Mr. Sridhar Korimilli

Enterprise-Scale AI and Cloud Innovation: Scalable Blueprints for Modern Data Ecosystems

Abstract:

As organizations embrace AI to transform operations and accelerate insights, the challenge lies in designing architectures that are not only scalable but also secure, explainable, and enterprise-ready. This talk presents a modern blueprint for deploying AI at scale by harnessing the integrated capabilities of Oracle 23c, with its AI/ML extensions, advanced database architecture, and security-first design principles.

With deep experience leading enterprise cloud and data modernization programs, I'll demonstrate how Oracle 23c AI empowers organizations to run in-database machine learning, real-time vector-based semantic search, and autonomous inferencing, all while ensuring robust data governance and minimal operational overhead. When combined with Oracle Cloud Infrastructure (OCI), these capabilities enable enterprises to build intelligent, policy-driven ecosystems that support regulatory compliance and mission-critical analytics.

The session also highlights research-driven innovations, including Retrieval-Augmented Generation (RAG) systems that deliver faster, scalable data insights by fusing traditional databases with generative AI for enterprise-scale Q&A and knowledge discovery. My cybersecurity automation solutions have fortified cloud environments through real-time threat detection and preventive risk mitigation, significantly improving resilience across critical workloads. Furthermore, my zero-downtime transition frameworks have reduced operational disruptions by over 60%, accelerating cloud adoption across healthcare, finance, and enterprise IT sectors.

Key discussion areas include:

Leveraging Oracle 23c’s converged database engine for unified processing of structured, unstructured, and vector data

Designing AI/ML pipelines natively within Oracle 23c to eliminate data movement and accelerate insight generation

Enabling enterprise-grade database security through built-in auditing, data redaction, encryption, and access control mechanisms

Applying responsible AI practices—including fairness, explainability, and auditability—at the core of the data and model lifecycle

Real-world architectures combining OCI Data Science, Autonomous Data Warehouse, and Oracle GoldenGate to deliver scalable, secure AI across hybrid and multi-cloud environments

This session provides researchers, data scientists, and practitioners with actionable strategies to build future-ready data science infrastructures that are performant, secure, and aligned with enterprise AI goals.

 Profile:

Sridhar Krishna Korimilli is a Senior  Technical Leader at Oracle America, Inc., with over 19 years of experience in enterprise IT modernization, cloud-native architecture, AI/ML enablement, and secure data engineering. He has led high-impact transformation initiatives across global enterprises including JPMorgan Chase, Dell Technologies, UnitedHealth Group, and Fannie Mae, delivering end-to-end modernization of data ecosystems, AI platforms, and database security frameworks.

He holds a Master of Science in Computer Science from Texas A&M University,Kingsville,  a Bachelor of Technology in Computer Science and Information Technology Engineering from Jawaharlal Nehru Technological University, and an Executive MBA from the Quantic School of Business and Technology with a focus on business strategy, corporate finance, and innovation management.

Sridhar is a Certified Oracle Cloud Infrastructure 2025 Multicloud Architect Professional, an Oracle Certified Professional (OCP), and has earned multiple certifications in AI and cloud data platforms. His technical focus areas include Oracle 23c AI, Oracle GoldenGate, OCI Data Science, Autonomous Database, and enterprise-grade database security for regulated industries.

He is a Senior Member IEEE, Fellow IETE, Fellow Hackathon Raptors, a peer reviewer and international awards judge in AI and cybersecurity, and has been an invited speaker at global conferences including IEEE AIC, ICIVC, and others. Sridhar actively contributes to the advancement of responsible and secure AI adoption in large-scale environments by combining deep technical knowledge with strategic leadership.