An Autonomous Cloud-Based Decision Support Framework Integrating Agentic AI, Business Analytics, Income Tax, and GST Intelligence

Artificial intelligence, cloud computing, and business analytics are increasingly converging to support automated financial decision making, yet integrated frameworks combining business intelligence with taxation remain limited. This study develops an autonomous cloud-based decision-support framework integrating agentic AI, business analytics, Income Tax intelligence, and GST intelligence. The framework coordinates specialized agents for data processing, business analytics, banking analysis, tax screening, GST rule evaluation, anomaly detection, orchestration, and decision support. Empirical evaluation used integrated commercial and banking records to assess sales, profitability, payment behavior, cash flow, and transaction-risk indicators. Results showed total sales of ₹437,771, recorded profit of ₹36,963, bank credits of ₹420,570.51, and bank debits of ₹422,089.90. UPI represented 45.07% of integrated records, while anomaly screening identified 152 high-value sales observations and 135 high-value banking transactions. Income Tax and GST outputs were generated as rule-based intelligence indicators rather than statutory assessments because direct return variables were unavailable. The proposed architecture demonstrates the feasibility of combining autonomous agents, cloud-enabled analytics, financial monitoring, and tax-oriented screening while retaining explainability, auditability, and human oversight for consequential decisions. The framework provides a scalable foundation for future enterprise deployment, real-time integration, and compliance-oriented financial intelligence applications.