AI-Driven Software Development Architecture for Enterprise Integration: Leveraging Oracle EBS, SAP, and BERT Models in Quantum-Optimized Business Analytics
DOI:
https://doi.org/10.15680/IJCTECE.2025.0806008Keywords:
AI-enabled clinical intelligence, Oracle EBS, SAP framework, BERT models, quantum optimization, business analytics, cloud-native healthcare, NLP, predictive diagnostics, enterprise resource planning (ERP), intelligent automation, healthcare interoperability, data-driven decision-making.Abstract
The integration of Artificial Intelligence (AI) with enterprise systems such as Oracle E-Business Suite (EBS) and SAP frameworks has revolutionized data-driven clinical decision-making and operational intelligence. This paper presents an AI-enabled clinical intelligence framework that synergizes BERT-based natural language processing (NLP) with quantum-optimized business analytics to enhance predictive, preventive, and personalized healthcare management. By embedding pre-trained BERT models within the Oracle EBS and SAP analytics layers, the system achieves contextual understanding of unstructured clinical narratives, automates anomaly detection, and improves diagnostic accuracy. The framework incorporates quantum-inspired optimization algorithms to accelerate large-scale data analysis and enhance ERP-driven clinical workflows. Furthermore, it integrates cloud-native architectures for secure data interoperability, ensuring compliance with regulatory standards such as HIPAA and GDPR. The proposed model not only improves clinical decision intelligence but also facilitates real-time business insight generation, cost optimization, and interoperability between heterogeneous healthcare systems. Experimental evaluation demonstrates the potential of the approach to transform enterprise healthcare ecosystems into adaptive, intelligent, and quantum-accelerated environments.
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