
Toshiba, a leading multinational electronics manufacturer, uses fileAI to address inefficiencies in processing procurement files. Previously, manual handling averaged ninety-two minutes per file. By embedding fileAI APIs, Toshiba automated the workflow for multilingual (English, Mandarin, Thai, etc), printed, and handwritten invoices, packing lists, and bills of lading. As a result, file processing time was reduced by 82% to just 17 minutes. This substantial improvement allowed Toshiba to significantly cut operational costs, reallocate personnel to high-priority tasks, and scale document processing capacity by 20x.
Toshiba faced significant inefficiencies with manual processing of procurement file. Each file required extensive manual entry, validation, and processing, leading to slow turnaround times, high labor costs, and limitations in operational scalability.
“The implementation of fileAI reduced document processing time from 92 minutes to 17 minutes, achieving an 82% efficiency improvement. This allows users to reallocate saved time to higher-priority tasks.”
— Auntra Matchima, Import Officer, Toshiba
Early engagement with stakeholders was crucial to simplify integration efforts and accelerate adoption across Toshiba Thailand’s operations. Comprehensive testing, particularly focused on multilingual and handwritten document processing, substantially reduced potential issues post-implementation. Additionally, ongoing monitoring and analysis have been key to sustaining continuous improvement and effectively adapting to evolving business requirements.
Looking ahead, Toshiba Thailand plans to broaden the adoption of fileAI technology to handle additional document types and business processes. Continuous optimization of the existing APIs is also underway to achieve even greater efficiency and accuracy. Moreover, Toshiba Thailand will explore deeper integration capabilities, aiming to leverage AI-driven analytics to unlock further insights and enhance procurement decision-making.
Toshiba Thailand automated procurement processing with fileAI APIs, significantly reducing document handling time by 82%. This efficiency boost enabled substantial cost savings, resource reallocation, and a twenty-fold increase in processing capacity.