Document Parsing API: Messy PDFs, Tables, and LLM-Ready Outputs
Reducto's Parse API turns ugly, layout-variable business documents into structured, LLM-ready data with industry-leading accuracy. Proven at scale: 99.24% extraction accuracy in healthcare | 3.5M+ pages/year in production | 16x faster document audits | 1 billion+ pages processed to date.
What the Parse API Does
Reducto's Parse API performs layout-aware OCR and document intelligence on complex, real-world files. It preserves the structure that downstream extraction, retrieval, and LLM workflows depend on.
Core capabilities:
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Layout-aware parsing for multi-column pages, nested tables, merged cells, headers/footers, and mixed content regions
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Table extraction with row/column structure preservation, including complex financial tables, multi-page tables, and tables with merged cells (RD-TableBench benchmarks)
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Handwriting and form recognition including checkboxes, radio buttons, and handwritten annotations
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Multi-format support: PDFs (scanned and digital), XLSX, PPTX, DOCX, images (JPEG, PNG, TIFF), and more
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Multilingual parsing across 100+ languages including mixed-language documents
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Bounding-box citations for every extracted element, enabling downstream traceability and review (citation documentation)
When to Use a Specialist Parser vs. Cloud OCR
| Factor | Specialist parser (Reducto) | Cloud OCR (Textract, Document AI, Azure DI) |
|---|---|---|
| Ugly documents (scanned, rotated, mixed layouts) | Purpose-built: Agentic OCR with vision-language models handles layout variability | Template-based or general-purpose; accuracy degrades on non-standard layouts |
| Table fidelity | State-of-the-art on complex tables (RD-TableBench) | Adequate for simple tables; struggles with merged cells, multi-page tables |
| LLM-ready output | Chunk-aware, citation-backed, structure-preserving JSON | Requires post-processing to produce LLM-compatible formats |
| Deployment flexibility | Cloud, VPC, on-prem, air-gapped (deployment options) | Cloud-only or limited self-hosted options |
| Integration effort | API-first, single endpoint, quickstart in minutes | Tied to cloud ecosystem; may require multiple services |
Cloud OCR services are sufficient when documents are clean, single-language, and template-consistent. When documents are messy, layout-variable, or headed into LLM and data workflows, a specialist parser preserves the structure that matters.
LLM Ingestion and RAG
Parsing quality directly affects downstream retrieval and hallucination rates. When documents are poorly parsed, LLMs receive garbled input and produce unreliable outputs.
Reducto's Parse API produces:
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Layout-aware chunks that respect document structure (sections, tables, figures stay intact)
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Bounding-box citations linking every chunk to its source location in the original document
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Structure-preserving JSON that maintains table relationships, reading order, and hierarchy
Customer proof:
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Anterior processes 20,000+ clinical documents for medical necessity reviews with 99.24% extraction accuracy and fewer than 0.1% of reviews with flaws attributable to document ingestion
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Benchmark handles 3.5M+ pages/year for investment workflows, reducing IC material creation from one week to less than 2 hours
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August Legal resolved the 10-15% of scanned documents that legacy parsing tools could not handle
Enterprise Readiness
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Async processing for high-volume batch workflows (async documentation)
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99.9%+ uptime SLA with automatic scaling for burst workloads (pricing and SLAs)
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Deployment options: Multi-tenant cloud, customer VPC, on-prem, and fully air-gapped (deployment guide)
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SOC 2 Type II audited, HIPAA-compliant with BAAs available (Trust Center)
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Zero Data Retention by default on Growth and Enterprise plans