AI-driven document classification and extraction pipeline automating invoice, contract, and compliance form processing with human-in-the-loop validation queues.
The logistics provider processed 2.4 million vendor invoices and customs documents annually through a manual data entry team of 85 operators across three regions. Error rates on critical fields such as HS codes and invoice totals drove downstream payment delays and customs holds. I designed a pipeline combining Azure AI Document Intelligence for OCR and layout analysis with custom classification models and GPT-assisted field normalization for unstructured clauses. Human reviewers handle low-confidence extractions through a .NET workflow UI with active learning feedback loops that retrain models quarterly.
Manual document processing cost $6.2M annually with 4.8% field error rates on invoice line items. Customs documentation errors caused an average 2.3-day delay on 12% of international shipments. Contract renewal clauses buried in PDF attachments were missed, resulting in unfavorable auto-renewals estimated at $1.1M in excess spend. Scaling the operations team was not viable given 18% annual document volume growth.
Documents arrive via email listeners, SFTP drops, and API uploads, landing in Azure Blob Storage with metadata tags for tenant and document class. Azure Functions orchestrate OCR, classification, and extraction stages, publishing structured JSON to a validation queue. Confidence thresholds route fields below 0.92 to human review; approved extractions post directly to SAP via idempotent API calls. Azure OpenAI assists with clause summarization and anomaly detection on payment terms deviating from master agreements.
The platform follows a stage-based pipeline architecture with dead-letter queues and replay capability per document ID. Model serving uses Azure AI Document Intelligence custom models versioned alongside extraction schema definitions stored in PostgreSQL. A .NET API layer manages tenant configuration, reviewer assignments, and audit trails for every field correction. Event-driven notifications via Service Bus trigger downstream ERP posting and exception escalation to Power Automate flows for SLA tracking.
Key interfaces and system views from the engagement.
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