90% no-touch extraction from handwritten, faxed and scanned healthcare documents
Client: A US healthcare services organisation processing high volumes of clinical and operational documents.
Leadership experience: this programme was delivered by a member of Robral's leadership team during a previous role at another organisation, and is shared with their permission. It is not a Robral Technologies engagement. Client identity is withheld.
- Industry
- Healthcare operations
- Region
- USA
- Inputs
- Handwritten, fax, email, PDF
- Solution
- OCR + RAG platform
The challenge
Huge volumes of unstructured documents: handwritten prescriptions, faxes, email threads, Office files and scans.
Manual processing caused high effort, delays in clinical workflows and inconsistent accuracy.
Heavy dependency on human interpreters for difficult documents.
What was built
Combined OCR with retrieval-augmented generation to interpret complex or low-quality documents.
Field-level and file-level confidence scores, with an exception workflow for the few documents that need review.
Ready APIs into EHR, scheduling, CRM and care-management systems.
A real-time dashboard of extractions, exceptions and confidence, plus clean Excel export.
- 90%no-touch processing at high confidence
- <10%routed to manual review
- 6healthcare providers live
Outcomes
- 90% no-touch processing of fields and documents at strong confidence levels.
- Significantly less manual effort, with better turnaround time and accuracy.
- Scaled across many document types and six providers' daily operations.
Technology & capabilities
- React
- Node.js
- SQL Server
- OCR
- RAG
- OpenAI
- Gemini
- Azure DevOps
Relevant forAny document-heavy operation, such as healthcare, insurance, finance, logistics or legal, still keying data by hand.
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