Snowflake and Anthropic are teaming up to push AI projects from pilot to production

Snowflake and Anthropic have announced an expansion of their strategic partnership aimed at driving broader AI adoption for enterprises.

According to the duo, the move comes as both report increased demand from enterprises looking to move AI from pilot projects into full production.

The initial partnership, signed in December last year, saw Anthropic’s Claude models integrated within Snowflake’s Cortex AI platform.

This allowed customers to use Claude with Snowflake data through the platform, helping to streamline access, support agent deployments, and provide users with a range of safety and governance controls.

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So far, the partnership has proved beneficial for customers and highlights a growing demand for AI that “works directly on their governed data, not in isolated systems”, according to Christian Kleinerman, Snowflake’s EVP of product.

“We’re seeing strong demand across our AI products, with Snowflake Cortex Code becoming the fastest growing product in Snowflake’s history,” he said.

“Together with Anthropic, we’re helping organisations move from experimentation to product faster and laying the foundation for the agentic enterprises, where AI, data, and governance work together to drive real business outcomes.”

Snowflake and Anthropic target deeper integration

Building on this, the duo has expanded access to Claude within the Cortex AI platform, now enabling enterprises to build AI agents and applications directly on in-house data.

The Cortex Agents framework, for example, allows customers to build custom agents spanning a range of use-cases, including customer support, data analysis, and core operations.

Elsewhere, Claude will also now power Snowflake Cortex Code and Snowflake Intelligence, the companies confirmed.

According to Snowflake, a host of customers, including Block, have recorded marked improvements using Claude across its core platforms.

Block engineering lead Arnaud Weber said the company has built an “AI-native operating layer” which connects data across different brand ecosystems, spanning CashApp, Afterpay, and Square.

Weber noted this has helped bolster security, data governance, and developer efficiency.

“By combining Anthropic Claude with Snowflake’s governed data platform, our teams can investigate compliance and security issues in real-time, trace controls and requirements, surface operational insights, and automate workflows grounded in trusted enterprise data,” Weber commented.

“Developers are also using Snowflake Cortex Code to build and operationalize these capabilities directly within Snowflake, creating a unified layer where AI can move seamlessly from analysis to action.

“This approach helps us reduce friction across investigations and decision-making, while maintaining the governance, performance, and scalability needed to apply AI responsibly across financial services and commerce.”

Moving from pilot to production

The continued collaboration between Anthropic and Snowflake targets a recurring pain point for enterprises - mainly the inability to move projects out of the pilot stage and into full production.

Research from Google as far back as 2024 identified this as a key challenge for enterprises dabbling in AI adoption, describing the trend as “pilot purgatory”.

Crucially, the situation has remained much the same over the last two years. Analysis from Informatica in January 2025 found just over one-third (38%) of companies had successfully transitioned AI projects into full production, for example.

This problem has been further exacerbated with the advent of agentic AI, with integration of agents proving far more complicated. Research from Dynatrace in January this year, for example, found around half of AI agent projects are still stuck in proof of concept (PoC) stages.

A key factor here, the study noted, lies in the fact enterprises fail to efficiently govern agents, which prevents them from scaling projects safely. More than half (52%) of IT leaders highlighted concerns around security, privacy, and compliance as key hurdles.

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