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The enterprise data catalog market has undergone dramatic shifts in the modern gen AI era.
Traditional data catalogs served as static repositories where users searched for datasets and documentation. The market expanded to include data governance capabilities with many vendors branding the technology as data intelligence platforms.
Early AI enhancements to data catalog implementations promised to revolutionize data access, but often delivered inconsistent results that enterprises couldn’t trust for critical decisions.
Now, a new generation of metadata-aware AI agents promises to bridge this gap, maintaining business context across conversations and provide the accuracy levels enterprises demand.
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Alation, which is one of the largest independent data intelligence platform vendors and claims 40% of the Fortune 100 as its customers, has been steadily expanding its AI capabilities as the need for data has changed.
Today the company announced its latest set of AI capabilities with an enhanced data query capability it calls ‘Chat with Your Data’ that claims to improve answer accuracy by up to 30%.
The transformation of the data catalog market reflects a fundamental shift in enterprise expectations. Organizations no longer want separate systems for data discovery, governance and analysis. They demand unified platforms that democratize data access while maintaining the precision required for business-critical decisions.
“I think generative AI impacts the work of data management and also impacts the importance of data management and building applications,” Satyen Sangani, CEO and co-founder of Alation told VentureBeat.
Traditional data catalogs operated on a destination model. Users navigated to the platform, searched for information and browsed through results. This approach worked when data teams served as intermediaries between business users and data systems.
“Previously, Alation has been sold to primarily data management professionals,” Sangani said. “Increasingly, we’re finding CIOs, CTOs and CPOs who are building technology and who are trying to roll technology out, are leveraging Alation in order to be able to build agents and simultaneously make sure that those agents are appropriately governed and managed.”
Simply put, business users wanted direct access to data without technical expertise or analyst intervention. Those types of users just want to get the data they need and the right answers without worrying about the complexity of the underlying data platforms, which is where AI makes a big difference.
“I think the world has been turned upside down, and I think chat is really the new medium through which people will do this idea of self service data, where the catalog was the old medium,” Sangani said.
Alation’s approach centers on what Sangani calls a “knowledge layer” of curated data products and comprehensive metadata. While Alation has had its own data catalog and governance capabilities that it has developed over the past decade, it recently acquired privately-held startup Numbers Station to help build out agentic AI capabilities for data.
“What Numbers Station did is they basically built agents on top of structured data,” Sangani said. “What they realized as they were building these agents is that building these agents wasn’t so much an AI problem as it was a metadata and evaluation problem.”
The Numbers Station technology is now a foundational part of Alation’s new chat capabilities. This integration allows users to query their data through chat, making data more accessible and queryable at scale. The technology focuses on ensuring that the right metadata is available, that the precision of agents can be evaluated, and that agents are given the correct instructions and tuning.
Competitive positioning in the data intelligence market
There is no shortage of competition in the traditional data catalog market.
Large data platform vendors including Databricks and Snowflake each have their own technologies. Informatica, which is in the process of being acquired by Salesforce, is also active in the space as is Collibra and Atlan. In the midst of the competition, analyst firm Forrester positioned Alation as a leader in its Q3 2025 evaluation of data governance solutions.
Alation differentiates by remaining compute-agnostic and focusing on the metadata and evaluation layer rather than building a vertically integrated stack.
“We don’t see ourselves as a compute vendor,” Sangani noted. “We allow you to build these precision agents, we allow you to test them and evaluate them, and just as critically, we also allow you to do that agnostic of any underlying compute.”
This approach addresses enterprise concerns about vendor lock-in while solving the precision problem that has limited AI adoption in structured data scenarios.
“We think that data management is no longer something that sits off to the side, but that’s really fundamentally merged with the construction of business processes, and that’s what we see as being exciting,” he said.
How the AI-powered data catalog powers real world intelligence
Euromonitor International demonstrates how modern data catalog and data intelligence technology transforms business operations.
The market intelligence company is integrating Alation’s conversational data intelligence capabilities into its Passport platform, which serves over 2,500 organizations worldwide.
The Euromonitor data stack includes a cloud-native data warehouse for structured data, which is fed by a variety of sources, including operational databases, third-party applications and internal systems through data integration and ETL tools.
Business intelligence and analytics tools sit on top, allowing analysts to create the reports and dashboards available in Passport. The company’s data science teams use cloud-based machine learning services for building predictive models and advanced analytics. Euromonitor engaged Alation to enhance its Passport AI capabilities by adding natural language insights on its statistical data.
“This capability allows our customers to access insights quickly using natural language queries without having to configure complex filters,” Lamine Lahouasnia, Director of Gen AI at Euromonitor International told VentureBeat. “It allows our users to discover data and insights that may have been hidden in the past.”
Lahouasnia explained that the previous workflow required clients to navigate multiple pages and complex filters to find specific market data. Users often had to restart their searches when refining criteria. This created bottlenecks that slowed customer decision-making.
The conversational interface allows clients to ask questions in plain English and receive immediate answers with full transparency. The system shows underlying data sources, calculations and reasoning behind each response.
The implementation also enables flexible data aggregation. For example, Lahouasnia said that the Euromonitor Passport platform includes pre-calculated regional groupings like the Middle East and Africa. He noted that many clients define regions differently based on their internal business needs. The conversational interface allows custom aggregation based on client-specific definitions without requiring data extraction and manual processing.
How enterprises should implement and deploy data intelligence
Euromonitor went though what Lahouasnia described as a ‘rigorous’ process when it was looking to select a vendor.
That process and the overall journey revealed a number of key lessons and best practices:
Trust is the foundation: Never compromise on accuracy, especially when your data is a product. Look for a solution that can provide clear lineage, definitions, and quality metrics. When users can see how an answer was generated and where the data came from, they build trust in the result and are more likely to use it for critical decisions.
Focus on people and process: A data intelligence platform is a cultural shift. You must invest time and effort in change management. Appoint data champions within different business units, establish clear governance roles, and provide ongoing training. Technology is the tool, but your people are the ones who will drive its success.
Governance from day one: Don’t let your data get ahead of your governance. Implement a solution that enforces your existing security policies from the start. This proactive approach ensures data is always protected and reduces risk.
Strategic partnerships are key: Technology alone isn’t enough.“Our partnership with Alation has been a critical component of our success, especially with legacy data structures that don’t always work with out-of-the-box configurations,” Lahouasnia said. “It was incredibly helpful to work with a partner that guided us through our own data and made recommendations on how best AI agents could work with it.”
