DocuOCR is the OpenText Intelligent Capture alternative for teams that want accurate document data extraction without an enterprise rollout. It classifies a mixed file, reads any layout, extracts the fields you define, checks them, sends uncertain values to a built-in reviewer, and exports clean data, with self-serve per-page pricing and nothing to deploy, configure, or template first.
Built for teams that looked at OpenText Intelligent Capture, formerly Captiva, and found it was more capture platform, partner rollout, and content-stack project than their workflow needed: business users get a dashboard, developers get one REST API, and you start on your own files the same day.
Still running a Captiva-branded release? No version carrying the Captiva name is in primary maintenance any more, and Intelligent Capture 21.4 reaches its date on 1 November 2026. The full dated table is on our OpenText Captiva support lifecycle reference.
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Drop in a document you would run through OpenText Intelligent Capture and watch DocuOCR classify it, read it, and return named fields, free, no deployment and no signup required.
OpenText Intelligent Capture, formerly Captiva, is a capable, mature platform. It carries years of scan-and-capture heritage and blends traditional OCR with AI classification, machine-learned extraction, and exception workflows in one product, with a configurable workflow layer that routes classified content into downstream business systems. It runs on-premises, as embedded microservices, or in a private or hybrid cloud, and it has been named a Leader in the IDC MarketScape for intelligent document processing. For a large enterprise already invested in the OpenText content stack, with the volume, budget, and IT resources, that breadth is a real asset. The reasons teams shop for an alternative usually come down to one thing: how much platform you have to buy, deploy, and maintain to get the extraction done.
Intelligent Capture is built for large organizations, so adopting it tends to mean an enterprise sales conversation, a configured implementation that is often partner-led, and the system integration and IT resources to deploy, connect, and maintain it inside the wider OpenText ecosystem. Pricing is not published; it is licensed on volume and custom-quoted, and reviewers note that the volume-based model can make it expensive for small and mid-sized businesses, which makes the cost hard to forecast before a sales cycle. Getting accurate extraction on specialized or variable documents also involves configuration and tuning during the implementation. For a mid-market team, or anyone with a single workflow to automate, that is a lot of weight to take on for the result they actually want, which is clean data out of their documents.
DocuOCR takes the focused, ready-to-use route. Instead of deploying a capture platform and configuring it per format, you tell it which fields you want and it uses AI to read those fields on any layout, classifies a mixed batch automatically so the right extraction runs on each file, validates the values against your rules, routes anything low-confidence to a built-in review screen, and exports clean data through a dashboard for business teams and one REST call for developers, with self-serve per-page pricing. There is no rollout, no partner project, and no infrastructure to stand up. You can test it on your own documents this week to see the accuracy on your layouts and the all-in cost before you change anything.
Both apply AI to document data extraction. The difference is how you get to it: a focused, ready-to-use product that runs the same day with the workflow built in, versus a mature enterprise capture platform you deploy and configure as part of a content ecosystem, often through a partner. This is an honest look at where each one fits.
| Factor | DocuOCR | OpenText Intelligent Capture |
|---|---|---|
| Product type | Focused, ready-to-use extraction product | Mature enterprise capture and IDP platform |
| Best fit | Teams that want extraction running the same day | Large enterprise, high volume, OpenText content stack |
| Getting started | Self-serve, start on your own files today | Enterprise sales cycle and configured implementation |
| Deployment | Cloud product, nothing to stand up | On-premises, microservices, or private/hybrid cloud |
| Specialized documents | Template-free, define the fields you want | Configured and tuned during the implementation |
| Classification | Sorts a mixed batch automatically | Built in, configured during implementation |
| Human review | Low-confidence reads route to a reviewer | Exception workflows, part of the platform |
| Moving data out | Dashboard, export, and one REST API | Routes into ECM and enterprise systems |
| Pricing model | Self-serve, per page, workflow included | Not published, licensed on volume, custom-quoted |
| Try before you buy | Free on your own files, no signup to test | Demo and sales conversation |
If you are a large enterprise standardized on OpenText that wants a deployed capture platform feeding your content management stack, with on-premises options and the budget and IT resources to run it, Intelligent Capture is built for exactly that. If you want accurate extraction without an enterprise project, DocuOCR is built on intelligent document processing: it classifies, reads, extracts, validates, and exports, so your team reviews data instead of standing up a platform. If you want the neutral background before deciding, we wrote a full explainer on what OpenText Intelligent Capture and Captiva do.
Start with whether you actually need a deployed enterprise capture platform. If you do not, these are the things that decide whether an alternative fits how your team works and a budget you can plan around.
Look for a product you can start on your own documents now, with no implementation project, no partner rollout, and no sales cycle to get through first.
