An intelligent enterprise system with processing and verification of business documents using big data and AI
Balakayeva G. Zhanuzakov M. Zhapbasbayev U. Nurlybayeva K.
1 January 2025Walter de Gruyter GmbH
Journal of Intelligent Systems
2025#34Issue 1
The increasing demand for operational efficiency and data integrity has led enterprises to prioritize the digital transformation of internal workflows. This is done through automation of document-related business processes. This study proposes an intelligent enterprise system that integrates artificial intelligence and big data technologies for the automated generation, validation, and approval of business documents. The motivation behind this work derives from the need to reduce human error, enhance accuracy, and accelerate document turnaround times in enterprise environments. The authors employ large language models to automatically generate document templates and a fine-tuned bidirectional encoder representations from transformer-based classifier for validating document content. Big data tools such as Apache Spark are used for processing and cleaning large volumes of enterprise documents. Additionally, low-confidence predictions are handled through a human-in-the-loop mechanism to ensure high reliability. The research process involves system design, data collection from over 9,000 real enterprise documents, model training, and integration into a business process management system. Experimental results show that the proposed approach improves document processing efficiency while maintaining data quality. This article presents a unified framework and implementation methodology that can be adapted for broader enterprise automation needs. The authors use data from thermal grid enterprises as an example for testing the developed intelligent models.
artificial intelligence , automation , big data , business processes , digitalization , document generation , enterprise
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Department of Computer Science, Al-Farabi Kazakh National University, Almaty, 050040, Kazakhstan
Laboratory Modeling in Energy Sector, Satbayev University, Almaty, 050013, Kazakhstan
Department of Computer Science
Laboratory Modeling in Energy Sector
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