Subvolts take Enterprise AI needs governance. Snowflake VP explains how to bring AI to your data securely. Jan 14, 2026 - Developers
- Learn about building trustworthy AI agents and integrating them with governed enterprise data using Snowflake.
- Business
- Understand how to deploy AI securely within your organization, focusing on data governance and accessibility for users.
This interview provides practical insights from a major cloud data platform on enterprise AI deployment challenges and solutions.
Snowflake VP of AI Baris Gultekin on Bringing AI to Data, Agent Design, Text-2-SQL, RAG & More
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From Subvolts
Summary and analysis by Subvolts editorial, AI-assisted.
Snowflake VP of AI Baris Gultekin discusses bringing AI directly to governed enterprise data. He covers advances in text-to-SQL, semantic modeling, and the foundational role of high-quality retrieval for trustworthy AI agents. Gultekin also details Snowflake’s approach to agentic AI, including model choice, cost tradeoffs, and the necessity of governance, security, and open standards for broad business user accessibility.
Imagine bringing smart computer helpers directly to your company's private information, safely. This episode explains how to do that, making AI useful for businesses without risking sensitive data. It covers making AI understand questions and give reliable answers.
This episode offers insights into deploying AI within enterprise constraints, focusing on data security and governance. It's for AI builders and business leaders navigating the practicalities of AI integration. The discussion on agent design and trustworthy AI connects to ongoing work at frontier labs like OpenAI and Google Gemini, who are also developing robust AI systems for enterprise use. Snowflake's emphasis on governance aligns with industry-wide efforts to ensure responsible AI deployment.
- HostNathan Labenz
- GuestBaris GultekinVP of AI, Snowflake
- Guest: Baris Gultekin, VP of AI at Snowflake
- Show: The Cognitive Revolution
- Length: 99 minutes
- Key Concept: Bringing AI to governed enterprise data
- Foundational Element: High-quality retrieval for trustworthy AI agents
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:
Sponsors:
MongoDB:
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MATS:
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Tasklet:
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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:
- Text-to-SQL
- Baris Gultekin
- Turning plain language questions into database queries.
- RAG
- Baris Gultekin
- Retrieval Augmented Generation; using external data to improve AI answers.
- Agentic AI
- Baris Gultekin
- AI systems designed to perform tasks autonomously.
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42 minQuestions people ask
- What is the core idea behind "bringing AI to the data"?
- It means deploying AI directly to governed enterprise data, ensuring security and compliance requirements are met.
- Why is high-quality retrieval important for AI agents?
- High-quality retrieval is foundational for building trustworthy AI agents that can reliably access and use information.
Page generated Oct 19, 2026. Summaries are Subvolts' own; the audio, artwork and notes belong to Erik Torenberg, Nathan Labenz.