llms.txt snapshot

# Reducto

> Reducto is the complete agentic document platform for leading AI teams that need performance at enterprise scale. Document work starts here: the most accurate document processing available — parsing, extraction, splitting, and classification — plus document editing, workflows, and agent-ready tooling, in one platform.

Reducto provides a comprehensive toolkit for working with documents the way a human would, combining custom in-house models with leading frontier models to power efficient, accurate document workflows. Teams replacing brittle OCR pipelines and legacy intelligent document processing (IDP) tools choose Reducto for zero-shot accuracy on complex documents — tables, charts, figures, handwriting, scans — across 30+ file types. Over 5 billion pages processed for AI teams at companies like Harvey, Scale AI, and Vanta.

Get started free: sign up at https://studio.reducto.ai/ for 15,000 free credits. AI agents can start with the [Agent skill](https://reducto.ai/SKILL.md), then connect through the MCP server or CLI (see Developer Tools below); the full documentation index for LLMs lives at https://docs.reducto.ai/llms.txt, and every docs page is available as raw Markdown by appending `.md` to its URL.

Agent skills discovery: https://reducto.ai/.well-known/agent-skills/index.json

## Products

- [Parse](https://reducto.ai/parse): The ingestion layer. Turn PDFs, scans, spreadsheets, and slides into structured, citation-ready JSON for LLM, RAG, and agent workloads at production scale. API docs: https://docs.reducto.ai/parse/overview.md. For choosing a parser, see [Best Document Parsers for RAG](https://reducto.ai/guides/best-document-parsers-rag).
- [Split](https://reducto.ai/split): The segmentation layer. Describe sections in plain language; Split returns the page ranges for each. Partition keys group repeating sub-documents automatically. API docs: https://docs.reducto.ai/split.md. For where segmentation fits in a larger pipeline, see [Intelligent Document Processing](https://reducto.ai/guides/intelligent-document-processing).
- [Extract](https://reducto.ai/extract): The extraction layer. Return defined fields as typed JSON with a citation and bounding box on every value. Schemas, prompts, and Deep Extract for production accuracy on the long tail. API docs: https://docs.reducto.ai/extract/overview.md. For comparing extraction options before you build, see [Best Enterprise Data Extraction Software](https://reducto.ai/guides/best-enterprise-data-extraction-software).
- [Classify](https://reducto.ai/classify): The routing layer. Define your taxonomy in plain language and Classify returns the best match plus per-criterion confidence, fast enough to gate every pipeline. API docs: https://docs.reducto.ai/classify/overview.md. For how classification platforms differ on routing and human review, see [Best Document Classification Software](https://reducto.ai/guides/best-document-classification-software-2026).
- [Edit](https://reducto.ai/edit): Closes the agentic document loop, turning extracted data back into a finished file. Vision-based field detection, reusable form schemas, and optional DOCX highlighting at production scale. API docs: https://docs.reducto.ai/editing/edit-overview.md. For the architecture around write-back steps, see [Document Workflow Automation](https://reducto.ai/guides/document-workflow-automation).
- [Studio](https://reducto.ai/studio): The no-code workspace for the platform. Build, test, and deploy document pipelines without code — same engine as the API, included with every plan. Docs: https://docs.reducto.ai/studio-quickstart.md. For scoring platforms against enterprise requirements, see [Enterprise IDP Evaluation Guide](https://reducto.ai/guides/idp-enterprise-evaluation).

## Key Differentiators

- **Accuracy where others aren't production ready**: zero-shot accuracy on complex documents; Deep Extract achieves 99% recall and precision on micro1's LongExtractionBench.
- **12+ models orchestrated**: automatic routing balances accuracy, latency, and throughput for each document's complications, continuously updated so your team doesn't chase the frontier. Reducto uses the best parts of frontier models rather than competing with them.
- **Long-tail robustness**: complex tables, charts, figures, handwriting, scans, checkboxes, equations, rotated pages, and multilingual documents — without templates, pre-labeling, or retraining when documents change.
- **Trustable outputs**: a citation and bounding box on every extracted value, with a side-by-side citation viewer in Studio.
- **One platform, every document task**: parse, split, extract, classify, and edit across 30+ file types — from raw file ingestion to agent-ready outputs and workflow orchestration, replacing 4–5 stitched-together vendors.

## Enterprise Readiness

- **Deployable anywhere**: hosted cloud, hybrid VPC, on-premises, and fully air-gapped to meet any data residency or security requirement
- **Compliant**: SOC 2 and HIPAA compliant (BAAs on Growth tier and above), zero data retention agreements on Growth tier and above
- **Production scale**: autoscaling built in for bursty workloads, white-glove forward-deployed engineering support, custom SLAs — over 5 billion pages processed
- Details: https://docs.reducto.ai/security/policies

## Industries & Use Cases

- [Finance](https://reducto.ai/industries/finance): Research reports, SEC filings, financial statements, and complex spreadsheets with decimal-level fidelity
- [Healthcare](https://reducto.ai/industries/healthcare): HIPAA-compliant processing of medical records, clinical notes, and claims
- [Legal](https://reducto.ai/industries/legal): Contract review, due diligence, NDAs, and filings with citation-ready accuracy
- [Insurance](https://reducto.ai/industries/insurance): Underwriting, claims, and ACORD forms on mixed-format evidence with audit-ready accuracy
- [Government & Defense](https://reducto.ai/industries/government): Secure processing of forms, permits, intelligence reports, and regulatory filings
- [Construction](https://reducto.ai/industries/construction): Blueprints, contracts, bids, invoices, and submittals
- [Logistics & Supply Chain](https://reducto.ai/industries/logistics-supply-chain): Bills of lading, customs forms, invoices, and shipping manifests

Cross-industry use cases: invoice and AP automation, KYC and onboarding, RAG preprocessing and embedding-optimized chunking, replacing manual data entry, and document generation workflows. Full case studies at https://reducto.ai/customers.

