Alation Acquires Numbers Station: Enabling AI to Understand Structured Data at Scale

I am thrilled to announce Alation's acquisition of Numbers Station AI, marking an exciting new chapter for Alation, our customers, and the broader market.

Why this matters: Unlocking AI's enterprise potential 

The most critical enterprise data—like customer records and financial transactions—is highly structured and precise. Ironically, it’s this precision that makes scaling AI in real-world use cases difficult for organizations. You can ask an LLM the same question three times and get three different answers; you would never want that when asking about costs for your last quarter.  Beyond that, models interpret structured data poorly and get confused if the data is sufficiently complex or lacks sufficient context.

To scale agents in the enterprise, we still have to solve the problem of getting stochastic and error-prone LLMs to talk to deterministic and precise databases. This requires innovations in gathering context and building agents.   

This is where Numbers Station comes in.  Founded by Stanford researchers Chris Aberger, Ines Chami, Sen Wu, and Professor Chris Ré—pioneers in applying foundation models to data workflows—the team wrote the first academic paper demonstrating how LLMs can be used to wrangle structured data. Long before the AI hype cycle, they were building practical agents and putting them in production.

At Alation, we’ve admired their work for years. We reference them in Slack. We share customers and a vision. When we started collaborating, it quickly became clear: our technologies and philosophies are powerfully complementary. The timing was perfect. 

Pioneering AI for data intelligence

Today’s AI agents hold enormous promise—but they face real challenges in enterprise environments. Hallucinations, lack of context, and opaque decision-making limit their reliability. Agents need the right information to function, and metadata is at the center of their ability to reason and make good decisions. For this reason, scaling AI to tackle high-stakes business processes requires a foundation of trusted metadata, governed data products, and deep contextual understanding.

With Numbers Station’s powerful AI agents and Alation’s metadata intelligence, we’re tackling these challenges head-on. For customers, the result is dramatically enhanced power:

• Precision Meets Flexibility: Imagine financial services firms developing credit models that can adapt to changing market conditions and regulatory requirements. By combining AI's adaptability with rigorous data governance, businesses can confidently explore new insights while maintaining compliance and data integrity across complex operations.

• Mission-Critical Reliability:  When a commercial real estate organization needs to have accurate data to decide whether and how to renew their leases, AI can make clear and actionable recommendations around what the agent should do and how they should work with customers to craft the best possible outcome.

• Accelerated Innovation: A retail company that previously spent months developing customer segmentation models will soon be able to prototype, test, and deploy sophisticated data-driven workflows in days. By providing AI agents with the context they need to understand structured data assets, we remove the barriers that have historically prevented enterprises from realizing AI's full potential

When you combine Numbers Station’s agent technology with Alation’s trusted data ecosystem, the barriers to enterprise AI fall away – unlocking faster decisions, smarter operations, and incredible business outcomes.  

Powering AI with data products

This acquisition positions Alation at the forefront of AI-powered data product development. Foundation models have shown remarkable effectiveness, yet they often falter when confronted with the precision, compliance, and contextual depth required by mission-critical enterprise applications—the very environments where they stand to deliver the most value.  

AI-ready data products are the bridge. They provide the structure, governance, and semantic clarity that foundation models need to interpret enterprise data accurately and act reliably. But building these products isn’t as simple as organizing metadata into neat tables—it requires deep technical experience and problem-solving to ensure models can reason with structured data effectively. The Numbers Station team has already walked this path.

Their technology delivers the critical capabilities needed to operationalize this vision:

• Natural language interfaces that enable intuitive human-AI collaboration

• Enterprise-specific context awareness to ensure relevance and accuracy

• Compositional reasoning to support complex, multi-step data workflows

When combined with Alation’s industry-leading metadata foundation, these capabilities empower organizations to build differentiated, AI-powered data products—solutions that are proprietary, precise, and impossible for competitors to replicate.

A future without limits

Numbers Station further enables Alation to move data management from the data suppliers to the point of demand. We envision a future in which non-technical domain experts can direct sophisticated data operations through natural language interfaces, breaking down technical barriers that have historically siloed data knowledge. We see a world where organizations can consolidate multiple specialized tools into unified AI-driven platforms, dramatically reducing operational complexity while improving outcomes.

We have so much to show and tell you about over the coming months and couldn't be more excited to do so. This isn't just an acquisition—it's a catalyst for transformation, and we invite you to join us on this extraordinary journey.

Learn more by reading the press release: Alation Acquires Numbers Station to Unlock a New Era of Agentic Workflows.