Favor AI that reads the fields you define on any layout, so you are not configuring a capture template or tuning rules per document type as your documents vary.
Sorts a stack of different document types automatically, so no one pre-separates files before the right extraction runs.
Self-serve per-page pricing tracks actual usage and is easy to forecast, unlike a volume-based enterprise license quoted per customer.
Choose a product that routes low-confidence values to a review screen, so accuracy holds without you checking every field by hand.
Lets you check accuracy and the all-in cost per page on the exact documents you process, free and without a signup or a sales call.
On security, the data in your documents often includes names, account numbers, and other sensitive details, so DocuOCR supports your recordkeeping with encryption in transit and at rest, role-based access, a full audit trail of every extraction and review, configurable retention, and US data handling. How records satisfy an internal control or an audit depends on how a system is configured and operated, so ask us about your specific requirements and deployment.
Classify, read, extract, validate. Drop a file in and the whole sequence runs on its own, with no platform to deploy and no template to configure first.
The engine reads a mixed batch and sorts it by document type, so the right extraction runs on each one without anyone separating the stack first.
OCR and ICR convert PDFs, photos, faxes, and scans into machine-readable text, including handwriting and stamps, without a template tuned per layout.
DocuOCR pulls the values tied to their labels and returns the fields you defined, on any layout, so you get structured data instead of just recognized text.
Values run through your rules, low-confidence reads route to review, and clean data exports to a spreadsheet or your systems by API, with an audit trail.
# invoice.pdf -> extracted data (any layout, no template) { "doc_type": "invoice", "vendor_name": "Lakeside Supply Co", "invoice_number": "INV-44821", "total_amount": "18420.55", "confidence": 0.98 } # classified, read, validated, ready for export
Teams that priced out OpenText Intelligent Capture and found the capture platform, the partner rollout, and the content-stack project were more than their workflow called for.
Want enterprise-grade extraction without an enterprise sales cycle, a deployed capture platform, or the IT resources to run one.
Want a dashboard to process documents and review results without an implementation project or capture configuration to maintain.
Receive mixed stacks of invoices, statements, and forms and want classification to sort them automatically before extraction.
Want self-serve per-page pricing they can forecast, instead of a volume-based enterprise license quoted per customer.
Run an older Captiva or Intelligent Capture setup and want extraction that reads any layout without rebuilding capture configurations.
Prefer a product they can start on their own files this week over a platform that takes a procurement and deployment cycle to stand up.
OpenText Intelligent Capture routes content into enterprise systems through a configured deployment inside its content stack. DocuOCR works the other way: you post a document to a single endpoint and get back the classified type, the recognized text, and the extracted fields with a confidence score on every value, on any layout, with nothing to deploy or template, and the review, validation, and export steps already exist in the product, so you can use the API alone or the dashboard, whichever fits. There is no infrastructure to stand up and no implementation to schedule before you call it.
# classify + extract in one request curl https://api.docuocr.com/v1/extract \ -H "Authorization: Bearer $KEY" \ -F "file=@scanned_document.pdf" \ -F "classify=true" # -> doc type + named fields + confidence
OpenText does not publish pricing for Intelligent Capture. It is licensed on document volume and custom-quoted, and reviewers note the volume-based model can make it expensive for small and mid-sized businesses, so the number depends on a sales conversation and is hard to forecast up front. Check OpenText for a current quote. DocuOCR is priced per page with classification, review, validation, and export already in the product, no enterprise quote to negotiate and no platform to deploy before you can start, so you pay for the pages you actually process. Start free to check accuracy on your own documents, then pay per page as your volume grows, with lower committed rates for high volume.
The questions teams ask most when they compare OpenText Intelligent Capture, formerly Captiva, with a focused, ready-to-use document data extraction product.
The best alternative to OpenText Intelligent Capture depends on whether you need a deployed enterprise capture platform or a product you can run the same day. OpenText Intelligent Capture, formerly Captiva, is a mature platform built for large organizations and rolled out as a configured implementation, often through a partner, inside OpenText's broader content ecosystem. If you do not need an on-premises capture suite and the IT resources to run it, a focused, ready-to-use product fits better. DocuOCR classifies a mixed file, reads any layout, extracts the fields you define, validates them, routes low-confidence reads to a built-in reviewer, and exports clean data through a dashboard and one REST API, with self-serve per-page pricing. You can test it on your own documents the same day, with no sales cycle or rollout.
OpenText Intelligent Capture is used by large organizations to capture documents and automate document-heavy processes, turning invoices, forms, and applications into structured data that flows into back-office systems. Common use cases include accounts payable invoice processing, employee and customer onboarding, insurance claims, and audit readiness. The product classifies documents, extracts fields, scores confidence, queues low-confidence reads for review, and routes content into downstream systems, usually as a configured implementation. Teams that want the same extraction without an enterprise rollout, or that process lower volumes, tend to look at a focused, self-serve alternative.