## Developer Tools

- [Agent skill](https://reducto.ai/SKILL.md): Self-contained SKILL.md for AI agents — setup, API usage, CLI, and MCP server instructions
- [Agent card](https://reducto.ai/.well-known/agent-card.json): Machine-readable agent card for Reducto's MCP and REST API interface
- [Agent discovery](https://reducto.ai/.well-known/agents.json): Discovery metadata linking Reducto's agent card, skill, and MCP endpoint
- [MCP discovery](https://reducto.ai/.well-known/mcp.json): Machine-readable MCP endpoint, authentication, and server-card metadata
- [Web MCP discovery](https://reducto.ai/.well-known/webmcp.json): Machine-readable Web MCP endpoint and server-card metadata
- [MCP server cards](https://reducto.ai/.well-known/mcp/server-cards.json): Index of Reducto's hosted MCP server cards
- [MCP server](https://docs.reducto.ai/mcp-server): Connect AI agents directly to Reducto via the Model Context Protocol. Hosted endpoint at https://mcp.reducto.ai/mcp (Bearer API key) or local via `uvx mcp-server-reducto`. Works with Claude Code, Claude Desktop, Codex, Cursor, VS Code, Windsurf, and any MCP client.
- [CLI](https://docs.reducto.ai/cli): `pip install reducto-cli` — parse, extract, split, classify, and edit from the terminal. Built for batch processing, scripting, and CI/CD; writes agent-readable Markdown next to each input file.
- [Agent integration guide](https://docs.reducto.ai/agent-guide.md): Complete, structured API reference written for AI coding agents
- [API documentation](https://docs.reducto.ai): Quickstarts, API reference, and SDKs for Python and Node. For the developer-side comparison of PDF extraction APIs and SDKs, see [Best PDF Data Extraction APIs and SDKs](https://reducto.ai/guides/best-pdf-data-extraction-apis-sdks)
- [OpenAPI specification](https://reducto.ai/openapi.json): OpenAPI 3.1 schema for the Reducto API
- [Documentation index for LLMs](https://docs.reducto.ai/llms.txt): Curated index of all docs pages, each available as raw Markdown
- [Checking API Health & Usage](https://docs.reducto.ai/reference/checking-api-health.md): How to check hosted API availability (via https://status.reducto.ai), usage, and throttling signals
- [Agent capabilities catalog](https://reducto.ai/.well-known/ai-catalog.json): Machine-readable list of Reducto's MCP servers
- [API catalog](https://reducto.ai/.well-known/api-catalog): RFC 9727 machine-readable index of Reducto's APIs, including the OpenAPI specification

## Get Started

- [Reducto Studio](https://studio.reducto.ai/): Sign up and get 15,000 free credits to try the platform on your own documents
- [Pricing](https://reducto.ai/pricing): Per-product plans — Standard (self-serve pay-as-you-go with 15,000 free credits), Growth (custom volume pricing with security and compliance features), and Enterprise (custom pricing with VPC, on-premises, and air-gapped deployment). r-1 Parse starts at $10 per 1,000 pages, and Extract starts at $20 per 1,000 pages with parsing included; Markdown: https://reducto.ai/pricing.md
- [Contact](https://reducto.ai/contact): Talk to sales or request a demo; Markdown: https://reducto.ai/contact.md
- [About](https://reducto.ai/about): Company, products, customers, compliance, and contact details; Markdown: https://reducto.ai/about.md
- [Developers](https://reducto.ai/developers): API, SDK, CLI, and MCP implementation guidance; Markdown: https://reducto.ai/developers.md
- [Authentication](https://reducto.ai/auth.md): How agents obtain and use Reducto API credentials

## Company

- [Customers](https://reducto.ai/customers): Case studies from AI teams running Reducto in production, including Harvey, Scale AI, and Vanta
- [Industries](https://reducto.ai/industries): Industry solutions hub
- [Blog](https://reducto.ai/blog): Technical articles, case studies, and product announcements
- [Engineering blog](https://reducto.ai/engineering/llms.txt): Deep dives from the team building Reducto, indexed for LLMs
- [Careers](https://reducto.ai/careers): Open positions
- [Reducto for Startups](https://reducto.ai/startups): Credits, startup pricing, and priority support for teams scaling document workflows from prototype to production
- [Reducto for YC](https://reducto.ai/yc): The exclusive YC deal — startup pricing and credits for YC companies, from the team that went through YC W24

## Optional

- [Cookbooks](https://reducto.ai/cookbooks): Templates and recipes for building with Reducto
- [Guides](https://reducto.ai/guides): Buyer guides, comparisons, benchmarks, and technical explainers for document AI
- [Compare](https://reducto.ai/compare): Tool-by-tool comparisons of Reducto vs other document parsing, OCR, and extraction options. For the published evidence behind those comparisons, see [Document AI Benchmark: OCR, Parsing and Extraction](https://reducto.ai/guides/document-ai-benchmark-ocr-parsing-extraction)
- [Privacy policy](https://reducto.ai/privacy)
- [Terms of service](https://reducto.ai/terms)

# Reducto — Full Overview for LLMs

> Reducto is the complete agentic document platform for leading AI teams that need performance at enterprise scale. Document work starts here: the most accurate document processing available — parsing, extraction, splitting, and classification — plus document editing, workflows, and agent-ready tooling, in one platform.

This file is the extended companion to https://reducto.ai/llms.txt. For complete, always-current API documentation, prefer https://docs.reducto.ai/llms.txt — every docs page there is available as raw Markdown by appending `.md` to its URL.

