Case Study - Intake/OCR & Spend Analytics for Healthcare
Document intake & OCR with auto-classification, summarization, routing and budgeting & spend analytics copilot over GL/PO data.
- Client
- National Health Network
- Year
- Service
- Document AI, Spend Analytics, MLOps
Overview
A national health network struggled with paper-heavy correspondence and unreliable rolling forecasts across 14 hospitals.
We delivered document intake & OCR (Arabic/English capability retained for international referrals), auto-classification, summarization, routing with SLA timers.
The budgeting & spend copilot operates over GL/PO data to explain variances, detect leakage, and forecast spend with dashboards for controllers and CFO.
Private-cloud deployment includes SOC/SIEM hooks, retention and redaction policies, processing 1.8M pages and enabling 600+ monthly users across registry, finance, and operations.
What we did
- Document Intake & OCR
- Auto-classification
- Spend Analytics Copilot
- Private-cloud Deployment
- SOC/SIEM Integration
- Arabic/English Processing
- Registry backlog cleared
- 12 days
- SLA breaches reduction
- 27%
- Forecast MAPE improvement
- 37%
- Spreadsheet chains reduced
- 60%