A global chemical industry client struggled with metadata proliferation from managing relationships with over 90 supplier partners. Aspire Systems proposed an AI-powered solution using ML algorithms to standardize documents, split large files, classify them with CNN models, and extract data via Tesseract and YOLO for metadata fields like dates, names, and amounts. The system consolidated content with NER for full context. Benefits included halving time and costs, higher accuracy with zero human error, scalable handling of large datasets, more organized inputs, and enhanced metadata extraction from scanned documents.

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