Case Study - Million-page OCR at predictable unit cost.
Engineered an OCR pipeline designed to process massive document volumes with strict unit-cost discipline. Auto-scaling, monitoring, cost alerting — all at approximately $0.04 per 1,000 pages.
- Domain
- Scale Engineering / OCR
- Year
- Service
- OCR, Scale Engineering, Cost Optimization
The problem
High-volume document processing with a hard constraint: unit cost had to be predictable and controlled. No "we'll optimize later" — the budget was a requirement, not a wish.
The pipeline needed to handle variable load patterns, maintain quality across document types, and provide real-time visibility into cost and throughput.
What we built
An OCR pipeline engineered for scale and cost discipline:
- Auto-scaling infrastructure that scales with document volume — not with cloud bills
- Unit-cost monitoring built into the pipeline, not bolted on after
- Cost alerting so you know before the invoice arrives, not after
- Quality gates ensuring OCR accuracy doesn't degrade under load
- Throughput monitoring with real-time dashboards
The key insight: at scale, the engineering challenge isn't the model — it's the system around the model. Queue management, retry logic, cost attribution, and graceful degradation under pressure.
- OCR Pipeline
- Auto-scaling
- Cost Monitoring
- Throughput Engineering
- Peak throughput
- ~1M pages/h
- Per 1,000 pages
- $0.04
- Cost and throughput dashboards
- Real-time
- Scaling with load patterns
- Auto