## Overview

Reducto provides a comprehensive toolkit for working with documents the way a human would, combining custom in-house models with leading frontier models to power efficient, accurate document workflows. It is used by AI-native companies and document-heavy enterprises — teams at Harvey, Scale AI, Vanta, and organizations up to Fortune 10 scale. Over 5 billion pages processed and counting.

Three things define the platform:

1. **Performance for you** — zero-shot accuracy on complex documents where other solutions aren't production ready, with automatic routing across 12+ orchestrated models to balance accuracy, latency, and throughput. Handles the long tail — tables, charts, figures, handwriting, scans — without templates or retraining. Deep Extract achieves 99% recall and precision on micro1's LongExtractionBench.
2. **Enterprise readiness** — deployable anywhere (hosted, VPC, on-premises, air-gapped), SOC 2 and HIPAA compliant with zero data retention agreements on the Growth tier and above, autoscaling for bursty workloads, white-glove support, and custom SLAs.
3. **Complete toolkit** — every document task in one platform: parse, split, extract, classify, and edit across 30+ file types, from raw file ingestion through agent-ready outputs and workflow orchestration.

**Get started free:** sign up at https://studio.reducto.ai/ for 15,000 free credits. AI agents can begin with the Agent skill at https://reducto.ai/SKILL.md, then connect through the MCP server or CLI.

## Products

- Parse — the ingestion layer: PDFs, scans, spreadsheets, and slides into structured, citation-ready JSON. https://reducto.ai/parse · https://docs.reducto.ai/api-reference/parse.md · choosing a parser: https://reducto.ai/guides/best-document-parsers-rag
- Split — the segmentation layer: describe sections in plain language, get page ranges back. https://reducto.ai/split · https://docs.reducto.ai/api-reference/split.md · segmentation in a full pipeline: https://reducto.ai/guides/intelligent-document-processing
- Extract — the extraction layer: typed JSON with a citation and bounding box on every value. https://reducto.ai/extract · https://docs.reducto.ai/api-reference/extract.md · comparing extraction tools: https://reducto.ai/guides/best-ai-data-extraction-tools-unstructured-documents
- Classify — the routing layer: plain-language taxonomy, best match plus per-criterion confidence. https://reducto.ai/classify · https://docs.reducto.ai/api-reference/classify.md · comparing classification platforms: https://reducto.ai/guides/best-document-classification-software-2026
- Edit — closes the loop: write extracted data back into finished PDF and DOCX files. https://reducto.ai/edit · https://docs.reducto.ai/api-reference/edit.md · workflow architecture: https://reducto.ai/guides/document-workflow-automation
- Studio — the no-code workspace, same engine as the API, included with every plan. https://reducto.ai/studio · https://studio.reducto.ai/ · evaluating platforms: https://reducto.ai/guides/idp-enterprise-evaluation

## Developer Tools

- Agent skill: self-contained setup instructions for AI agents, including API usage, CLI, and MCP server instructions. https://reducto.ai/SKILL.md
- Agent skills discovery index: https://reducto.ai/.well-known/agent-skills/index.json
- Agent card: Machine-readable agent card for Reducto's MCP and REST API interface. https://reducto.ai/.well-known/agent-card.json
- Agent discovery: Discovery metadata linking Reducto's agent card, skill, and MCP endpoint. https://reducto.ai/.well-known/agents.json
- MCP discovery: Machine-readable MCP endpoint, authentication, and server-card metadata. https://reducto.ai/.well-known/mcp.json
- Web MCP discovery: Machine-readable Web MCP endpoint and server-card metadata. https://reducto.ai/.well-known/webmcp.json
- MCP server cards: Index of Reducto's hosted MCP server cards. https://reducto.ai/.well-known/mcp/server-cards.json
- MCP server: hosted at https://mcp.reducto.ai/mcp (Bearer API key) or local via `uvx mcp-server-reducto` — guide at https://docs.reducto.ai/mcp-server, server cards at https://reducto.ai/.well-known/ai-catalog.json
- CLI: `pip install reducto-cli` — parse, extract, split, classify, and edit from the terminal. https://docs.reducto.ai/cli
- Agent integration guide: https://docs.reducto.ai/agent-guide.md · SDKs (Python, Node): https://docs.reducto.ai
- OpenAPI specification: https://reducto.ai/openapi.json

## Pricing, Security, Industries

- Pricing: per-product Standard / Growth / Enterprise plans. Standard includes 15,000 free credits; Growth adds custom volume pricing with security and compliance features; Enterprise adds custom pricing with VPC, on-premises, and air-gapped deployment. r-1 Parse starts at $10 per 1,000 pages, and Extract starts at $20 per 1,000 pages with parsing included — https://reducto.ai/pricing
- Security: SOC 2, HIPAA (BAAs on Growth+), zero data retention agreements (Growth+), deploy hosted/VPC/on-prem/air-gapped — https://docs.reducto.ai/security/policies
- Industries: finance, healthcare, legal, insurance, government, construction, logistics — https://reducto.ai/industries · case studies at https://reducto.ai/customers

## Comparisons

Honest tool-by-tool comparisons — accuracy, deployment, tooling, pricing, and when each option fits. Hub at https://reducto.ai/compare. Benchmark evidence behind these comparisons: https://reducto.ai/guides/document-ai-benchmark-ocr-parsing-extraction.

