MULTI-MODEL GROUNDING: ADVANCING INTELLIGENT DOCUMENT PROCESSING WITH GENERATIVE AI
DOI:
https://doi.org/10.34218/IJCET_16_01_135Keywords:
Intelligent Document Processing, Multi-Model Grounding, Generative AI, Document Automation, Enterprise IntegrationAbstract
Multi-model grounding in Intelligent Document Processing represents a transformative approach that leverages dual generative models to enhance document automation accuracy and efficiency. This article combines context-aware extraction with robust validation mechanisms, creating a synergistic system capable of handling diverse document types across multiple industries. The article demonstrates significant improvements in processing speed, error reduction, and compliance adherence, particularly in regulated sectors such as finance, healthcare, and legal services. Through strategic architecture design and continuous optimization, the system overcomes traditional challenges in model synchronization and conflict resolution while maintaining high security standards. The integration of human-in-the-loop validation further strengthens the system's reliability, making it a comprehensive solution for modern enterprise document processing needs.
References
MarketsandMarkets, "Intelligent Document Processing Market by Component (Solutions, Services), Deployment Mode (Cloud, On-Premises), Organization Size, Technology, Vertical (BFSI, Government, Healthcare and Life Sciences) and Region - Global Forecast to 2027," 2022. Available: https://www.marketsandmarkets.com/Market-Reports/intelligent-document-processing-market-195513136.html
Chanaka Madusanka Wickramasinghe, et al., "A Comparative Analysis of Extensible Approaches for Document Layout Segmentation - Extensibility of Document Layout Segmentation," 2023. Available: https://www.researchgate.net/publication/373829641_A_Comparative_Analysis_of_Extensible_Approaches_for_Document_Layout_Segmentation_-_Extensibility_of_Document_Layout_Segmentation
Xiaolu Zhang et al., "File processing security detection in multi-cloud environments: a process mining approach," 2023. Available: https://www.researchgate.net/publication/372162299_File_processing_security_detection_in_multi-cloud_environments_a_process_mining_approach
Anusha Venkatesh., "Understanding IDP: Data Extraction Solution - Intelligent Data Extraction," 2024. Available: https://www.infrrd.ai/blog/understanding-idp-data-extraction
Leli Alhapip, et al., "Comparative analysis of document management systems for document development process in Indonesian Public Institution: Based on curriculum development at Puskurbuk," 2017. Available: https://ieeexplore.ieee.org/document/8068544
Tyler Suss, "Mastering Intelligent Document Processing: Capabilities and Benefits of IDP for Modern Enterprises," 2024. Available: https://www.neudesic.com/blog/mastering-intelligent-document-processing/
Aarav Goel, "Common Challenges in System Analysis and How to Overcome Them," 2024. Available: https://www.koenig-solutions.com/blog/system-analysis
Alicia Y.C. Tang, "A Conflict Resolution Strategy Selection Method (ConfRSSM) in Multi-Agent Systems," 2017. Available: https://www.researchgate.net/publication/317275134_A_Conflict_Resolution_Strategy_Selection_Method_ConfRSSM_in_Multi-Agent_Systems
Kurtis Pykes, "Intelligent Document Processing with GenAI: Key Use Cases," 2024. Available: https://www.v7labs.com/blog/intelligent-document-processing
Kezia Nadira, "5 Strategies to Scale Intelligent Document Processing for Your Office Tasks," 2024. Available: https://gleematic.com/5-strategies-to-scale-intelligent-document-processing-for-your-office-tasks/
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Ashrith Reddy Mekala (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
