Mahesh Kumar

In this session, Mahesh Kumar of Acceldata runs a live simulation of what happens to enterprise AI as it leaves the lab and meets the real world: more agents, more places your data lives, more systems in the path. Set the conditions and watch the numbers you answer to - cost, reliability, speed - move in real time. The surprise is how they move: these effects compound. As you add agents, platforms, and management systems, costs don't rise in step, they outpace the scaling and keep climbing. The proof runs live, not on a slide. You'll point the model at your own environment, then see whether different architecture choices keep the costs compounding or bring them back down.

Data teams waste hours on reactive, manual work, patching pipelines, chasing quality issues, and keeping governance current. Join us for a demo of an agentic data system reducing manual intervention across quality and governance workflows, learn how probabilistic and deterministic approaches improve data reliability and pipeline efficiency, and discover how to build AI-ready data products using MCP to accelerate AI and analytics outcomes.

Legacy data tools weren’t built for the AI era. Agentic Data Management replaces static rules and siloed platforms with intelligent agents that monitor, reason, and act—automating quality, governance, and lineage at scale. Discover how data leaders are shifting from manual firefighting to autonomous control, powering faster, trusted, and scalable data for AI and analytics. - See a live demo of an agentic system in action - Learn how probabilistic and deterministic approaches work in concert - Explore how to build intelligent data products using the MCP protocol