- [Reducto vs LlamaParse](https://reducto.ai/compare/reducto-vs-llamaparse): Compare two document AI platforms across extraction evidence, citations, agent tooling, deployment, ecosystem fit, and pricing.
- [Reducto vs Unstructured](https://reducto.ai/compare/reducto-vs-unstructured): A managed agentic document platform with measured accuracy vs an open-source document parsing and ETL library for LLM pipelines.
- [Reducto vs AWS Textract](https://reducto.ai/compare/reducto-vs-aws-textract): A complete agentic document platform that can run in your own VPC vs a cloud OCR primitive inside the AWS ecosystem.
- [Reducto vs Azure Document Intelligence](https://reducto.ai/compare/reducto-vs-azure-document-intelligence): A zero-shot agentic document platform with the full toolkit in one API vs a cloud OCR service with prebuilt and custom-trained models.
- [Reducto vs Google Document AI](https://reducto.ai/compare/reducto-vs-google-document-ai): A zero-shot agentic document platform that deploys anywhere vs cloud OCR processors you configure per document type.
- [Reducto vs Gemini](https://reducto.ai/compare/reducto-vs-gemini): An agentic document platform that orchestrates frontier models inside a production pipeline vs a general-purpose frontier LLM used raw for document work.
- [Reducto vs Extend](https://reducto.ai/compare/reducto-vs-extend): A complete agentic document platform with benchmark-leading extraction and flexible deployment vs a managed document workflow product.
- [Reducto vs Pulse](https://reducto.ai/compare/reducto-vs-pulse): A complete agentic document platform proven at enterprise scale vs a focused document parser with a financial-documents emphasis.
- [Reducto vs Datalab](https://reducto.ai/compare/reducto-vs-datalab): A complete agentic document platform proven at enterprise scale vs the research-driven vendor behind the open-source Marker and Surya models.
- [Reducto vs ABBYY](https://reducto.ai/compare/reducto-vs-abbyy): An AI-native agentic document platform with zero-shot accuracy vs decades-old enterprise OCR with template-based capture.

## Blog

Technical articles, case studies, and product announcements. This is an index — fetch each URL for the full article.

