A dedicated human review layer built into extraction. Backed by proprietary models trained on billions of documents over 15 years. That's the infrastructure behind the API.
Generic OCR's have built solid APIs. But they're solving for breadth — passports, bank statements, HR documents, identity verification. Financial document extraction is one use case among many for them. For us, it's the only one. That focus shows in the benchmark numbers. 99% of documents returned 100% correct. Not a field-level average. The whole document.
Building with a general OCR layer plus a classification model plus an LLM for field extraction feels flexible. In practice, every handoff is a failure point. One model misreads a supplier name, the next misclassifies the document, the third extracts the wrong total. We run a single purpose-built pipeline with human in the loop catching what the model misses — in under 3 minutes, invisible to your users.
In-house / traditional OCR | Dext | |
|---|---|---|
Documents fully correct | 45-90% | 99% - with human review built in |
Who fixes errors | Your users | Our pipeline |
New geography or format | Delays, patches, tickets | Works day one |
Setup | Configuration required | No templates, no training |
Benchmarking | Usually none | 100k documents/month |
Who owns the errors | Passed back to your team | Human review & invisible to users |
Vendor stability | Varies | Backed by IRIS Group |
JSON in, structured data out. Invoices, receipts, bank statements, expense documents. Full field extraction: header, line items, totals, tax, supplier.
Zero-shot extraction. New document format or geography — no setup required, no retraining cycle.
We benchmark 100,000 random documents every month and share the results. Backed by 150+ engineers and data controllers dedicated to accuracy. You'll always know exactly what your accuracy is.
New geography, new document formats, new languages — no setup sprint, no retraining cycle, no engineering delays. Zero-shot extraction means your product works from the first document, wherever you launch next.
Invoices, receipts, bank statements. Every field extracted correctly, every time. 1,000 human reviewers catch what the model misses in under 3 minutes — invisible to your users. Your reputation stays intact.
In-house pipeline, generic API, or a model that needs constant babysitting — every hour your team spends on extraction is an hour not spent on your product. Hand it off. Own the roadmap instead.
Dext EaaS extracts data from a wide range of financial documents:
Transaction documents: Invoices, sales invoices, receipts, credit notes, delivery notes, expense statements, rental statements, supplier statements, mileage documents, ATM withdrawals
Bank documents: Bank statements, including multi-page statements with full transaction-level extraction (dates, amounts, opening and closing balances)
All document types support multi-currency, multi-language, and multi-page processing. Submit scanned, photographed, or digital PDF — no templates, no configuration required.
Header data (supplier, date, document reference, currency), totals (net, tax, gross), line items (description, quantity, unit price, total), payment terms, and bank statement transactions. Full field list in the documentation.
Yes. Built on 15 years of financial document context, not a generic classifier.
Volume-based pricing with no setup cost and no support subscription fee. Talk to the team for a quote based on your expected document volumes.
All EaaS customers get access to a dedicated Slack channel with direct access to the Dext engineering team. No ticket queues.
Most teams are live within a few days. REST API, JSON output, clear documentation. No template setup, no training period.
A dedicated sandbox with full API access. Test against your own documents before you write a line of production code. No limits on test volume during evaluation, and no commitment required to get started.
Dedicated technical support, no subscription fee for support.
We benchmark 100,000 random documents every month — not a curated test set. "Document fully correct" means every field on that document is correct. Not an average. We share the results.
It depends on how that number is measured. 90% field accuracy means most documents have at least one error. The question is: who finds those errors and who fixes them? We'd rather show you the comparison than argue about the number.
Yes. Full details in our security documentation — available on request.
EU-based processing available. Talk to the team for specifics relevant to your architecture. You can review Dext's full security posture, certifications, and incident history at trust.dext.com.