MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202611008826 A) filed by Pawan Whig; Pramod Raja Konda; Nikita Chawla; and Ms. Radhika Mahajan, New Delhi, on Jan. 29, for 'a secure artificial intelligence and machine learning system for enterprise data analytics and financial intelligence (sai-fi system).'
Inventor(s) include Pawan Whig; Pramod Raja Konda; Nikita Chawla; and Ms. Radhika Mahajan.
The application for the patent was published on March 13, under issue no. 11/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a secure Artificial Intelligence and Machine Learning based system for enterprise-scale data analytics and financial intelligence, herein referred to as the SAI-FI System. The SAI-FI System provides a cloud-native, microservices-oriented architecture that integrates advanced data ingestion, processing, and analytics with AI-ML driven automation to deliver real-time, predictive, and prescriptive insights across enterprise and financial service environments. The SAI-FI System enables secure collection, normalization, and transformation of structured and unstructured data from multiple sources, including enterprise applications, cloud platforms, and financial systems. AI-ML algorithms within the SAI-FI System perform advanced data analytics, anomaly detection, fraud and risk assessment, forecasting, and intelligent decision support. Integrated cybersecurity mechanisms, including data encryption, identity-based access control, audit logging, and continuous threat monitoring, ensure data confidentiality, integrity, and regulatory compliance. The SAI-FI System further supports automated DevOps, MLOps, and agile product workflows, enabling continuous model training, deployment, validation, and optimization in dynamic enterprise environments. By unifying secure data engineering, AI-ML driven automation, and financial intelligence within a single framework, the SAI-FI System enhances scalability, operational efficiency, and decision accuracy for enterprises operating in finance, FinTech, and other data-intensive domains."
Disclaimer: Curated by HT Syndication.