- [Introducing r-1 and our new generation of document parsing models](https://reducto.ai/blog/parse-r-1-model) (2026-09-01): Reducto's Agentic OCR already leads the industry on accuracy. With r-1, we're making the best even better.
- [Introducing simpler, more transparent pricing at Reducto](https://reducto.ai/blog/reducto-simple-transparent-document-processing-pricing) (2026-08-25): We’re simplifying Reducto’s pricing to make costs easier to understand and forecast—and to pass model efficiency gains more directly into better rates for customers.
- [The Document Is the Database: How Vector Legal Is Building an AI-Native Law Firm with Reducto](https://reducto.ai/blog/reducto-vector-legal-ai-customer-story) (2026-08-14): Vector Legal processes thousands of documents each month, using Reducto’s Parse and Extract to turn complex legal files into structured data for VectorOS.
- [Built to Scale: How Doe Automated Over 8 Million Agent Tasks with Reducto](https://reducto.ai/blog/reducto-doe-ai-agent-customer-story) (2026-07-21): Doe has completed over 8 million tasks for customers through its AI agent command center, using Reducto to handle complex document work at scale.
- [Deep Extract vs. Frontier Models vs. Humans: The Real Tradeoffs for Long Structured Extraction](https://reducto.ai/blog/reducto-deep-extract-mode-vs-frontier-models-vs-humans) (2026-07-20): Deep Extract trades a higher cost for near perfect accuracy on long, high stakes documents, compared with the manual review process most teams still rely on.
- [Reducto Deep Extract Leads Benchmark on Complex Document Extraction](https://reducto.ai/blog/reducto-leads-benchmark-complex-document-extraction) (2026-06-30): micro1 released an independent benchmark evaluating document extraction systems on difficult, high-field-count workloads. Reducto Deep Extract ranked first overall.
- [Reducto Raises Frontier Model Accuracy on GDP.pdf](https://reducto.ai/blog/reducto-raises-frontier-model-accuracy) (2026-06-16): Frontier models score under 30% on GDP.pdf, a benchmark of 100 real professional documents. We ran the same tasks with Reducto's structured parse added: macro accuracy jumped 9pp, reasoning tokens dropped 13%, and answers arrived faster despite 82% more input.
- [What is an Agentic Document Platform?](https://reducto.ai/blog/reducto-what-is-an-agentic-document-platform) (2026-06-11): Learn about what makes an agentic document platform, and how it differentiates from previous IDP and OCR solutions.
- [Parsing the 10-K: why financial filings defeat standard PDF pipelines](https://reducto.ai/blog/10k-document) (2026-06-08): Most financial RAG pipelines fail before the model ever runs. Here's where the parser loses the structure and what it takes to get it back.
- [Build your first document workflow with Reducto](https://reducto.ai/blog/build-document-feature-with-reducto) (2026-06-08): Building a document feature or integrating Reducto into your existing document workflow should be quick and easy. We'll show you how.
- [Deep Split: Utilizing Agent Harnesses for Accuracy at Scale](https://reducto.ai/blog/reducto-deep-split-agent) (2026-06-03): We're introducing a new version of split for longer documents and workflows with large numbers of categories.
- [Announcing Reducto’s Classify Endpoint: Route Documents Before Processing](https://reducto.ai/blog/reducto-classify-endpoint-api) (2026-05-21): Learn about Reducto's new Classification endpoint, which helps categorize documents in a fast and lightweight way before downstream document work.
- [Reducto acquires Opennote](https://reducto.ai/blog/reducto-acquires-opennote) (2026-05-07): We're announcing our acquisition of Opennote, the AI notebook that helps students understand, organize, and practice from their notes.
- [Introducing Smart Schema](https://reducto.ai/blog/reducto-smart-schema-extract-optimization) (2026-04-28): Accurate extraction starts with your schema. Today, we're introducing Smart Schema in our Studio experience to help teams autonomously create contextually aware schemas and improve them automatically.
- [How Harvey Turned OCR Quality Into Customer Confidence with Reducto](https://reducto.ai/blog/reducto-harvey-legal-ai-customer-story) (2026-04-07): Read how Harvey partners with Reducto to upgrade its document processing capabilities, going from evaluation to full production in roughly six weeks while improving accuracy across complex legal documents like handwritten notes, redlines, and image-based files.
- [Introducing Deep Extract](https://reducto.ai/blog/reducto-deep-extract-agent) (2026-04-06): We're releasing our most powerful update to structured extraction yet with Deep Extract.
- [How Vanta is Building AI-Native Compliance with Reducto](https://reducto.ai/blog/vanta-reducto-case-study) (2026-02-20): Learn how Vanta's AI team utilize Reducto to power their AI-native compliance workflows, including questionnaire automation and evidence evaluation.
- [Reducto Is Now Available on AWS Marketplace](https://reducto.ai/blog/aws-marketplace-reducto) (2026-02-06): Reducto is now available on AWS Marketplace, enabling enterprises to purchase the leading AI document intelligence platform using their committed AWS spend.
- [Scaling Beyond Annotation: How Reducto Powers Scale AI’s Agentic Expansion](https://reducto.ai/blog/scale-ai-reducto-case-study) (2025-12-15): See how Scale's Public Sector and Enterprise teams use Reducto to power their new agentic workflows with high precision, security, and scale.
- [How Reducto is building SOTA chart extractions](https://reducto.ai/blog/reducto-chart-extraction) (2025-12-03): Our approach to developing a new chart extraction method, returning near pixel-perfect data accuracy for complex line graphs, bar graphs, and more.
- [August’s Competitive Edge: Legal AI Built on Reducto](https://reducto.ai/blog/august-law-case-study) (2025-11-24): August delivers attorney-ready legal workflows by pairing its agentic platform with Reducto’s high-fidelity document understanding, enabling accurate, traceable work products even from the hardest-to-parse documents.
- [How LEA Uses Reducto to Deliver Document Intelligence to Enterprise Wealth Management Firms](https://reducto.ai/blog/lea-reducto-case-study) (2025-11-11): LEA uses Reducto’s secure document AI to automatically organize, extract, and pipe data from thousands of complex financial documents—helping $10B+ RIAs scale operations, cut manual data entry in half, and grow without adding headcount.
