On May 27, 2026, Snowflake had one of the busiest days in its company history. It reported a strong Q1 FY2027 earnings beat, announced a $6 billion multi-year commitment to Amazon Web Services, and disclosed plans to acquire Natoma, an enterprise Model Context Protocol (MCP) governance platform. Taken together, the announcements mark a clear pivot: Snowflake is no longer positioning itself as a data warehouse. It wants to be the control layer for the agentic enterprise.
The Numbers First
Snowflake’s Q1 FY2027 product revenue came in at $1.33 billion, up 34% year-over-year and above Wall Street’s consensus estimate of $1.30 to $1.31 billion. Adjusted earnings per share were $0.39, well ahead of the $0.32 expected. The company raised its full-year FY2027 product revenue guidance to $5.84 billion, implying 31% growth. Shares surged roughly 37% in after-hours trading.
The results matter beyond the numbers. Snowflake had been under pressure to show that its pivot toward AI wasn’t just a story. Q1 showed customers are actually spending.
The $6 Billion AWS Bet
Alongside earnings, Snowflake announced a five-year, $6 billion commitment to AWS infrastructure, its largest cloud deal ever. The spending covers Amazon’s Graviton chips, which are ARM-based CPUs built for general-purpose compute, alongside GPU-accelerated infrastructure for AI workloads.
This isn’t just a procurement agreement. The deal is structured to deepen joint development on generative AI and agentic AI, with particular focus on reducing friction between Snowflake’s data platform and the growing number of AI services running on AWS.
The reasoning is practical. As enterprise AI shifts from retrieval-based chatbots toward autonomous agents that take actions, the computational profile changes. GPUs handle reasoning and model inference, but CPUs handle the orchestration, routing, and workflow execution that agents generate at scale. Snowflake’s customers doubled their AWS spending to $2 billion in calendar year 2025. That trajectory explains the commitment.
CEO Sridhar Ramaswamy put it directly: “AI is fundamentally reshaping how work gets done, and Snowflake is at the center of the transformation.”
The Natoma Acquisition
The third announcement was the one that tells you where Snowflake is actually heading. The company signed a definitive agreement to acquire Natoma, a startup building enterprise MCP governance infrastructure.
MCP, the Model Context Protocol developed by Anthropic, has become the de facto standard for connecting AI agents to external tools, APIs, and data sources. The problem is that as MCP adoption grows inside enterprises, it creates a governance vacuum. Agents are calling tools across systems with minimal audit trails, inconsistent permissions, and no central policy enforcement.
Natoma solves this with a centralized MCP gateway that enforces identity, policy, and audit at the individual tool-call level. Before an agent can take an action, Natoma’s platform verifies who requested it, what permissions apply, and whether the action falls within policy. It already operates inside some of the world’s largest enterprises.
Ramaswamy framed the acquisition sharply: “Agents don’t just need access to data. They need the right context, permissions, and policy guardrails to operate safely inside the enterprise. Snowflake has long served as the governed data foundation for enterprises, and with Natoma’s expertise in identity governance and privileged access management, we can extend that trust layer to AI-driven actions and workflows.”
Financial terms were not disclosed. The deal is subject to customary closing conditions and was announced at Snowflake Summit 26.
What This Means for Business
If you run a business using AI agents or are planning to, these three announcements carry real implications.
Your data layer is becoming your AI infrastructure layer. Snowflake’s bet is that wherever your trusted business data lives, that’s where your agents should operate from and be governed from. If your organization is already on Snowflake, the path to managed agentic AI just got clearer. If you’re not, the pressure to consolidate is growing.
MCP governance is becoming table stakes. The shift from AI assistants to autonomous agents introduces a class of risk that most businesses haven’t thought about: agents taking actions across systems without a human in the loop. Natoma’s model, which Snowflake is now folding into its platform, treats governance at the tool-call level rather than just the application level. This will matter when something goes wrong, and eventually something does.
The infrastructure race is deciding winners. The $6 billion AWS commitment is not a typical vendor contract. It signals that Snowflake sees AI-first infrastructure as a strategic moat, not a cost line. Companies that wait for this market to stabilize before committing to a data and AI platform are going to find themselves catching up.
Enterprise DNA’s Omni services help businesses navigate exactly these decisions: which platforms to commit to, how to structure AI governance, and where agentic automation creates the most leverage. If you’re mapping out your AI infrastructure strategy for the next 12 months, these are the kinds of moves worth paying close attention to.