The Impact
10
x
improvement in search speed across digitized archives
98
%
accuracy in metadata extraction
40
%
reduction in record storage and retrieval costs
Enterprise AI: Build or Buy?
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The bank’s legacy records - stored across thousands of physical boxes with inconsistent or incomplete cataloging - were difficult to locate, validate, or delete for GDPR and legal hold. Scanned PDFs often lacked usable metadata, breaking the link between physical and digital files. Retrieval required ordering multiple boxes, resulting in long turnaround times and operational inefficiency, especially as markets used different filing structures. Regulatory obligations around retention, deletion, and auditability made manual processes risky and unsustainable. The bank required a fully on-prem solution that met data-sovereignty standards and scaled globally.
Unframe deployed an on-prem AI-native Intelligent Document Processing engine that digitizes and structures scanned PDFs into a unified Records Management system. The solution performs OCR, extracts key metadata, classifies document types, and automatically links each digital record to its corresponding physical box and location. Integrated with the bank’s Cloudera Hadoop and CIB data platform, it enables fast, multi-criteria search across clients, dates, document types, and retention attributes - turning unstructured archives into a searchable, compliant, audit-ready repository. A human-in-the-loop workflow ensures continuous accuracy improvement.