Yes. OpenText Intelligent Capture is the product formerly known as OpenText Captiva, so the Captiva capture engine many teams remember now sits under the Intelligent Capture name, and a lot of buyers still search for it as Captiva. The capabilities carry the same scan-and-capture heritage: ingest documents, classify them, extract data, and route content into enterprise systems, deployed on-premises or in the cloud as a configured implementation. DocuOCR is a different category: a focused, ready-to-use document data extraction product you run the same day, not a platform you deploy, so the comparison is about how much you have to stand up to get clean data out of your documents.
OpenText Intelligent Capture is not free. It is an enterprise platform that does not publish pricing; it is licensed on document volume and custom-quoted, and it is typically deployed through OpenText or an implementation partner, so the all-in cost includes the license plus the implementation. Reviewers note the volume-based licensing can make it expensive for small and mid-sized businesses. DocuOCR takes a different approach: you can process documents free to check accuracy on your own files before you commit, and instead of an enterprise contract you pay per page for what you actually process, with classification, review, validation, and export already included in the product.
OpenText does not publish pricing for Intelligent Capture. It is licensed on document volume and quoted per customer, and it is usually sold and deployed through OpenText or a partner, so the all-in number includes the license plus the implementation and integration work. Reviewers note the volume-based licensing model can make it expensive for small and medium businesses, which makes the cost hard to forecast before a sales cycle. DocuOCR keeps it self-serve and per page: one price that already includes classification, human review, validation, and export, so you pay for the pages you process and can forecast the cost from your own volume. Check OpenText for a current quote.
OpenText Intelligent Capture is a capable, mature platform, but teams cite a few common reasons they look at alternatives. It is built for large organizations, so adopting it tends to mean an enterprise sales cycle, a configured implementation that is often partner-led, and the IT resources to deploy, integrate, and maintain it inside OpenText's broader content ecosystem, which is a lot for a mid-market team or a single workflow. Pricing is not published and is licensed on volume, which reviewers note can make it expensive for smaller businesses and hard to forecast. A focused, self-serve product that reads any layout, ships classification, review, and export, and prices per page removes that setup and overhead for teams that do not need a full capture platform.
OpenText Intelligent Capture blends traditional OCR with AI classification, machine-learned extraction, and exception workflows in one product, with a configurable workflow layer that routes classified content into downstream business systems. Like most enterprise capture suites, getting accurate extraction on specialized or variable documents involves configuration and tuning during the implementation. DocuOCR is template-free: it reads the fields you define on any layout using AI, without you building a capture configuration per format or training a model first, which is the main reason teams that want extraction without a configuration project switch.
OpenText Capture, the broader name for the Intelligent Capture product, is the front door to OpenText's content stack: it ingests documents from scanners, email, and files, classifies and extracts them, and routes the structured content into enterprise content management and downstream systems. It is one component of a much larger OpenText ecosystem, deployed as a configured implementation. DocuOCR covers the document data extraction part of that, classify, read, extract, validate, review, export, as a ready-to-use product, so teams that mainly need clean structured data out of their documents get it without standing up a full capture and content platform.
Start with whether you actually need a deployed enterprise capture platform. If you do not, look for template-free AI extraction that reads any layout without configuring a capture template per format, built-in document classification so a mixed batch sorts itself, a human review step for low-confidence values, schema-based output that returns named fields, and both a dashboard for business users and an API for developers. Prefer self-serve per-page pricing over a volume-based enterprise quote so cost tracks your actual usage and you can forecast it, and favor a tool you can try free on your own documents and start the same day without a sales cycle or a partner rollout. Then check the security controls, encryption, access control, audit logging, and where your data is handled, before you move production volume.
A primer on OpenText's capture stack before you weigh a ready-to-use alternative.
The end-to-end IDP workflow that classifies, reads, extracts, and validates documents in one pipeline.
The full platform behind the comparison, with a dashboard for teams who want document data without code.
How DocuOCR reads PDFs, scans, and photos into machine-readable text before it extracts named fields.
The single REST call that returns classified type, text, and named fields for your own automation.
Comparing DocuOCR with Kofax (Tungsten Automation), another enterprise capture platform, for teams weighing a deployed suite against a ready-to-use product.
Comparing DocuOCR with ABBYY, another enterprise capture platform, for teams weighing a deployed suite against a ready-to-use product.
Upload a document you would run through OpenText Intelligent Capture, watch DocuOCR classify it, read it, and return named fields with nothing to deploy, then use the dashboard or connect the API to process every document that follows on its own.
