#327 Baris Gultekin: The Next Phase of AI - Agents That Understand Your Company's Data
This episode is sponsored by Modulate. Most voice AI focuses on transcription. Velma takes it further by actually understanding conversations, analyzing tone, timing, stress, and intent using its Ensemble Listening Model architecture. Explore the live preview: https://preview.modulate.ai/
Baris Gultekin, Head of AI at Snowflake, breaks down how enterprise AI is actually being built, deployed, and scaled today. From running AI directly inside governed data environments to enabling natural language access across entire organizations, this conversation explores the shift from experimentation to real-world impact.
You'll learn why Snowflake's core philosophy centers around bringing AI to the data, how data agents are transforming decision-making across teams, and what it takes to build trustworthy AI systems with governance, guardrails, and high-quality retrieval at the core.
Baris also shares how leading companies are already saving thousands of hours through AI-driven automation, why culture and leadership determine AI success, and what the future looks like as agents move from pilots to full-scale production.
If you want to understand where enterprise AI is actually headed and what separates hype from real execution, this episode breaks it down.
(00:00) The Evolution of Snowflake AI
(01:40) Baris Gultekin: Background & AI Mission
(02:59) Why AI Must Run Next to Data
(04:29) Inside Snowflake's AI Infrastructure
(09:08) Model Choice vs Product Layer Strategy
(12:16) Building Trust: Governance, Guardrails & Quality
(16:01) How Enterprise Agents Are Built & Orchestrated
(20:10) AI Adoption Across the Entire Organization
(24:39) Reasoning vs Retrieval: What Matters More
(27:43) Real Use Case: Faster Decision-Making with AI
(31:44) AI as a Co-Pilot for Leaders
(36:52) Preparing Data for AI at Scale
(38:46) What the AI Data Cloud Really Means
Snowflake VP of AI Baris Gultekin on Bringing AI to Data, Agent Design, Text-2-SQL, RAG & More
Baris Gultekin, VP of AI at Snowflake, explains how “bringing AI to the data” is reshaping enterprise AI deployment under strict security and governance requirements. PSA for AI builders: Interested in alignment, governance, or AI safety? Learn more about the MATS Summer 2026 Fellowship and submit your name to be notified when applications open: https://matsprogram.org/s26-tcr. He shares the importance of bringing AI directly to governed enterprise data, advances in text-to-SQL and semantic modeling, and why high-quality retrieval is foundational for trustworthy AI agents. Baris also dives into Snowflake’s approach to agentic AI, including Snowflake Intelligence, model choice and cost tradeoffs, and why governance, security, and open standards are essential as AI becomes accessible to every business user.
LINKS:
AWS' Automated Reasoning checks
Sponsors:
MongoDB:
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Serval:
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MATS:
MATS is a fully funded 12-week research program pairing rising talent with top mentors in AI alignment, interpretability, security, and governance. Apply for the next cohort at https://matsprogram.org/s26-tcr
Tasklet:
Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai
Claude
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CHAPTERS:
(00:00) About the Episode
(03:02) Snowflake 101 and AI
(09:25) Text-to-SQL and semantics
(19:10) RAG, embeddings and models (Part 1)
(19:17) Sponsors: MongoDB | Serval
(21:02) RAG, embeddings and models (Part 2)
(32:23) Bringing models to data (Part 1)
(32:29) Sponsors: MATS | Tasklet
(35:29) Bringing models to data (Part 2)
(51:14) Designing enterprise AI agents
(58:35) Trust, governance and guardrails
(01:07:14) Agents and future work
(01:15:33) Platforms, competition and value
(01:26:04) Enterprise models and outlook
(01:40:00) Outro
PRODUCED BY:
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Snowflake's Baris Gultekin on Unlocking the Value of Data With Large Language Models - Ep. 231
Snowflake is using AI to help enterprises transform data into insights and applications. In this episode of NVIDIA’s AI Podcast, host Noah Kravitz and Baris Gultekin, head of AI at Snowflake, discuss how the company’s AI Data Cloud platform enables customers to access and manage data at scale. By separating the storage of data from compute, Snowflake has allowed organizations across the world to connect via cloud technology and work on a unified platform — eliminating data silos and streamlining collaborative workflows.