Extend vs. Reducto
Reducto was built for teams looking for a standard OCR API. Extend is designed for teams that want high performance processing, a suite of APIs, and comprehensive tooling for deploying production-grade document pipelines. For organizations that want best-in-class accuracy and reliability for mission-critical use cases, Extend offers a more comprehensive solution out of the box.
Updated: 11/23/2025
Try out Extend for free| Features Comparison | Extend |  Reducto |
|---|---|---|
| Parse | ||
| Agentic OCR | Yes | Yes |
| Embedding optimization | Yes | Yes |
| Layout aware OCR | Yes | Yes |
| Checkboxes / Signatures | Yes | Yes |
| Fast parsing | Optionally enable low-latency parsing for real-time use cases. | One single mode for parsing regardless of use case requirements. |
| Cost-optimized parsing | Optionally enable low-cost parsing for high volume use cases. | One single mode for parsing regardless of use case requirements. |
| Extract | ||
| Agentic array extraction | Extract 1000s of items in an array with high accuracy. | In beta. |
| Granular citations | Yes | Yes |
| Dedicated citation model | Yes | Yes |
| Chain-of-thought traces | Optionally enable COT traces to understand model reasoning. | No |
| Schema versioning | Native versioning system for safely making and deploying changes in production. | Risky changes must be made directly in production. |
| Fast extraction | Optionally enable a low-latency, low-cost processing for latency sensitive use cases. | One single mode for extraction regardless of use case requirements. |
| Intelligent merging strategies | Resolves duplicates intelligently across document chunks with a multi-step LLM process. | Duplicates are naively merged. |
| Split | ||
| Fast splitter | Optionally enable a fast splitter for latency sensitive use cases. | One single mode for splitting regardless of use case requirements. |
| Cost-optimized splitter | Optionally enable a cost-effective splitter for high volume use cases. | One single mode for splitting regardless of use case requirements. |
| Classify | ||
| Document classification API | Dedicated classification API optimized for cost and speed. | Required to do classification within extraction, at the expense of additional cost and latency. |
| Memory System | Vision-based retrieval system for few shot document classification, enabling 100% accuracy. | No |
| Edit | ||
| File editing API | Yes | Yes |
| Overflow logic for long answers | Yes | Yes |
| Accurate form field detection | Yes | Yes |
| Edit forms in UI-based environment | Yes | Yes |
| Speed | Fast. Long documents process in seconds. | Medium. Long documents take minutes to fill. |
| Field types | Comprehensive support for text fields, checkboxes, radio groups, signatures, and tables. | Only supports simple text fields and checkboxes. |
| Evals | ||
| Evaluation experience | Comprehensive evaluation framework built-in to improve performance. | No |
| Reports | Generate accuracy reports to measure performance metrics. | No |
| Custom evaluation scoring | LLM-as-a-judge, vector similarity, and fuzzy matching scorers. | No |
| Agents | ||
| Automated schema optimization | Composer, an AI agent that optimizes prompts and schemas for production-ready accuracy. | Requires trial-and-error tuning of prompts by hand. |
| Schema Drift | Composer automatically updates your ground truth data when schemas are updated. | Requires manually updating ground truth datasets. |
| Agentic Confidence Scoring | Review Agent flags low confidence results for escalation. | No |
| Enterprise-Readiness | ||
| Compliance | SOC2, HIPAA, GDPR | SOC2, HIPAA |
| Up time | 99%+ uptime | 99%+ uptime |
| Deployment Model | Cloud, self-host | Cloud, self-host |
| Audit logs | Comprehensive | Minimal |
| Version history | Yes | No |
| Human-in-the-Loop UI | Built-in review and corrections UI. | No |
| Team | ||
| Market focus | Fortune 100 to mid-market and startups in healthcare, financial services, supply chain, insurance. Customers include Zillow, Chime, Square, Amgen, Brex, Mercury, First American, CH Robinson. | Small startups to enterprises including Harvey, Vanta, and Zip. |
| Pricing | ||
| Free credits available | Free trial | Free trial |
| Pay-as-you-go pricing | Pay as you go for top-ups | On standard plan |
| Slack support | Yes | Yes |
| Custom volume discounts | Scale and above | Growth and above |
Leading AI teams that perform bakeoffs between Extend and other solutions repeatedly choose to build with Extend.
Case Study
How Brex Reached 99% Accuracy Across Millions of Financial Documents
Brex uses Extend to power 99%-accurate document workflows across 30,000+ customers.
Kushal Byatnal
7 min read
Case Study
HomeLight Hits 99% Accuracy and Eliminates Manual Review with Extend
HomeLight used Extend to automate contract review with 98%+ accuracy and zero human input.
Kushal Byatnal
4 min read
Case Study
Vendr Unlocks Data from Millions of Documents to Launch New Products
Vendr used Extend to turn millions of SaaS contracts into actionable pricing intelligence.
Kushal Byatnal
4 min read
Extend's Approach
Enterprise-grade performance requires the flexibility of a customized build that adapts to your toughest edge cases.
The best models
Extend combines agentic OCR and custom-trained VLMs and LLMs to handle your most difficult edge-cases, e.g., checkboxes, strikethroughs, redlines, multi-page tables.
The best context
Extend's pre-processing pipeline, semantic chunking, vision-based memory system, and context engineering tooling ensures that clean, contextualized data flows into your pipeline.
The best tooling
Agents, like our Composer background agent for schema optimization and Review agent, along with an intuitive evaluation suite allow for maximum control and flexibility to ship with confidence on your hardest use cases.
