Reducto AI - Document Parsing for LLM Pipelines
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Y Combinator-backed document ingestion platform that converts unstructured documents into LLM-optimized structured data, achieving >99% accuracy across 1 billion+ pages processed.
Overview
Reducto AI is a San Francisco-based startup founded in 2023 that specializes in document ingestion for LLM workflows. In February 2026, the company closed a $75M Series B led by Andreessen Horowitz, bringing total funding to $108M from a16z, Benchmark, First Round Capital, Y Combinator, and BoxGroup. That round followed a $24.5M Series A led by Benchmark in April 2025 and an $8.4M seed led by First Round Capital in October 2024.
Unlike full-stack document intelligence platforms, Reducto positions itself as a specialized document ingestion layer that converts complex unstructured documents into structured data optimized for LLMs and vector databases. Monthly processing volume grew 6x in the six months following the Series A, reaching 1 billion pages processed to date - up from 250 million at the October 2025 milestone. Named AI-native customers include Harvey, Mercor, Rogo, and Scale AI; unnamed enterprise accounts include a Fortune 10 company, a Global Top 5 Hedge Fund, and category leaders in healthcare, insurance, and real estate. All growth figures and accuracy claims are self-reported; no independent analyst validation was found in available sources.
For broader context on this approach, see our guides on PDF to structured data conversion and document processing for RAG. See also the Reducto AI competitive analysis.
How Reducto AI Processes Documents
Reducto's core Parse API combines traditional computer vision with Vision-Language Models (VLMs) to produce LLM-ready output from 30+ document formats including PDFs, Excel, and PowerPoint. The architecture reflects a deliberate bet: rather than competing on base OCR accuracy alone, Reducto layers an Agentic OCR framework on top to correct last-mile parsing errors that the base model misses. Roadmap items - agentic chart extraction and agentic extraction review - extend this approach further. Whether the agentic correction layer outperforms competitors' base models remains unverified; no independent benchmarks comparing Reducto against AWS Textract, Azure Document Intelligence, or Unstructured were found.
Beyond parsing, the platform exposes additional endpoints: split, extract, and an unstructured document editing API - the last described by the company as the industry's first. In July 2025, Reducto expanded into document generation with the launch of Reducto Edit. The company also released RolmOCR, an Apache 2.0 licensed OCR model with 8.29B parameters that recorded 190,046 downloads in its first month, and Open-Source RD-TableBench for evaluating extraction performance on complex tables. Teams evaluating open-source alternatives for table extraction benchmarking may also reference document parsing benchmarks for independent methodology comparisons.
Reducto Studio provides an interactive workspace for building, evaluating, and deploying document pipelines - the interface layer connecting the API endpoints into end-to-end workflows.
Use Cases
Healthcare Document Processing
Reducto achieved 99.24% extraction accuracy in clinical SLAs on real patient cases, demonstrating performance in accuracy-critical regulated environments with complex medical documentation. The platform's BAA support for HIPAA and zero data retention policy address the data handling requirements common in this sector. Our healthcare claims automation guide covers industry-specific implementation patterns.
Insurance Claims Processing
Insurance sector deployments report up to 16x faster claim reviews with improved auditability, processing policy documents, claims forms, and supporting documentation at enterprise scale. The combination of burst handling at 1/10/100+ QPS tiers and SOC 2 certification addresses the volume and compliance requirements typical of large carriers.
Legal and Compliance
Enterprise customers including Harvey leverage Reducto for legal document processing, contract analysis, and compliance documentation where extraction accuracy and auditability are mission-critical. The platform's LLM-optimized output format is designed to feed directly into downstream legal AI workflows rather than requiring intermediate transformation steps.
Financial Services
A Global Top 5 Hedge Fund is among Reducto's unnamed enterprise accounts, alongside customers in real estate. The extract endpoint and structured JSON output support the financial document workflows - earnings filings, fund documents, loan packages - where data fidelity determines downstream analytical quality. Teams building investment research pipelines may also evaluate Parsewise, a Y Combinator-backed platform targeting similar extraction use cases for investment teams and underwriters. Financial services teams requiring deeper document analytics and research automation may also consider Acuity Knowledge Partners, which serves 800+ institutions with agentic AI for document-intensive research workflows.
Technical Specifications
| Feature | Specification |
|---|---|
| Accuracy | >99% extraction accuracy (self-reported) |
| Uptime | 99.9% availability |
| QPS Tiers | 1 / 10 / 100+ queries per second |
| OCR Model | RolmOCR (8.29B parameters, Apache 2.0) |
| Supported Formats | 30+ including PDF, Excel, PowerPoint, images, scans |
| Output Format | LLM-optimized structured data |
| API Endpoints | Parse, split, extract, document editing |
| Deployment | Cloud, on-premise, VPC |
| Compliance | SOC 2 certified, HIPAA (BAA available) |
| Data Retention | Zero data retention |
| Auth | SSO / SAML |
| SLAs | Custom SLAs available |
| AWS Marketplace | prodview-55iompy2idj36 |
| Pricing | Usage-based, pay-as-you-go; flexible tier for early-stage teams (specific per-page costs not disclosed) |
| Open Source | RolmOCR (Apache 2.0), RD-TableBench |
Resources
- Company Website
- Documentation
- Case Studies
- RolmOCR Model
- Reducto Edit
- AWS Marketplace Listing
- Series B Announcement
- AWS Marketplace Blog Post
- Competitive Analysis: Reducto AI
Video about reducto.ai - Review
Company Information
Reducto AI was founded in 2023 by Adit Abraham and Raunak Chowdhuri and went through Y Combinator before raising institutional funding. The company is headquartered in San Francisco. Total funding stands at $108M across three rounds: $8.4M seed (First Round Capital, October 2024), $24.5M Series A (Benchmark, April 2025), and $75M Series B (a16z, February 2026).
The AWS Marketplace listing, announced alongside the Series B, is a procurement play as much as a product milestone: enterprise buyers with committed AWS spend can now route Reducto purchases through existing contracts, removing a common friction point in vendor evaluation. The company explicitly positions Reducto against AWS Textract as the higher-accuracy alternative for complex document types - a direct challenge to Textract's incumbency advantage inside AWS environments. Teams evaluating open-source alternatives for LLM pipeline ingestion may also consider Unstract, which takes a no-code approach to the same document-to-structured-data problem with hallucination mitigation built into its extraction layer.
Transfer of Personal Data: Reducto processes and stores information in the U.S. and other countries. Use of their services authorizes transfer of personal information across national borders in accordance with applicable laws. See Reducto Terms of Service for details.
