Manual classification would take 3.5 years. The deadline was 6 months. A regional bank needed to classify 35 million historical documents for compliance. THE PROBLEM: - 40 years of accumulated files - Retention rules depended on document type - Sensitive data had to be identified - Manual reviewers could not meet the deadline - Regulators wanted proof of a working classification system THE n8n WORKFLOW: - Batch processor pulls archive files in chunks - Parser extracts text and metadata - Classifier assigns document type - Retention node maps policy by category - Sensitive data detector flags PII and financial fields - Confidence threshold routes low-score docs to human review - Dashboard tracks volume, accuracy, and completion THE RESULTS: - 35M documents processed in 11 days - 6% routed to human review - Random sample validation: 98.7% classification accuracy - 11.3M files marked eligible for retention-based disposal - Regulatory deadline met early THE LESSON: When manual math says “years,” adding more people is usually not the answer. Change the processing model. What archive project is sitting untouched because the manual estimate looks impossible?

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