Reducto vs Unstructured | Platform vs Parsing Library

Reducto leads independent benchmark on structured extraction with Deep Extract

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

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Dimension	Reducto	Unstructured
Category	Full platform: parse, extract, split, classify, and edit in one API.	Open-source parsing and ETL library, with a hosted platform on top.
Parsing accuracy	Yes: Up to 99–100% zero-shot accuracy on complex documents.	Partial: Solid on standard types; mixed on complex layouts and long-tail documents.
Table extraction	Yes: 0.90 on RD-TableBench; merged cells, multi-level headers, borderless tables.	Partial: Documented weak point; no reconstruction pass for irregular tables.
Structured extraction	Yes: Deep Extract: 99.6% precision and recall on micro1's benchmark.	Partial: Single enrichment pass; no self-correction loop or spatial citations.
Platform breadth	Yes: Parse, Extract, Split, Classify, Edit; MCP server, CLI, SDKs, Studio.	Partial: 65+ file types and broad connectors; no editing or form filling.
Enterprise readiness	Yes: SOC 2 Type II, HIPAA, zero data retention; VPC to air-gapped.	Yes: SOC 2 Type II, HIPAA, ISO 27001, GDPR on hosted platform.
Operations at scale	Yes: Managed autoscaling for bursty workloads; 5B+ pages processed.	No: Self-hosting means you own scaling; no documented autoscaling.
Pricing	From $0.015/page pay-as-you-go; 15,000 free credits.	Open source is free to self-host; hosted platform priced separately.

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

Accuracy on complex, long-tail documents is the bottleneck: dense tables, scans, charts, handwriting, mixed-content pages.
You'd rather delete pipeline code than maintain it: parsing, extraction, splitting, classification, and editing in one managed API.
You're in a regulated industry where zero data retention, a BAA, or VPC/on-prem/air-gapped deployment are non-negotiable.
You need spatial citations linking every extracted value to its source for compliance, audit, or human review.
You're running production workloads that need autoscaling for bursty volume, not a self-managed cluster.

You want an open-source, self-hosted library you can inspect, modify, and run entirely on your own infrastructure.
Your priority is broad ETL connector coverage into cloud storage and data warehouses, across a wide range of file types.
You're prototyping with standard document types where complex-layout accuracy isn't yet critical, and community support fits your workflow.