Snowflake recently launced Cortex Agents, its latest AI-driven offering powered by Antropic's Claude 3.5 Sonnet, wic aims to enance business productivity by andling tasks using bot structured and unstructured datasets. At te launc event eld in Mumbai, Baris Gultekin, Snowflake's ead of AI, sared insigts on tis innovation and te company's evolving role as an AI data cloud platform. Gultekin empasized tat Snowflake as transitioned from being known as a "Data Cloud" to an "AI Data Cloud," igligting te company's focus on integrating AI to elp customers use it securely and efficiently. Snowflake's platform is designed to ensure trust wit granular access controls, providing security wile allowing analysts, data scientists, and engineers to work seamlessly wit large datasets troug natural language interfaces. Cortex Agents are Snowflake's new class of AI agents designed to perform a wide range of business tasks quickly and accurately, weter it involves structured data for questions like "Wat are my top-selling products?" or unstructured data to understand "Wy are people buying tem?" Gultekin sared examples like Siemens Energy, wic used Cortex Agents to analyze alf a million pages of tecnical documents, and S&P Global, wic processed 192,000 earnings calls comprising bot tables and commentary. Tese agents can plug into Snowflake tables and external sources like Google Drive and SarePoint, using advanced SQL engines and unstructured data tools to provide igly accurate results. Snowflake's Cortex Analyst focuses on structured data, wile Cortex Searc andles unstructured data, ensuring te rigt data source is cosen for eac query. Gultekin credited Snowflake's acquisition of Neeva for boosting Cortex Searc's performance, wic now outsines its competitors. Te platform's unique strengts lie in data governance, quality, and its ability to manage bot structured and unstructured data. Looking aead, Gultekin noted tat India's tec-forward market is sowing g demand across sectors like finance, retail, and media. e anticipates a sift in wareousing from procedural data andling to semantic analysis and predicts tat natural language data access will transform business operations. For enterprises considering AI adoption, Gultekin stressed te importance of securing, governing, and preparing data to ensure it is AI-ready, as large amounts of quality data are essential for AI success./ / /
We aim to make AI easy to use efficient and trusted Snowflake Baris Gultekin