- [Reducto Announces $108M in Funding to Define the Future of AI Document Intelligence](https://reducto.ai/blog/reducto-series-b-funding) (2025-10-14): We're announcing $108M in total funding following a new $75M Series B led by a16z. See what we've learned and our plans for the future.
- [How we did a database migration without logical replication - with zero downtime](https://reducto.ai/blog/reducto-database-migration-zero-downtime) (2025-09-18): Database migrations are tough - here's how we did it using Pgdog and database mirroring.
- [How Elysian uses Reducto to Review Insurance Claims 16x Faster](https://reducto.ai/blog/reducto-elysian-case-study) (2025-09-04): Read about how Elysian utilizes Reducto to process insurance claims of all shapes and sizes, resulting in a 16x faster audit process compared to traditional methods.
- [Enterprise RAG at scale: search techniques for million-document databases](https://reducto.ai/blog/reducto-ingestion-rag-enterprise-scale) (2025-08-26): How to build reliable retrieval systems on top of Reducto’s parsing and chunking pipelines—so your enterprise AI can handle massive unstructured document ingestion with accuracy.
- [Streamlining Document Processing with Reducto and Databricks](https://reducto.ai/blog/streamline-document-processing-reducto-databricks) (2025-06-26): How to unlock your unstructured data with Reducto, with Databricks.
- [How Gumloop Enables Anyone to Make AI Workflows with Reducto](https://reducto.ai/blog/gumloop-case-study) (2025-06-24): Read how Reducto powers Gumloop's AI automation of enterprise workflows, allowing non-technical teams at Instacart and Webflow to rapidly scale AI adoption.
- [How Benchmark uses Reducto to Build the First-Party Data Engine for $1 Trillion in Assets](https://reducto.ai/blog/benchmark-case-study) (2025-06-18): Benchmark is an AI-native investment platform used by firms managing ~$1T in assets under management, including some of the world’s top financial institutions. See how they utilize Reducto in some of their most important features, such as Document Builder.
- [How to use Reducto parsing with Elasticsearch for Semantic Search](https://reducto.ai/blog/how-to-reducto-parsing-elasticsearch-semantic-search) (2025-06-05): Demonstrating how Reducto's document processing API can be integrated with Elasticsearch for semantic search.
- [How Anterior Accelerates Prior Authorization and Clinical Decision-Making with 99%+ Accuracy with Reducto](https://reducto.ai/blog/anterior-case-study) (2025-06-05): Learn how Anterior accelerates prior authorizations with 99%+ precision using Reducto’s document ingestion engine—turning unstructured medical records into real-time decisions.
- [Automating Enterprise Workflows at Scale with Stack AI and Reducto](https://reducto.ai/blog/reducto-stack-ai-case-study) (2025-05-29): Learn how Stack AI customers have processed over 5M+ documents using Reducto in their enterprise automation workflows.
- [How to Use AI to Extract Data from Claim Submissions at Scale](https://reducto.ai/blog/extract-api-health-insurance-claims) (2025-05-09): Health insurance is a unique space that can benefit greatly from LLMs and proper document ingestion at scale - use AI to help automate extracting important data with accuracy.
- [Reducto raises $24.5M Series A to help enterprises unlock unstructured data](https://reducto.ai/blog/reducto-series-a-funding) (2025-04-25): We raised a $24.5M Series A led by Benchmark to help enterprises turn unstructured data into accurate, LLM-ready inputs—at scale. Read more on what we've built and where we're headed next.
- [Extraction Trouble? Here Are 5 Pitfalls to Avoid when Configuring Your JSON Schema](https://reducto.ai/blog/document-ai-extraction-schema-tips) (2025-04-16): If your extraction outputs aren't as expected, troubleshoot first by checking if you're making any of these 5 mistakes. A good quality schema will lead to a good quality output!
- [Build vs. Buy for Document Processing: How to Choose the Right Approach for Your AI Infra](https://reducto.ai/blog/build-vs-buy-ai-document-ingestion) (2025-04-15): If you're deciding whether to build your own document processing pipeline in house or buy with a vendor, this guide highlights some of the tradeoffs and why Reducto might be a good fit.
- [Introducing RolmOCR: A Faster, Lighter Open Source Document Model Built on olmOCR](https://reducto.ai/blog/introducing-rolmocr-open-source-ocr-model) (2025-04-03): We're excited to release RolmOCR, a drop-in alternative to olmOCR with a newer base model and other performance improvements.
- [Mistral OCR vs. Gemini Flash 2.0: Comparing VLM OCR Accuracy](https://reducto.ai/blog/lvm-ocr-accuracy-mistral-gemini) (2025-03-06): We benchmarked Mistral AI vs. Gemini Flash 2.0 to assess the accuracy of their OCR models after release. The results are intriguing as they don't appear to align with what was posted on Mistral's blog.
- [How We Started Working With Fortune 10 Enterprises](https://reducto.ai/blog/reducto-enterprise-sales) (2025-01-13): A behind the scenes look of how Reducto started powering ingestion for one of the world's largest companies.
- [State-of-the-art table parsing](https://reducto.ai/blog/sota-table-parsing) (2024-11-04): See how leading PDF parsers handle complex tables in RD-TableBench, an open benchmark of 1,000 hand-labeled examples covering merged cells, dense text, and irregular structures.
- [Announcing RD-TableBench: An Open-Source Table Benchmark](https://reducto.ai/blog/rd-tablebench) (2024-11-04): We released a new comprehensive open benchmark for table parsing.
- [Reducto raises $8.4 million to help LLMs read documents the way humans do](https://reducto.ai/blog/seed-round) (2024-10-02): Reducto now powers ingestion pipelines for some of the world's leading AI companies, and we're excited to share we've raised $8.4M in funding led by First Round to further our mission of making human data LLM-ready.
- [Introducing Reducto's Document API](https://reducto.ai/blog/document-api) (2024-02-27): We've spent the last few months building a powerful document ingestion for LLM workflows. We're excited to share more about what we've built.
- [The Real Cost of Manual Document Processing](https://reducto.ai/blog/the-real-cost-of-manual-document-processing) (2024-01-19): Explore the hidden costs of manual document processing, from time inefficiencies to error rates. Learn how Reducto's AI-driven solution can streamline these processes, saving businesses significant time and resources.

