MCP in Practice: Connecting AI Agents to Your Enterprise Data Platforms
Key Speaker
Technical Lead, Ksolves India Limited
He is a Technical Lead with hands-on experience in enterprise AI integration, Model Context Protocol implementation, data platform architecture, and building governed AI workflows on Snowflake and Databricks.
In this session, Ketan Goel, Technical Lead at Ksolves India Limited, addresses the connectivity challenge that quietly derails most enterprise AI initiatives: connecting AI agents to business data securely, reliably, and at scale is significantly harder than building the models themselves.
Most enterprise AI projects do not fail because of model quality. They fail because the infrastructure connecting AI to business systems was never designed with agents in mind. Data access is fragmented, governance is inconsistent, and the surface area for security risk grows with every integration. Teams end up building one-off connectors that are brittle, difficult to audit, and impossible to scale across the data platforms an enterprise actually depends on.
The Model Context Protocol is emerging as the open standard that changes this. MCP provides a structured, governed way for AI agents to interact with enterprise systems, with controlled access to tools and data, without bypassing the security and governance requirements that enterprise environments demand. This webinar demonstrates MCP in practice, not as a concept, but as a working implementation. Ketan walks through connecting AI agents to Snowflake and Databricks through MCP, shows a live end-to-end demonstration of AI agents analyzing transactions, detecting fraud patterns, and searching customer complaints with governed data access, and covers the practical steps teams need to integrate MCP into their own enterprise data platforms.
If your organization is building AI agents or enterprise AI applications, this session provides practical, implementation-focused insights into making secure AI and enterprise data connectivity a reality.
Key Takeaways
- Why enterprise AI projects struggle with data connectivity and how MCP addresses this challenge.
- Understanding the Model Context Protocol, its architecture, and why it is becoming the open standard for enterprise AI integration.
- How to connect AI agents to Snowflake and Databricks using MCP with enterprise-grade governance.
- A live demonstration of AI agents analyzing transactions, detecting fraud patterns, and searching customer complaints through MCP.
- How to enforce enterprise security, governance, and controlled tool access in AI workflows.
- Practical approaches to integrating MCP into your existing enterprise data platform.
