Large-scale medical records automation processing 694K+ patient records
Processing hundreds of thousands of patient records manually would take months, creating backlogs and delays. Traditional automation struggles with complex web interfaces, authentication flows, and error recovery.
Production-grade automation system with intelligent error recovery, distributed cloud infrastructure, and three-layer verification. Processes 2,800-3,200 patients/hour with 8 concurrent browsers and zero false negatives.
Production-grade distributed automation system processing 694K patient records across cloud infrastructure with intelligent error recovery, 24/7 autonomous operation, and triple-layer verification
Phase 1: Requirements & Design - Platform analysis, CAPTCHA/session limits identification, data partitioning
Phase 2: Proof of Concept - Single browser automation, OAuth setup, end-to-end workflow validation
Phase 3: Scale-Up - Parallel browser processing (8 concurrent), distributed architecture (2 droplets)
Phase 4: Resilience - Session expiry recovery, Start Day/Night handling, error classification system
Phase 5: Production Deployment - Clean databases, monitoring, comprehensive documentation
Phase 6: Enhanced Resume - Google Drive verification, zero false negatives guarantee
Transferable skills and capabilities beyond the technical implementation
Understood manual process inefficiency (6-8 months of work) and designed automation to deliver same outcome in 9-10 days. Identified and automated daily operational requirements.
Recognized constraints (session limits, CAPTCHA, timeouts), designed solution respecting those constraints (8 browsers, sequential startup), built resilience into every layer.
Sophisticated error classification (failed search vs. no PDFs), hybrid verification (database + actual files), mathematical verification of coverage.
Self-healing system with auto-recovery, complete auditability through database tracking, operator-friendly with one-command status checks and clear documentation.
Used managed services where appropriate (Google Drive, 2Captcha), avoided over-engineering (SQLite sufficient), balanced speed with reliability.
Evaluated OAuth vs Service Account authentication, identified infrastructure constraints before full migration, made informed decisions based on operational requirements.