How do you implement intelligent document routing in automated workflows?

Intelligent document routing uses AI classification to direct documents to appropriate processing workflows. Architecture: document ingestion (email, upload, scan) feeds into a classification model that determines document type (invoice, contract, purchase order, support ticket), then routes to type-specific processing workflows. Classification: fine-tune a BERT-based classifier on your document types (typically needs 100-500 labeled examples per class), or use zero-shot classification with GPT models for rapid prototyping. Multi-stage routing: first classify document type, then extract key fields to determine business routing (e.g., invoice amount determines approval level, contract type determines legal reviewer). Implementation: combine text classification with rule-based routing (if-then logic on extracted fields), implement confidence thresholds (auto-route above 0.9 confidence, human triage below), and maintain a feedback loop where corrections improve the classifier. Integration: connect to document management systems (SharePoint, Google Drive, Box), ticketing systems (Jira, ServiceNow), and ERP systems (SAP, NetSuite) via API. Metrics: classification accuracy, routing accuracy, straight-through processing rate, and average time from receipt to correct routing.