At Snowflake Inc.’s annual conference in June, the company introduced several platform updates designed to expand interoperability, improve performance and reduce operational cost. The focus of these enhancements was artificial intelligence and how Snowflake intends to help customers embrace the agentic revolution.

Christian Kleinerman, EVP at Snowflake, talks with theCUBE about platform updates.

“It’s the ability to leverage organizations’ data to effectively drive productivity through AI, through AI agents and through agentic applications,” said Christian Kleinerman (pictured), executive vice president of product at Snowflake. “That is, in many ways, the core of what we’re enabling for organizations here at Snowflake Summit, and it starts with helping organizations make their data be AI-ready, whether it’s structured or unstructured data.”

Kleinerman spoke with theCUBE’s Dave Vellante and George Gilbert at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio, and they discussed recent new products from Snowflake and the company’s evolving platform role. (* Disclosure below.)

Platform updates for unstructured data

A key focus for Snowflake has been providing tools for unstructured data. The company unveiled new additions in June to its Cortex portfolio, which expanded capabilities to query data across diverse formats, including unstructured image, audio or long-form text files, according to Kleinerman.

“Unstructured is on a tear, enabled and lit up by AI,” Kleinerman said. “Cortex Analyst is our ability to do text-to-structured data. Cortex Search is our hybrid search capability that does semantic search and keyword search to do retrieval on unstructured data and to orchestrate it amongst those two multiple data sets of … Cortex agents.”

Snowflake is also seeking to improve the ease and speed of structured and unstructured data integration. The company announced Openflow, a managed service that’s designed to reduce the time and effort spent wrangling ingest pipelines while supporting batch and streaming workloads. Openflow can be implemented in multiple environments, according to Kleinerman.

“We want to help organizations with the entire life cycle of data,” Kleinerman said. “How about if we help from the very beginning, the creation of that data set? That’s where Openflow has two deployment models. One is typical Snowflake; it’s Snowflake-managed resources. It’s in the cloud, but there’s also BYOC, bring your own cloud, which can be deployed in the customer’s virtual private cloud.”

Snowflake’s role in the enterprise is evolving from providing data management tools to serving as a platform on which other businesses can be built. Kleinerman cited Capital One Financial Corp. as an example, which recently announced two new features, built on the Snowflake platform, for its enterprise B2B Capital One Software division.

“When we talk about the AI data cloud, it’s not just some pretty words to say database, it’s truly the insight of a technology platform,” Kleinerman said. “When you see the folks like Capital One that took what they had built for Snowflake and decided to turn it into a business, that’s the blurring of roles. We do believe that our role is to enable that collaboration, enable that facilitation, which is common data, common governance, common semantic models and metadata.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Snowflake Summit:

(* Disclosure: TheCUBE is a paid media partner for Snowflake Summit. Neither Snowflake Inc., the primary sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE