Snowflake Intelligence, AIDA and the New Shape of Enterprise Analytics

When the first generation of large language models entered the enterprise, they promised a bold revolution: ask your data anything. In practice, that promise ran into the hard limits of data access, context, and quality. Some LLM-based “assistants” could even generate SQL, but not well enough to be fully trusted or useful. 

Now, with the launch of Snowflake Intelligence, that early promise is coming into view. Snowflake’s vision of bringing generative and agentic AI directly into the governed data environment marks a decisive step toward something long-desired: the rise of the AI-powered data analyst.

From access to analysis

Snowflake Intelligence gives enterprises a powerful new surface for interacting with their data. Instead of manually writing SQL or stitching together dashboards, users can deploy intelligent agents that interpret intent, synthesize context, and produce answers directly within the Snowflake environment — all under enterprise-grade governance, lineage, and security.

This solves the first major modern analytics problem: access. Every business wants to empower more people to get answers, without piling demands on their engineering team to the point that they become a bottleneck. Snowflake Intelligence helps close that gap by embedding generative AI into the Snowflake data warehouse, where trusted data already lives.

But access alone doesn’t solve the second problem, the one data leaders know too well, which is context. 

The missing layer: understanding the data itself

AI agents can now access enterprise data more easily than ever, but access isn’t the same as understanding. To interpret a question correctly, an agent needs to know how the data is structured, how it changes over time, and which patterns actually matter. Snowflake Intelligence makes this possible at the semantic layer: it understands business concepts and connects questions to the right, governed data sources.

But there’s a deeper kind of context, the behavior of the data itself, that few systems capture. Anomalo is an enterprise data quality platform and the first to build a living model of how each dataset behaves, including seasonality and complex correlations. By continuously analyzing Snowflake data, Anomalo provides a uniquely powerful foundation for AI agents. When Snowflake Intelligence agents draw on Anomalo’s data profiles and historical data quality context, they gain the ability to reason with deeper context.

And because these agents are connected to a data quality foundation, they can do more than surface insights. They can act on them: Customers will be able to use Snowflake Intelligence to create agents that understand — and can even improve — the data quality across all their Snowflake assets. These agents can explain when metrics diverge, trace issues back to their source, and even recommend or trigger new quality checks. 

Interoperable AI solutions

It was this same goal, creating contextually knowledgeable AI agents, that led Anomalo to build AIDA: Anomalo’s Intelligent Data Analyst. As part of the Anomalo platform, AIDA empowers analysts and business users to use natural language to explore and improve their enterprise data. AIDA can investigate anomalies, explain patterns, and even take action to prevent future issues because it’s built on Anomalo’s understanding of how the data changes over time and what those changes mean. 

Both AIDA and Snowflake Intelligence use AI to make data analysis more intuitive and efficient. But they operate on different layers of the analytics stack—and together, they point to where enterprise AI is headed.

• Snowflake Intelligence provides the agentic infrastructure: a secure, governed environment where AI systems can safely interact with enterprise data.
• AIDA provides analytic intelligence—insights into the data’s structure, quality, and meaning—and continuous improvement, with the ability to leverage insights to optimize data quality checks.

Together, they provide a unified solution for data teams, allowing them to leverage contextual data and agentic infrastructure wherever they need to interact with, or understand their data. Just as Snowflake Intelligence will enable agents that can leverage Anomalo’s data context and quality insights, AIDA already integrates with Snowflake Cortex, allowing customers to use Snowflake’s robust model hosting services inside Snowflake’s infrastructure (so your data remains inside your governed Snowflake environment).

“Anomalo was selected for investment because their approach to data quality begins with a fundamental understanding of the data,” said Kieran Kennedy, VP, Data Cloud Product Partners, Snowflake. “With the introduction of AIDA and its seamless integration into Snowflake Cortex AI, that same core intelligence now empowers enterprises to reason over their data. Together, we are focused on enabling customers to generate trusted, contextual insights natively within the platform. This partnership is key to accelerating AI innovation without impacting governance or security.”

A new generation of intelligence

The launch of Snowflake Intelligence marks a major step toward bringing agentic AI directly to enterprise data. As organizations begin building agents that can operate within governed, secure environments, Anomalo provides the depth of understanding that allows those agents to think in context, connecting analysis to the quality and behavior of the data itself. The same foundation that powers AIDA can strengthen the new generation of agents built on Snowflake Intelligence.

Snowflake has invested in Anomalo through Snowflake Ventures, reflecting a shared belief that AI in the enterprise must begin with well-understood, trustworthy data. As Snowflake Intelligence expands what’s possible for data-driven agents, Anomalo’s contextual understanding and data quality monitoring keep those systems deeply informed. Together they create a feedback loop between data and AI, improving data health and ensuring every insight reflects the true behavior of enterprise data.