Enterprises have often dreamed about AI systems that can reason across their most sensitive data, execute multistep tasks, and explain their logic while remaining inside a highly governed environment.
Snowflake and Anthropic are betting they can finally crack the code.
Through a multiyear, $200-million expansion of their agentic AI partnership, the companies plan to deliver an operational “control plane” that uses Anthropic’s latest Claude models, such as Sonnet and Opus 4.5, to power enterprise intelligence. The announcement landed alongside Snowflake’s Q3 earnings for fiscal year 2025, which showed the company maintaining strong momentum. Snowflake reported $1.21 billion in revenue, up 29% year over year, driven by $1.16 billion in product revenue. The company now operates at a $100 million AI run rate (year to date) while adding a record 615 new customers.
But as the race to dominate enterprise agentic AI accelerates, not everyone is convinced that Snowflake’s momentum guarantees staying power. “Snowflake is still in the early innings of seeing if the traction will stick,” says William Falcon, founder and CEO of Lightning AI. “For a database like Snowflake, they’ve hopefully learned from others’ mistakes and invested in Anthropic to try and avoid similar problems.”
That skepticism frames what makes Snowflake’s approach so interesting. Instead of treating AI as an external service that companies must funnel their data toward, the company wants the intelligence layer to reside where the data already lives. Its philosophy is to “bring AI to the data.”
“By deeply integrating Claude into Snowflake Intelligence and Cortex AI, we’ve collapsed that sprawl into a single governed environment where the model runs directly where a company’s data already lives, securely with full business context and without ever moving that data or introducing risk,” says Vivek Raghunathan, senior vice president of engineering at Snowflake.
The hallmark of this collaboration is a new class of AI agents capable of multistep reasoning on governed corporate data through Snowflake Intelligence, the company’s enterprise intelligence agent powered by Claude Sonnet 4.5. Under the hood of Snowflake Intelligence sits Cortex Agents, the Snowflake Horizon Catalog, and a layer of semantic models.
Analysts can ask complex questions in natural language, developers can build intelligent agents without stitching together infrastructure, and business teams can get deep insights with citations and traceability. In practice, the integration means a business user can ask a natural-language question, such as “What is driving churn in our Northeast customer segment?” and Claude will determine which datasets are relevant, write and execute the SQL, and explain how it arrived at its conclusion.
In highly regulated industries such as healthcare, financial services, or life sciences, that combination of deep reasoning with end-to-end governance is especially transformative.
“In regulated environments, ‘here’s the answer’ isn’t enough. You need ‘here’s how I got there’,” says Katelyn Lesse, head of API at Anthropic. In areas like financial reconciliation, companies routinely juggle data from disparate systems that rarely align cleanly, with exceptions that demand human judgment. Lesse noted that earlier approaches either overlooked this nuance or relied so heavily on manual review that any promised efficiency gains disappeared. “Claude can work through those discrepancies and flag where it’s uncertain, which is just as important as getting the answer right.”
