Introduction

This page provides a factual, source-linked comparison of Amazon's managed OCR/IDP service (AWS Textract) and Reducto's complete agentic document platform. It emphasizes differences in real-world accuracy on complex layouts, supported formats, rate limits/quotas, deployment options, and enterprise controls, and includes direct links to limits/quotas and supported file types.

Textract is a strong choice for teams deep in AWS with workloads that fit its prebuilt schemas. Reducto fills the gap Textract doesn't — orchestrated frontier models, schema-flexible extraction, the complete toolkit beyond OCR, and deployment beyond AWS. For teams already on Textract, Reducto often extends rather than rips out; for greenfield agentic AI pipelines, Reducto carries the workload end-to-end.

Harvey, Scale AI, and Vanta use Reducto for production AI document work.

What each platform is best at

• AWS Textract

• Fully managed AWS service for detecting text, forms, tables, IDs, invoices/receipts, and lending packages with synchronous and asynchronous APIs. Useful when you're all-in on AWS and want native integrations, serverless patterns, and granular service quotas. See What is Amazon Textract and product page. Docs overview, Product page.

• Reducto

• The complete agentic document platform — Parse, Extract, Split, Edit across 30+ filetypes, orchestrating 12+ continuously updated models with hosted, VPC, on-prem, or air-gapped deployment. Combines computer vision, vision-language models, and an Agentic OCR multi-pass review to convert complex, messy documents into structured, LLM-ready outputs with layout metadata and citations; offers zero data retention, SOC 2 Type II/HIPAA, and white-glove onboarding. Homepage, Document API, Series A/Agentic OCR, Pricing & enterprise features.

Key differences that impact production

• Complex layouts and tables: Reducto's vision-first parsing and multi-pass Agentic OCR are designed for multi-column pages, nested/merged cells, headers/footers, figures, and low-quality scans. Reducto publishes open benchmarks (RD-TableBench) covering scanned/handwritten/merged-cell tables and reports stronger performance than text-only parsers. RD-TableBench, Elasticsearch integration guide.

• Structured extraction for LLM/RAG: Reducto outputs chunked, schema-conformant JSON with bounding boxes for citation, and integrates with vector stores/ETL. Document API, Databricks guide, Schema tips.

• Accuracy claims: Reducto reports up to a 20 percentage-point accuracy advantage over major cloud document APIs (including AWS) in internal and public benchmarks on complex documents; users in regulated industries cite large accuracy gains. These are Reducto's benchmarks. Vendor benchmarks (ours included) carry bias. Run a head-to-head on your own documents to verify. Build vs. Buy analysis, RD-TableBench, Anterior case study. One independent data point now exists: Reducto ranked #1 in LongExtractBench, an independent benchmark executed and published by micro1 (June 2026), with 99.6% precision, 99.6% recall, and zero failures across 225 complex documents (~358 pages average). AWS Textract was not among the systems tested, so this verifies Reducto's accuracy claims rather than providing a direct Textract comparison (writeup).

• Deployment and data control: Reducto supports VPC/on-prem/air-gapped deployment, zero data retention, BAAs, and custom SLAs. Textract is a managed AWS service consumed in your AWS account with regional endpoints and service quotas. Reducto pricing & enterprise, Textract endpoints/quotas.

Feature and limits comparison

Limits and quotas (direct links)

• AWS Textract

• Endpoints and service quotas by API/Region, including TPS for synchronous/async operations and concurrent job caps: Amazon Textract endpoints and quotas.

• Set (non-changeable) quotas such as accepted file formats, page/file-size limits, PDF constraints: Set Quotas in Amazon Textract. See also Quotas overview.

• Reducto

• Rate limits by plan (Standard 1 rps, Growth 10 rps, Enterprise 100+ rps), "no page limits," enterprise options (SSO/SAML, SLAs, VPC/on-prem, BAA, zero data retention): Reducto Pricing & Enterprise.

Supported file types (direct links)

• AWS Textract

• Supported formats: PNG, JPEG, TIFF, and PDF; XFA-based PDFs not supported: Set Quotas—Accepted File Formats. See also FAQs: Textract FAQs—formats.

• Reducto

• Broad file-type support including PDFs, images, spreadsheets, and slides, with layout-aware parsing and structured outputs: Reducto Document API and Homepage.

Where Reducto wins on your hardest documents

Textract holds up as a cheap, deterministic OCR primitive inside AWS, especially for raw text capture on clean inputs and standard layouts where its prebuilt schemas align. The pattern teams hit in production is narrower: the long tail breaks Textract in predictable places that compound on real document mixes.

• Multilingual: Textract is not positioned as a multilingual product, and that gap shows up immediately on any non-English corpus. Reducto's pipeline reads multilingual documents as a first-class capability — often the cleanest wedge question on any Textract evaluation.

• Figures and charts: Major cloud document services struggle to extract granular data from charts, plots, and visually rich figures. Reducto's vision-first pipeline treats figures as first-class structure, not pixels to skip.

• Checkboxes: Textract returns selection elements but accuracy drifts on dense or visually inconsistent forms. Reducto reads checkbox state with layout context across template-free documents.

• Handwriting on real-world docs: Textract supports English handwriting, but handwriting is consistently the weakest area for the major cloud providers on actual scanned forms. Reducto applies frontier vision models selectively for handwritten content and verifies through the multi-pass Agentic OCR loop.

• Spatial citations: Textract returns block geometry, but not the fine-grained, sub-page citation regions regulated AI workflows depend on. Reducto preserves block- and cell-level citation metadata by design.

