An LNG export company faced a persistent struggle managing vast archives of technical drawings, particularly due to the lack of structured, searchable metadata. Without consistent indexing of critical fields like titles, revision numbers, and document IDs, locating specific data became a manual, time-consuming process. These inefficiencies not only delayed project timelines but also introduced compliance risks, especially in environments requiring strict documentation traceability.
To overcome these challenges, our AI-powered Cognitive Data Extractor (CDE) was implemented to automate the extraction of metadata directly from technical drawings. By automatically identifying and capturing fields such as the title, revision, and document number from hundreds of thousands of document pages, the system eliminated the need for depending on a person to manually enter data. CDE transformed how metadata was processed, bringing consistency, accuracy, and speed to a task that previously required hours of manual effort.
As a result, more than 500,000 pages were processed annually with over 95% AI accuracy. The company reported more than 70% savings in manual effort, which allowed documents to be retrieved faster and teams to make informed decisions. With improved indexing and accessibility, the solution not only accelerated workflows but also ensured compliant document management.
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