Snowflake Ventures shifted how it invests in AI startups - here’s what it looks for now
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Snowflake Ventures, the corporate VC arm of AI data cloud company Snowflake, is redefining what it looks for in AI companies. For Harsha Kapre, director at Snowflake Ventures, the question is no longer whether a startup can demonstrate an impressive AI capability, but whether customers are willing to put it to work. "We're more focused and disciplined around backing companies that can demonstrate real customer outcomes, not just compelling AI demos," says Kapre. The shift reflects a broader change in enterprise technology: after the initial rush to experiment with generative AI, buyers increasingly want evidence that new tools can improve workflows, reduce costs, strengthen governance or generate revenue. That has implications for what Snowflake Ventures chooses to fund. The investor is prioritising startups with meaningful usage, deep potential integration with Snowflake and evidence that customers are taking products into production. It is particularly interested in the infrastructure needed to make AI usable at scale, including governance, observability and industry-specific applications. "Financial returns matter, but the core focus is whether a company helps customers get more value from their data and AI investments on Snowflake." Like most corporate investors, Snowflake Ventures is not measuring success primarily through the conventional venture capital metric of...
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