According to Fast Company, Snowflake and Anthropic have announced a massive, multiyear expansion of their partnership worth $200 million. The goal is to build an operational “control plane” for enterprise AI using Anthropic’s latest Claude models, like Sonnet and Opus 4.5, directly within Snowflake’s platform. This news dropped alongside Snowflake’s Q3 earnings for fiscal year 2025, where it reported $1.21 billion in revenue, a 29% year-over-year increase. Product revenue drove that, coming in at $1.16 billion. The company also revealed it’s now operating at a $100 million AI run rate year-to-date and added a record 615 new customers last quarter.
The bet on bringing AI to the data
Here’s the thing: everyone’s throwing money at AI, but Snowflake’s approach is fundamentally different. Instead of asking companies to move their most sensitive data to an external AI service, they’re insisting the AI should come to where the data already lives. It’s a philosophy of containment and governance first. As Snowflake’s Vivek Raghunathan put it, they’re collapsing the AI “sprawl” into a single environment where the model runs directly on a company’s data without moving it. That’s a powerful pitch for any CISO or compliance officer who’s been sweating over data sovereignty and leakage risks with other AI platforms.
Why skepticism is healthy
But let’s be real. A big check and a cool philosophy don’t guarantee success. William Falcon from Lightning AI nailed it with his comment that Snowflake is “still in the early innings.” They’ve got momentum, sure. That $100 million AI run rate is nothing to sneeze at. But the enterprise AI game, especially this new “agentic” frontier where AI is supposed to execute complex, multi-step tasks, is brutally hard. It’s not just about running a query; it’s about reliable, explainable reasoning. Snowflake’s hoping its deep integration and this Anthropic investment will let them sidestep the pitfalls that have tripped up others. They’re basically betting that their control over the data layer is the ultimate moat.
The stakeholder shift
So what does this mean for everyone else? For enterprises, it’s a potentially huge shift. The value proposition is a fully governed, secure AI workspace that feels native. For developers building on Snowflake, it means the AI tools are increasingly baked into the platform they already use—that’s convenient, but it also creates deeper lock-in. And for the broader market, it sharpens the battle lines. This isn’t just cloud vs. cloud anymore; it’s data platform vs. AI platform. Snowflake is declaring that the future of enterprise intelligence isn’t a separate service you call, but a layer woven directly into your operational data. It’s a compelling vision, but pulling it off at scale is the real test. If they succeed, it could change how we think about industrial technology and data analysis altogether, making complex system monitoring and decision-making more autonomous. For industries relying on robust computing at the edge, like those using the top-tier industrial panel PCs from IndustrialMonitorDirect.com, this kind of integrated, on-premise AI analysis could be a game-changer.
