From Data Searching to Business Solving: How Alation's Chat with Your Data Transforms Enterprise AI

The enterprise data landscape has reached a tipping point. While organizations have invested heavily in BI tools and infrastructure, business users still struggle to get fast, accurate answers to critical questions.  The numbers tell a sobering story: according to recent research from MIT, 95% of enterprise AI initiatives fail to deliver meaningful value, with the most common user complaint being that AI systems "don't learn from our feedback." 

The promise of AI-powered analytics has largely fallen short, with generic language models producing unreliable results that enterprises simply cannot trust.

To address these challenges, Alation has launched Chat with Your Data, a solution specifically designed to overcome the learning gaps and static limitations that plague enterprise AI. This new capability was made possible through our recent acquisition of Numbers Station, a pioneer in applying generative AI to data workflows. By combining Alation’s metadata-rich catalog with Numbers Station’s advanced AI technology, we’ve created a “better together” solution that delivers trusted, context-aware AI for the enterprise.

In a recent webinar, the team demonstrated how metadata-aware agents can deliver more accurate answers, grounded in the enterprise’s own data context. This marks a fundamental shift toward AI systems that improve with usage while maintaining enterprise-grade governance and transparency.

The enterprise data problem: Why search-based discovery falls short

"The way that people want to use data has fundamentally changed," explained Meghan Brill, senior product marketing manager at Alation. "We're really moving from this out-of-date, search-based discovery into AI-powered answers. Nobody wants to search through endless dashboards and spreadsheets or reports anymore, or wait on a data team to get them answers."

Business users today expect the seamless experience of consumer AI tools like ChatGPT. But enterprise AI struggles to deliver at the same level—largely because structured data brings unique challenges that generic models weren’t built to solve. 

The root cause? Most AI solutions treat enterprise data like unstructured text. They ignore the organizational context that gives it meaning: the metadata, business definitions, and governance policies, which all live in the data catalog.

“The problem is that metadata is super messy and nobody wants to deal with it,” Brill elaborated. ”But that’s where Alation is different. We make metadata manageable, discoverable, and actionable. And instead of locking customers into a single stack, we help unify context across what they already use. That’s how you make AI work safely, transparently, and at scale.” 

How metadata improves AI accuracy

This isn’t just theory—it’s been validated in research. In a study with Numbers Station using production data from global real estate firm JLL, the team compared AI outputs with and without metadata context. The difference was striking; accuracy improved by nearly a third when grounded in metadata, or what the team calls a contextual knowledge layer:

Why is this the case? Metadata provides the schema, relationships, and definitions that language models inherently lack. Without it, results are often incomplete—or flat-out wrong. With it, AI becomes capable of producing results that enterprise leaders can actually trust.

By packaging metadata into data products, Alation delivers a foundational knowledge layer atop which trusted AI can be built for the enterprise. 

Using data products and metadata to build trusted AI

Ines Chami, co-founder of Numbers Station and Director of Product at Alation, walked through a demo of Chat with Your Data, which is embedded in the data products marketplace.

She explained that data products act as curated, context-rich bundles of enterprise data—complete with ownership, version control, and business definitions. Instead of sifting through conflicting dashboards, users interact with these trusted products directly through chat.

For example, in a retail use case, a data product might bring together sales, customer, and geography tables with defined relationships. Users can then ask natural language questions like “What are the top-selling coffee products?” and the system generates accurate SQL queries grounded in metadata from the catalog.

Because metadata drives the joins, lineage, and definitions, the results aren’t just more accurate—they’re traceable. Users can drill back to the catalog, review the SQL, and understand exactly which columns and tables produced the answer.

And it doesn’t stop with text. Chami also demonstrated how agents can instantly visualize results—such as generating a bar chart for a CEO presentation—with full customization options. This makes self-service analytics not only possible, but trustworthy.

What makes Alation Chat with Your Data unique?

Next, Chami offered a technical deep dive into how Chat with Your Data works—and why it stands apart from other AI solutions on the market. She highlighted four core capabilities that customers value most: accuracy, integration, transparency, and governance.

Accuracy in AI analytics: Why context is key

Working with structured data requires precision. As Chami explained, “Text-to-SQL and working with structured data is extremely hard. We need to have at least 90% or even more accuracy on these systems to get to production. And a lot of solutions don’t provide that.”

The difference comes down to context. Without metadata, AI agents may rely on misleading or outdated columns. For example, a naïve query might count customers flagged as “active” in a database column—but if the business defines “active” as customers who placed an order within the past month, the results are incorrect.

To solve this, Alation captures and stores organizational logic in data products, which act as knowledge containers enriched with metrics, definitions, and business rules. Rather than starting from scratch, the system ingests knowledge from dashboards, glossaries, and SQL queries across the catalog, then continuously improves through user feedback.

The result is a continuously evolving knowledge layer that powers agents to generate SQL grounded in business context—delivering accuracy that improves with every iteration.

Integrated: Works across your data stack

Most enterprises run on a mix of platforms. Unlike point solutions limited to a single ecosystem, Chat with Your Data is designed to span them all.

As Chami noted: “You may have some data in Snowflake, some in Salesforce, some in Databricks, or dashboards in Power BI. You don’t want to have to just use one platform to leverage AI—you want to leverage AI across everything.”

Alation makes this possible with 110+ native connectors, ensuring metadata and business context flow seamlessly across the entire stack.

Transparent, explainable AI: Full lineage and SQL visibility

Trust is critical for enterprise adoption. That’s why every answer generated in Chat with Your Data comes with full lineage and SQL visibility.

Agents explain how queries were generated, show the SQL behind the scenes, and trace results back to specific columns, tables, and metrics in the catalog. This ensures users can rationalize results, resolve conflicting dashboards, and maintain confidence in the outputs.

Governed: Enterprise-grade access control

Finally, governance is non-negotiable for enterprise-scale AI. Alation enforces granular access controls to ensure users only see data they are authorized to see. For example, if a global company sells subscription-based insights by region, a European customer should never see U.S. data—even if both are using the same chat interface.

To support this, Alation offers row-level, user-level, asset-level, and marketplace-level controls, all enforced at the database level and surfaced through the chat interface.

Taken together, these four capabilities—accurate, integrated, transparent, and governed—make Chat with Your Data not just another AI assistant, but a production-ready analytics solution enterprises can trust.

Chat with Your Data brings trust to enterprise AI

Alation’s Chat with Your Data marks a turning point for enterprise AI. By grounding answers in metadata-rich data products, it delivers results that are not only faster and easier to access but also accurate, transparent, and governed. Unlike generic language models, Chat with Your Data learns and improves with use, adapting to the unique context of each organization’s data. The result is AI that business users can finally trust—helping teams move beyond the hunt for information to making confident, data-driven decisions at scale.

Curious to see how Chat with Your Data can help you bring trust to AI? Book a demo with us today.