## Cookbooks

Templates and recipes for building with Reducto. This is an index — fetch each URL for the full recipe.

- [Turn loss runs and insurance submissions into underwriting-ready data](https://reducto.ai/cookbooks/reducto-loss-run-report-to-underwriting-data) (2026-08-06): Loss run reports are how carriers report claims history, and every one is laid out differently across dozens of pages of dense tables. This cookbook covers how you can create an end-to-end pipeline in Reducto that turns the whole report in one call into clean, structured tables you can load straight into code.
- [Split a law review article into sections and extract any part](https://reducto.ai/cookbooks/reducto-split-law-review-article) (2026-07-01): A law review article is long and highly structured: an abstract, a table of contents, and dozens of numbered sections, often across a hundred or more pages. Pulling one piece, say the abstract, first means finding where it lives before you can read it. With Reducto you parse the whole article once, split it into its constituent parts, and then run a targeted extract against only the pages that hold what you want. Three endpoints, one pipeline: Parse turns the PDF into clean structured text, Split maps the article into its sections, and Extract pulls the exact field you asked for with citations back to the source.
- [Parse any healthcare document into clean, structured text](https://reducto.ai/cookbooks/reducto-parse-healthcare-documents) (2026-07-01): Healthcare documents are some of the messiest inputs in any pipeline. A single patient's file might include a handwritten intake form, a scanned chart with checkboxes and body diagrams, a casualty card filled out under pressure, and a lab report full of dense tables, each laid out differently and often photographed or faxed. Retyping that by hand is slow, error prone, and does not scale. Reducto parses the entire document in one call and returns it as clean, structured text, handwriting transcribed and tables preserved, so your code or your model works with the data instead of the scan.
- [Pull every field from a handwritten property loss form](https://reducto.ai/cookbooks/reducto-extract-handwritten-property-loss-forms) (2026-06-29): First notice of loss forms come in handwritten, dozens of fields packed into a tight grid with corrections scribbled over the originals. Reducto reads the handwriting, skips the crossed-out edits, and returns every field as structured JSON with a citation on each value.
- [Turn a brokerage statement into structured account data](https://reducto.ai/cookbooks/reducto-extract-brokerage-statement-accounts) (2026-06-29): Brokerage statements bury account numbers, types, and balances in dense, multi-account tables that look different at every firm. Reducto parses those tables cleanly, then returns every account as structured JSON with a citation on each value.
- [Reconcile every transaction on a bank statement](https://reducto.ai/cookbooks/reducto-extract-bank-statement-reconciliation) (2026-06-19): Bank and brokerage statements arrive as PDFs and scans that spreadsheets can't read. Reducto's Extract turns one into a clean, typed list of every transaction, ready to load into a ledger, dashboard, or audit trail.
- [Extract structured data from patient intake forms](https://reducto.ai/cookbooks/reducto-extract-patient-intake-forms) (2026-06-19): Patient intake forms arrive as scans, faxes, and phone photos, every one laid out differently. Reducto's Extract reads them the way a nurse would, pulling demographics, insurance, and medication history into clean JSON with a source citation on every field.
- [Reducto + Databricks: a friendly parsing comparison](https://reducto.ai/cookbooks/reducto-databricks-comparison) (2026-06-15): Nine real cases where Reducto's parsing and Databricks ai_parse_document diverge, from spreadsheets and charts to signatures, tracked changes, and handwriting, and why those last-mile details decide whether downstream AI lands the right answer.
- [Pull every redline from a contract](https://reducto.ai/cookbooks/reducto-parse-redlined-legal-contracts) (2026-06-15): Redlined contracts are exactly the long-tail complexity that breaks template-based pipelines. Reducto reads every strikethrough, underline, and annotation as structured tags, so your team surfaces all 500+ revisions in code instead of page by page.

