency endpoints. |
| Deployment options | Cloud (multi-tenant), hybrid VPC (data stays in customer cloud, compute offloaded to Reducto), full VPC (AWS, GCP, Azure), on-premises, and fully air-gapped. Dynamic and dedicated worker tiers. | SaaS, dedicated instance, VPC (AWS, Azure, GCP), and bare metal. No documented hybrid VPC or air-gapped deployment option. |
Ready to see Reducto in action?
Reducto is the right choice when you need more than a parser: a complete platform that handles every document task at enterprise scale.
Unstructured may be a reasonable starting point for teams in early exploration stages or with strong open-source preferences.
