Huntington Bank: Redacting sensitive data from 400M+ documents with AWS
Huntington Bank used AWS services to redact sensitive data from 400M+ documents, cutting the timeline from years to months.
Huntington National Bank built a scalable redaction pipeline using Amazon Textract, SageMaker, Step Functions, and Lambda to find and redact sensitive customer data across more than 400 million documents, reducing a multi-year effort to months. It matters as a real-world enterprise case study for large-scale, compliance-driven document processing, but it is a vendor architecture write-up rather than a major AI industry signal.