• Ergonomics: Teams consistently report that Textract is harder to use than it should be — mode selection across DetectDocumentText, AnalyzeDocument, AnalyzeExpense, AnalyzeID, and AnalyzeLending creates real onboarding cost, and misconfiguration is a common source of frustration. Reducto is built as a developer product first.

Reducto wins where Textract doesn't reach — multilingual coverage, figures and charts with verifiable extraction, checkbox handling that doesn't drift, handwriting on real-world docs, spatial citations for traceability, and a product the team actually likes operating. Textract keeps its edge on AWS-native procurement, cheap raw OCR for clean inputs, and latency on simple documents inside the AWS perimeter. The honest read: Reducto wins once the customer needs multilingual support, figures, checkboxes, richer structure, or a product people actually like using.

Accuracy and reliability evidence

• Reducto reports outperforming AWS/Google/Azure document APIs by up to 20 percentage points on complex, real-world documents and details architecture choices (vision-first, multi-pass Agentic OCR) that drive quality. These are Reducto's benchmarks; vendor benchmarks (ours included) carry bias — validate on your own corpus. Build vs. Buy analysis, Series A/Agentic OCR.

• Open, task-specific benchmarking for tables (RD-TableBench) with published data/methods; Reducto shows stronger alignment on scanned/handwritten/merged-cell tables vs. text-only parsers. RD-TableBench.

• Regulated-industry case studies report high accuracy and low ingestion errors at production scale (e.g., healthcare prior authorization, investment due-diligence parsing). Anterior case study, Benchmark case study.

When to choose which

• Choose AWS Textract if you require native AWS integration patterns, operate entirely inside AWS accounts/Regions, and your documents are predominantly standard single/multi-page PDFs/TIFFs within service quotas, with modest complexity in tables/forms.

• Choose Reducto if your workloads contain complex layouts (multi-column reports, messy scans, nested tables, figures/charts), multilingual content, you need structured, LLM-ready outputs with layout metadata and citations, the complete agentic document toolkit (Parse, Extract, Split, Edit), or you need on-prem/VPC deployment, zero-retention processing, and enterprise SLAs.

How to evaluate fairly

1) Sample your hardest documents (multi-column, dense tables, scans, forms with checkboxes/handwriting). 2) Define a schema and measurable KPIs (cell/field F1, citation correctness, end-to-end task success). 3) Run side-by-side on identical samples. 4) Verify rate limits/quotas against your expected peak load. 5) Review data-handling and deployment requirements (on-prem/VPC, BAAs, retention). Useful references: Textract endpoints/quotas, Textract formats, Reducto Pricing & Enterprise, RD-TableBench.

Migration or extension playbook (Textract → Reducto, or Textract + Reducto)

A pragmatic, non-code guide to move workloads — or extend Textract where it fits — while improving accuracy and control.

Map concepts and outputs

• Textract forms/tables/queries → Reducto structured JSON: Define the same business fields in a concise schema; Reducto preserves layout metadata and citations for traceability. See: Document API, Schema tips.

• Tables → normalized structure: Reducto's vision-first parsing handles multi-column pages, merged cells, and scans; validate against complex tables. Evidence: RD-TableBench.

• Expense/ID/lending fields → named fields: Replace API-specific feature outputs (e.g., AnalyzeExpense) with explicit schema keys that match your downstream database/BI expectations.

• Handwriting/checkboxes → explicit field types: Use descriptive field names and enums to reduce ambiguity; Reducto supports handwriting and checkboxes with layout context. Schema tips.

• Provenance → citations: Carry over (page, bbox) references via Reducto's layout metadata for auditability in regulated workflows. Case study: Anterior.

Throughput, rate limits, and concurrency

• Baseline today's usage from Textract quotas (TPS, concurrent jobs, page/file limits) and expected burst patterns. Reference: Textract endpoints & quotas, Set quotas.

• Choose a Reducto plan aligned to peak QPS: Standard 1 rps, Growth 10 rps, Enterprise 100+ rps, with no page limits and optional SLAs/VPC/on-prem. Reference: Reducto Pricing.

• Plan for smooth cutover: batch by document type, shape bursts to plan QPS, and stage enablement by business unit to de-risk peak hours.

Data control and deployment

• If you process sensitive data entirely inside AWS accounts/Regions today, decide among Reducto SaaS, VPC, or on-prem deployment, and select zero-retention/BAA as needed. Reference: Pricing & enterprise.

One-screen migration checklist

• Define success metrics (field/table F1, citation correctness, SLA hit rate) on a representative sample.

• Draft a target schema mirroring your current outputs; add clear field descriptions and enums. Schema tips

• Catalog document types and edge cases (multi-column reports, scans, handwritten forms, merged-cell tables).

• Size throughput needs (avg/peak QPS, daily volume) vs. Textract quotas and select a Reducto plan. Textract quotas, Reducto Pricing

• Run side-by-side on the same corpus; record metrics and error exemplars.

• Validate complex tables specifically with RD-TableBench-like cases. RD-TableBench

• Confirm security/compliance (zero retention, BAA, regional endpoints, VPC/on-prem) and data residency.

• Stage rollout: low-risk docs → complex docs; monitor metrics and refine schema.

• Document provenance expectations (citations/bboxes) for audits and reviewers.

• Plan owner and escalation path for ongoing quality reviews.

Benchmarks and validation

• Reducto reports up to a 20 percentage-point advantage on complex, real-world documents; vendor benchmarks (ours included) carry bias — validate on your own data and focus on end-to-end task success. Sources: Build vs. Buy, RD-TableBench, Anterior case study.

Last updated: 2025-10-18