Vipin Kataria

Senior Lead Architect (Data/ML) Picarro Inc

Vipin Kataria is an IEEE Senior Member and Distinguished Fellow with 21+ years of experience in enterprise cloud platforms, machine learning, and AI systems. At Picarro, he designs cloud data solutions and ML-driven analytics for environmental monitoring, processing real-time IoT sensor data for Fortune 500 companies. His career spans Intel Corporation, Amazon, Aricent Technologies, and TCS, where he built scalable solutions across hardware, cloud, and enterprise domains. A sought-after speaker, Vipin has presented at DSS Miami, IEEE conferences, and the Applied AI Summit. As Chapter Lead for AI Collective's South Bay Chapter, he guides a global community of 100,000+ AI practitioners, fostering collaboration and knowledge sharing. He actively contributes to the AI research community as an author, peer-reviewer, and judge for international AI awards and hackathons, helping evaluate breakthrough innovations. Based in the San Francisco Bay Area, he continues advancing cloud architecture, machine learning, and IoT technologies through industry practice and thought leadership.

Monday, June 8, 2026: Workshop Day

11:10 AM Workshop #2: Data Readiness and Pitfall Prevention for Agentic AI: From Audit to Action

Walk through the critical steps of preparing enterprise data for successful agentic AI deployment, while spotlighting common pitfalls to avoid. You’ll learn how to audit existing data silos, assess data quality, and develop actionable plans to unify and ready your data foundation. Through interactive discussions and real-world case studies, explore frequent challenges such as undocumented processes, hidden biases, and data inconsistencies and discover practical strategies to mitigate these risks. Leave with a clear roadmap to build a robust, trustworthy data environment that empowers autonomous agents and drives sustainable AI value.

Key Takeaways:

Techniques for auditing and consolidating siloed enterprise data
Identification and mitigation of common data pitfalls in AI projects
Strategies to document and standardize data and decision frameworks
Approaches to detect and address hidden biases and quality issues
Actionable roadmap for ongoing data governance and improvement

Check out the incredible speaker line-up to see who will be joining Vipin.

Download The Latest Agenda

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