"Customers use Snowflake to store nearly any operational data, including financial records such as ERP data, CRM records including tickets and transactions, IoT and sensor data, API calls and responses, website user activity, and even content such as PDFs, document files, images, videos, and audio. Cortex AI allows users to pick the model of their choice, now including Gemini, to process that glacier of information using an LLM to get business insights."
""By running Gemini natively in Snowflake, customers can use Gemini models across all supported clouds via cross-region inference, regardless of whether their Snowflake environments run on AWS, Azure, or Google Cloud," Dwarak Rajagopal, VP of AI Engineering and Research at Snowflake, told The Register via email. Snowflake's phased rollout is part of its AI model-agnostic strategy, which he said should ensure customers can use best-in-class models across the Cortex stack without re-architecting data or workflows."
Snowflake integrates Google's Gemini into Cortex AI to provide customers access to a foundational model inside their Snowflake data environments across supported clouds. Snowflake stores nearly any operational data, including ERP, CRM tickets and transactions, IoT and sensor data, API calls, website activity, and content such as PDFs, images, videos, and audio. Cortex AI enables users to choose models, now including Gemini, to process that data with LLMs for business insights. Running Gemini natively supports cross-region inference across AWS, Azure, and Google Cloud without re-architecting data. The approach follows a model-agnostic strategy, supports multiple LLM providers, and uses a consumption-based pricing model where customers pay for actual usage.
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