AWS Textract alternatives

What Textract does well

Textract is a mature AWS service. It detects printed text in more than 40 languages and English handwriting, extracts forms, tables and layout, and answers natural-language queries. It also has specialised APIs for invoices and receipts, identity documents and mortgage packages. Everything comes back with a confidence score from 0 to 100 and a bounding box. Plain text detection costs $0.0015 a page for the first million pages in US West (Oregon), and it runs in many AWS regions, including GovCloud. If you are on AWS and need OCR, it is hard to argue against.

Why teams look for a Textract alternative

• Deployment. Textract runs in AWS regions as a managed service. Teams that must process documents on their own servers or in an air-gapped network need a product that installs there.
• Raw output. Textract returns text, key-value pairs and tables. Deciding which document arrived, which fields matter and which values to trust is work you build on top.
• Price as features stack up. Forms, Tables and Queries together cost $0.07 a page for the first million pages in US West (Oregon), against $0.0015 for text alone.
• Data handling. AWS's FAQ says Textract may store and use content to improve its services unless you opt out through an AWS Organizations policy. Many teams are happy with that opt-out. Some prefer a tool where the question never arises.

Azure Document Intelligence

Microsoft's service has prebuilt models for common documents, plus custom extraction models trained on your own samples. The free tier covers 500 pages a month. It is the only one of the three clouds that runs offline: Microsoft offers disconnected containers for environments with no internet connection, but you must apply for access and buy a commitment plan first. See docRefinery vs Azure Document Intelligence.

Google Document AI

Google prices by processor. Enterprise Document OCR is $1.50 per 1,000 pages, Layout Parser $10, and Form Parser and Custom Extractor $30 per 1,000 pages, falling at higher volumes. It also has prebuilt parsers for invoices, receipts and utility bills. It runs in Google Cloud. See docRefinery vs Google Document AI.

Reducto, Extend and LlamaParse

These three newer extraction APIs return typed fields from a schema you define. Reducto and LlamaParse both document source citations for extracted values. Reducto lists Extract at $20 per 1,000 pages and offers VPC, on-premises and air-gapped deployment on Enterprise. Extend adds evaluation sets and a human-review step, with Performance extraction at $30 per 1,000 pages plus parsing, and bring-your-own-cloud on Enterprise. LlamaParse is strongest when the output feeds an AI application. Our head-to-heads cover Reducto, Extend and LlamaParse.

Mindee

Mindee sells ready-made APIs for common back-office documents, including invoices, credit notes, delivery notes, receipts, ID cards, passports and proof of address. Plans are credit-based, with one page costing one credit, and start with a 14-day free trial. It suits developers who want a prebuilt model for a standard document without training anything.

Open source: Docling and Unstract

Docling is an MIT-licensed converter you install and run locally, which makes it the simplest way to keep documents off any third-party service. Unstract has an open-source edition, a managed cloud, and a self-hosted Enterprise edition, and its text extraction API costs $1 to $15 per 1,000 pages. With either, you own hosting, upgrades and the extraction logic. See docRefinery vs Unstract.

docRefinery

docRefinery is the layer Textract leaves to you, already built. It takes PDFs, scans and photographs and returns checked field sets for document types such as invoices, receipts, bank statements and passports.

What docRefinery does differently from Textract

• You define the output. Each field has a plain-language instruction, a "Return as" name you choose as its output key, a type and a required flag, so nobody maps a raw response onto your schema.
• One output format for every document. Every field returns text, alias, field_confidence and location, and every table returns rows, so one parser handles every document type.
• Long files, segmented. Long, multi-page files are handled at scale, separated into the documents inside them and classified into the right type.
• Layout memory. Each sender's layout is learned once and remembered, and re-trained when a form changes.
• Review built in. Values below your confidence threshold wait in a queue for a person, and a field missing from the page comes back null instead of a guess.
• Learns from corrections. A reviewer's correction becomes a suggested fix, tested on that layout's own documents before anyone applies it.
• Governed fields. Your administrator decides which fields may be extracted, from 20 document types and 785 field definitions.
• Custom types at no charge. Types outside the catalogue are trained, hosted and re-trained for you.

It runs in our cloud, in your private VPC, or air-gapped on your own servers on the Enterprise plan, so documents need never leave your network. Starter is free up to 100 pages a month, and paid plans are custom and quoted by sales.

Where Textract is still ahead of docRefinery

• Compliance and scale. Textract sits inside AWS's compliance programmes. Our SOC 2 Type II audit is in progress with no report yet, SSO is planned for Enterprise and not available yet, and we make no data-residency commitments yet.
• Plain OCR price. If you only need text, $0.0015 a page is very hard to beat.
• Maturity. Textract has years of production use. docRefinery is in Early Access and publishes no independent accuracy benchmark.
• Self-serve. Textract is billed through your AWS account. Our paid plans are quoted by sales.

How to choose

1. If documents must stay on your servers, shortlist Azure disconnected containers, Reducto Enterprise, Unstract, Docling and docRefinery Enterprise, then confirm each in writing.
2. If you need OCR only, the cloud providers are the cheapest per page.
3. If you need checked fields and review, compare what each option returns for a field that is not on the page. A plausible guess is worse than an empty field.
4. Test 50 to 100 of your own documents, including several from the same sender, and compare field by field.