A leading LNG export company faced ongoing challenges managing extensive repositories of technical drawings due to inconsistent and unstructured metadata. Critical information such as document titles, revision numbers, and document IDs was often difficult to locate, requiring employees to spend significant time manually searching and indexing records. These inefficiencies impacted project timelines, reduced operational productivity, and increased compliance risks in an environment where accurate document traceability was essential.
To address these challenges, the company implemented the Cognitive Data Extractor (rannsCDE), an AI-powered solution designed to automate metadata extraction from technical drawings. Using advanced document intelligence, rannsCDE automatically identified and captured key metadata fields, including titles, revision numbers, and document identifiers, directly from document images and files. By eliminating manual data entry and standardizing metadata capture, the solution improved consistency, accuracy, and processing speed across the organization’s document management workflows.
The deployment of rannsCDE enabled the company to process more than 500,000 document pages annually while maintaining over 95% AI extraction accuracy. Manual effort was reduced by more than 70%, allowing teams to retrieve documents faster and make informed decisions with greater confidence. Enhanced indexing, improved searchability, and stronger document traceability not only accelerated operational workflows but also strengthened compliance and governance across the organization
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