Featured work 02 · Document intelligence
Intelligent document processing system
An enterprise that handles large volumes of business documents had a platform that timed out under heavy load. We rebuilt it as independent microservices, so large documents and scanned files are processed reliably.
- Microservices architecture
- OCR
- PDF processing
- Asynchronous processing
The challenge
A platform that timed out under load
Processing large documents was slow and unreliable, and turning scanned files into usable data regularly failed when the system was busy.
What we built
The solution
- Independent microservices for ingestion, OCR, transformation and PDF generation.
- Performance bottlenecks found and processing flows changed, so long-running work no longer hits timeouts.
- An OCR pipeline that pulls structured text and data out of scanned documents and images.
- Automated PDF generation and editing: merging, splitting, annotation and building documents from templates.
The outcome
Impact
- No more timeouts
- Large and complex documents process reliably.
- Independent scaling
- Each service scales on its own, so heavy OCR loads no longer slow down the rest of the system.
- Microservices architecture
- OCR
- PDF processing
- Asynchronous processing
- REST APIs
FAQ
Frequently asked questions
Why split document processing into microservices?
OCR is far heavier than ingestion or PDF generation. Running each as its own service lets the heavy work scale on its own without slowing everything else down.
Can OCR extract structured data, not just text?
Yes. The pipeline pulls structured text and data out of scanned documents and images so it can be used by other systems.
Talk to us
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