Hari Patchigolla
Hari is a Data Scientist at Autodesk, focusing on Generative AI and Machine Learning for enterprise finance AI solutions. He specializes in agentic architectures to optimize critical financial workflows. Previously, he built predictive analytics and NLP models at Optum and conducted bioinformatics research at the University of Connecticut. With deep expertise in AI-driven automation and large-scale data solutions, Hari is passionate about leveraging advanced AI techniques to drive meaningful business impact.
Speaker Sessions
How Model Context Protocol (MCP) Can Help Enterprises Scale and Manage AI Tools
MCP redefines how enterprises can operationalize AI by addressing critical gaps in traditional tool integration. In this workshop, we’ll explore how to implement agents that take advantage of MCP’s capabilities. One key benefit is dynamic tool discovery—unlike static frameworks that require manual tool wiring, MCP enables agents to discover and utilize new tools at runtime, allowing organizations to quickly change how the tools are implemented without rearchitecting their systems. Centralized governance further streamlines operations by managing updates, permissions, and compliance policies from a single MCP server, ensuring consistency across all agents and eliminating version-lock issues. Finally, MCP offers elastic scalability, enabling tools to scale independently of the agent architecture so enterprises can grow their systems without disrupting existing infrastructure. Beyond implementation, we’ll also dive into the core concepts behind MCP and discuss why it’s gaining momentum across the AI landscape.