## Guides

Buyer guides, comparisons, benchmarks, and technical explainers for building with Reducto. Each guide is the buyer-facing companion to the API docs topic it covers, including parsing, extraction, classification, and workflows. This is an index — fetch each URL for the full guide. The docs index is at https://docs.reducto.ai/llms.txt.

- [What Makes an OCR API Production-Ready?](https://reducto.ai/guides/best-ocr-api-production-document-workflows) (2026-08-27): A production-ready OCR API must do more than recognize characters. It must reliably return complete, structurally correct, verifiable output for the documents a system actually receives.
- [Reducto vs. Rossum: Which Document Platform Should You Choose?](https://reducto.ai/guides/reducto-vs-rossum) (2026-08-18): Compare Reducto and Rossum across document scope, extraction, source evidence, validation workflows, deployment, and ideal use cases.
- [Best Accounts Payable OCR Software](https://reducto.ai/guides/best-accounts-payable-ocr-software) (2026-08-18): Compare accounts payable OCR for invoice extraction, line items, source evidence, validation workflows, ERP integration, and cloud deployment.
- [Best Document Parsers for RAG](https://reducto.ai/guides/best-document-parsers-rag) (2026-08-18): Compare document parsers for production RAG across reading order, tables, layout-aware chunks, citations, cloud fit, and self-hosting.
- [Best AI Document Analysis Software](https://reducto.ai/guides/best-ai-document-analysis-software) (2026-08-18): Compare AI document analysis software for parsing, search, structured extraction, cloud-native workflows, and enterprise document review.
- [Best Receipt OCR Software and APIs](https://reducto.ai/guides/best-receipt-ocr-software) (2026-08-18): Compare receipt OCR options for AI products, cloud-native applications, expense extraction, line items, and source-grounded review.
- [Best Enterprise Data Extraction Software](https://reducto.ai/guides/best-enterprise-data-extraction-software) (2026-08-18): Compare enterprise data extraction software for long documents, complex tables, structured schemas, cloud ecosystems, and human validation.
- [Best Document Processing Tools for AI Agents](https://reducto.ai/guides/best-document-processing-tools-ai-agents) (2026-08-18): Compare document processing tools for AI agents, including parsing, extraction, source citations, agent interfaces, and enterprise deployment.
- [Best Document AI Platforms and APIs](https://reducto.ai/guides/best-document-ai-platforms-apis) (2026-08-17): Compare leading Document AI platforms and APIs for complex parsing, structured extraction, cloud-native workflows, RPA, and transactional document operations.
- [What Is Agentic Document Processing?](https://reducto.ai/guides/agentic-document-processing) (2026-08-17): Learn how agentic document processing uses iterative parsing, extraction, validation, and workflow tools to handle difficult enterprise documents.
- [Best Document Automation Software for Enterprises](https://reducto.ai/guides/best-document-automation-software-enterprises) (2026-08-17): Compare enterprise document automation software for complex extraction, cloud-native processing, transactional workflows, and governed deployment.
- [Best OCR Models in 2026: Accuracy, Speed and Cost](https://reducto.ai/guides/best-ocr-models-accuracy-speed-cost) (2026-08-14): Compare open OCR models and managed APIs by document accuracy, speed, infrastructure cost, language coverage, license, deployment and limitations.
- [Best OCR for Handwriting Recognition in 2026](https://reducto.ai/guides/best-ocr-handwriting-recognition) (2026-08-14): Compare handwriting OCR for cursive, forms, historical documents and multilingual text, including custom training, review workflows, deployment and failure modes.
- [Best Table Extraction Software for Complex PDFs in 2026](https://reducto.ai/guides/best-table-extraction-software-complex-pdfs) (2026-08-13): Compare table extraction tools for merged, nested, multi-page, scanned and irregular PDF tables, with benchmark evidence, deployment and failure modes.
- [PDF-to-Excel Tools: Enterprise Accuracy Guide for Complex Tables](https://reducto.ai/guides/pdf-to-excel-tools-enterprise-benchmark) (2026-08-13): Compare PDF-to-Excel tools for financial and operational tables using published table-parsing evidence, security, batch/API support and cleanup requirements.
- [Best PDF Data Extraction APIs and SDKs in 2026](https://reducto.ai/guides/best-pdf-data-extraction-apis-sdks) (2026-08-13): Compare developer-focused PDF extraction APIs by authentication, SDKs, async jobs, webhooks, limits, outputs, citations, security, pricing and implementation effort.
- [Which OCR Software Is Most Accurate in 2026?](https://reducto.ai/guides/most-accurate-ocr-software) (2026-08-13): OCR accuracy depends on the task. Learn how to compare character recognition, layout parsing, table extraction and structured fields using the right metrics.
- [Document AI Benchmark: OCR, Parsing and Extraction Leaderboard](https://reducto.ai/guides/document-ai-benchmark-ocr-parsing-extraction) (2026-08-13): Compare published Document AI results for complex tables and long structured extraction without collapsing incompatible tasks or hiding completion rates.
- [Best PDF OCR Software for AI Workflows in 2026](https://reducto.ai/guides/best-pdf-ocr-software-ai-workflows) (2026-08-13): Compare PDF OCR and parsing tools for RAG and agents across scans, hybrid PDFs, structure, grounding, Markdown/JSON output, deployment, batching, security, and cost.
- [Best Invoice OCR Software for Accounts Payable in 2026](https://reducto.ai/guides/best-invoice-ocr-software) (2026-08-13): Compare invoice OCR software for accounts payable across header and line-item extraction, validation, review workflows, ERP integration, controls, and invoice volume.
- [Best PDF Data Extraction Software in 2026](https://reducto.ai/guides/best-pdf-data-extraction-software) (2026-08-13): Compare PDF extraction software for native, scanned, and hybrid files across OCR, tables, forms, output formats, validation, deployment, and best-fit use cases.
- [Best AI Data Extraction Tools for Unstructured Documents in 2026](https://reducto.ai/guides/best-ai-data-extraction-tools-unstructured-documents) (2026-08-13): Compare leading AI data extraction tools for complex PDFs, scans, forms and document packets using accuracy evidence, source traceability, review workflows, integrations and pricing models.
- [Best Document Classification Software in 2026: APIs, Workflows, and Trade-Offs](https://reducto.ai/guides/best-document-classification-software-2026) (2026-07-30): Compare six document classification platforms across setup, confidence signals, workflow routing, human review, cloud fit, and production operations.
- [Best OCR APIs for Complex Documents in 2026](https://reducto.ai/guides/best-ocr-apis-complex-documents-2026) (2026-07-28): Compare six OCR APIs for complex documents across layout, tables, grounding, completion rates, cloud fit, and production workflows.
- [Document Workflow Automation: Architecture, APIs, and Production Patterns](https://reducto.ai/guides/document-workflow-automation) (2026-07-28): Learn how to build reliable document workflow automation using classification, parsing, splitting, extraction, editing, validation, and asynchronous delivery.
- [Enterprise IDP Evaluation Guide: How to Compare Document Processing Software in 2026](https://reducto.ai/guides/idp-enterprise-evaluation) (2026-02-06): Compare intelligent document processing software across accuracy, tables, citations, deployment, security, throughput, and cost with this enterprise IDP scorecard.
- [Best PDF-to-Text Tools for AI and Enterprise Workflows](https://reducto.ai/guides/pdf-to-text) (2025-06-01): Compare PDF-to-text tools for AI ingestion, complex layouts, searchable PDFs, cloud applications, and self-hosted document conversion.
- [Intelligent Document Processing in 2026: Technology, Use-Cases, and Implementation](https://reducto.ai/guides/intelligent-document-processing) (2025-06-01): Learn how intelligent document processing combines classification, OCR, parsing, extraction, validation, and routing to automate document-heavy enterprise workflows.
- [Document Parsing: Turning Unstructured Files into Reliable, Structured Data](https://reducto.ai/guides/document-parsing-unstructured-files) (2025-06-01): Learn how document parsing converts PDFs, scans, spreadsheets, and images into structured text and JSON for search, analytics, automation, and LLM workflows.
- [Data Ingestion: Moving Unstructured Content into Your Analytics Stack](https://reducto.ai/guides/data-ingestion-unstructured-content) (2025-06-01): Build a document data ingestion pipeline that turns PDFs, scans, and spreadsheets into validated, structured outputs for analytics, automation, and RAG.
- [PDF Parser — What It Is, And Why You Need One](https://reducto.ai/guides/pdf-parser) (2025-06-01): Learn what a PDF parser does, why OCR alone struggles with complex layouts, and how to evaluate parsing software for structured data, RAG, and document automation.
- [Evaluating AWS Textract for PDF Parsing - Table Extraction](https://reducto.ai/guides/evaluating-textract-for-pdf-parsing) (2024-07-01): We evaluated AWS Textract's ability to parse documents.
- [Evaluating Azure Document Intelligence for complex PDFs - Table Extraction](https://reducto.ai/guides/evaluating-azure-document-intelligence-for-pdf-parsing) (2024-07-01): We evaluated Azure Document Intelligence's ability to parse complex PDF documents.
- [Evaluating LlamaParse Premium for PDF Parsing - Table Extraction](https://reducto.ai/guides/evaluating-llamaparse-for-pdf-parsing) (2024-07-01): We evaluated LlamaParse's ability to parse complex PDF documents.
- [Evaluating Unstructured.io for PDF Parsing - Table Extraction](https://reducto.ai/guides/evaluating-unstructured-for-pdf-parsing) (2024-07-01): See how Unstructured.io's Hi-Res mode scored 60.2% average table precision in RD-TableBench versus Reducto at 90.2%, including the errors behind the gap.
- [Evaluating Google Document AI for PDF Parsing - Table Extraction](https://reducto.ai/guides/evaluating-google-document-ai-for-pdf-parsing) (2024-07-01): See how Google Document AI scored 64.6% average table precision in RD-TableBench versus Reducto at 90.2%, including the structural errors behind the gap.

## More

- Markdown content pages: https://reducto.ai/developers.md · https://reducto.ai/pricing.md · https://reducto.ai/about.md · https://reducto.ai/contact.md · https://reducto.ai/auth.md
- Engineering blog, indexed for LLMs: https://reducto.ai/engineering/llms.txt
- Sales / demos: https://reducto.ai/contact · Support: support@reducto.ai