Thursday disaster: Law firm's Mistral OCR hitting 64% accuracy on contracts. Partner meeting Friday morning. THE FAILURE CASCADE Client processing merger documents - Mistral OCR: 64% accuracy (unacceptable) - Google Vision: 78% but $400/day cost - Tesseract: 51% (worse) - AWS Textract: Connection timeouts under load 3 AM emergency. Client threatening to fire us. THE HYBRID RESCUE n8n WORKFLOW Built intelligent routing system: Node 1: Document quality assessment - Resolution check - Text density analysis - Table detection - Handwriting presence Node 2: Processing route decision Path A: High-quality typed text → Mistral OCR (fast, cheap) Path B: Poor quality/scanned → Enhanced parsing API Path C: Complex tables → Structured extraction Path D: Mixed content → Multi-pass processing Node 3: Confidence validation and retry logic Node 4: Results merging with conflict resolution Node 5: Human review queue for <85% confidence THE FRIDAY MORNING SAVE Reprocessed all 8,000 documents overnight: - 4,200 docs: Mistral only (97% accuracy) - 2,400 docs: Enhanced parsing (94% accuracy) - 1,100 docs: Structured extraction (96% accuracy) - 300 docs: Human review flagged Overall accuracy: 95.8% Processing cost: $127 (vs $400 Google Vision estimate) Processing time: 6 hours (vs 3 days manual) Partner meeting result: "This is exactly what we needed." SCALED THE HYBRID APPROACH Now standard across all document workflows: - No single OCR for everything - Intelligent routing based on document characteristics - Automatic fallback strategies - Cost optimization through right-tool-for-job Current legal document processing: - 12 law firms using hybrid system - 150,000+ documents monthly - 96.4% average accuracy - Monthly revenue: $18,400 THE LESSON LEARNED OCR isn't broken. Using wrong OCR for the document type is broken. Hybrid routing now handles: - Medical forms: Handwriting detection → Enhanced processing - Invoices: Template matching → Standard OCR - Contracts: Complexity assessment → Appropriate method

Hey everyone,I’m working on a new case study to see how AI automation impacts different businesses. I’d love to collaborate with a few members here who are open to experimenting with automation and then sharing honest feedback/results with the group. There’s no service fee for being part of this experiment — you’d just need to have the tools/software we’ll test on. If you’re curious about participating in this little project and helping me gather data for the case study, drop a comment or send me a message.