AI-Powered Enterprise Intelligence Platform using Generative AI and Hybrid Cloud Architecture
DOI:
https://doi.org/10.15680/IJMRSETM.2025.0102010Keywords:
Artificial Intelligence, Generative AI, Enterprise Intelligence, Hybrid Cloud, Business Intelligence, Retrieval-Augmented Generation, Machine Learning, Cloud Computing, Data Analytics, Decision Support, Enterprise Data, Responsible AIAbstract
The rapid growth of enterprise data from business applications, cloud services, Internet of Things devices, customer interactions, documents, and operational systems has created both opportunities and challenges for organizational decision-making. Conventional business intelligence platforms frequently depend on structured datasets, predefined queries, dashboards, and historical reporting, limiting their ability to provide contextual, conversational, and predictive insights. This paper proposes an AI-powered enterprise intelligence platform that combines Generative Artificial Intelligence (GenAI), machine learning, retrieval-augmented generation, and hybrid cloud architecture to transform heterogeneous enterprise data into actionable intelligence. The proposed platform integrates private and public cloud environments to balance data sovereignty, security, scalability, computational efficiency, and accessibility. A hybrid data architecture enables sensitive information to remain within controlled enterprise environments while selected workloads, foundation models, and elastic computing resources can operate in public cloud infrastructure. Generative AI provides natural-language interaction, automated analytical narratives, intelligent summarization, knowledge retrieval, and decision-support capabilities. The research adopts a design-oriented methodology involving requirements analysis, architecture design, prototype development, experimental evaluation, and security assessment. Evaluation focuses on accuracy, response latency, scalability, data security, user satisfaction, and cost efficiency. The proposed approach aims to establish a flexible enterprise intelligence ecosystem capable of supporting real-time analysis and strategic decision-making while maintaining governance, transparency, and responsible AI principles
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