Impact Factor (2025): 6.9
DOI Prefix: 10.47001/IRJIET
Vol 9 No 2025 (2025): Volume 9, Special Issue of ICCIS-2025 May 2025 | Pages: 200-205
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 11-06-2025
Businesses generate vast visual data (e.g., quality check photos, warehouse snapshots, invoices, customer images), but traditional Enterprise Resource Planning (ERP) systems, built for structured data, cannot process it. This study explores integrating Vision Language Models (VLMs), AI combining computer vision and language processing, with ERPs to automate tasks like quality control, inventory monitoring, and document processing. We assess integration feasibility with Microsoft Dynamics 365 Business Central, Salesforce, and SAP S/4HANA, proposing an API-driven system architecture. VLMs face precision challenges, and ERP readiness varies: Microsoft Dynamics needs custom development, Salesforce offers flexible APIs, and SAP S/4HANA is robust but complex. Strategic planning and leveraging VLM strengths enable AI-enhanced enterprise systems.
Vision Language Models, ERP Integration, Enterprise AI, Computer Vision, Automation, API Integration, Microsoft Dynamics 365, Salesforce, SAP S/4HANA, Multimodal AI
T Bharath Chandra. (2025). Bridging the Visual Gap: Integrating Vision Language Models (VLM) and Artificial Intelligence (AI) with Enterprise Resource Planning (ERP) Software System. In proceeding of Second International Conference on Computing and Intelligent Systems (ICCIS-2025), published in IRJIET, Volume 9, Special Issue ICCIS-2025, pp 200-205. Article DOI https://doi.org/10.47001/IRJIET/2025.ICCIS-202532
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