Alation on Wednesday introduced Agent Builder, a set of features designed to make it easy for customers to use structured data to develop and deploy agentic AI applications.
Agents built with the new suite, which was unveiled during Alation's revAlation user conference in Chicago, draw from a Knowledge Layer to access metadata stored in Alation's Agentic Data Intelligence Platform, which provides the agents with proper business context.
In addition, among other features, Agent Builder includes no-code development capabilities, prebuilt agents for specific use cases, connections to data sources through Model Context Protocol (MCP) and REST APIs, security and governance features and built-in evaluations to address accuracy.
Given that Agent Builder's capabilities provide a framework for building agents using structured data, it is a valuable addition for Alation customers, according to Stewart Bond, an analyst at IDC.
"It closes the prototype-to-production gap for agents that act on structured data," he said. "[Agent Builder] aligns with trends we are seeing as agents are moving into the data control plane and need trustworthy context, lineage, policies and quality to operate reliably."
Furthermore, Agent Builder, now in private beta testing with general availability scheduled for the first quarter of 2026, represents an evolution for Alation, Bond continued, noting that the vendor has historically focused on providing data catalog capabilities.
"These new additions are transforming the user experience from catalog-centric workflows to working with chat-ready governed data products, automated curation and remediation," he said.
Based in Redwood City, Calif., Alation is a metadata management vendor that provides a platform for integrating, organizing and governing data from separate systems to make it operational for AI and analytics-based analysis. In March, Alation unveiled agents and an initial software development kit for developing agents.
New capabilities
With Agent Builder, Alation is getting in on the dominant trend in AI development.
Interest among enterprises in AI development has surged since OpenAI's November 2022 launch of ChatGPT significantly advanced generative AI (GenAI) capabilities, which can make employees better informed and more efficient. Initially, much of that development focused on building chatbots that enable users to query and analyze data using natural language, expanding the use of analytics by allowing non-technical workers to work with data.
By mid-2024, however, AI development was focused on agents. Agents, unlike chatbots that require human prompts to act, have reasoning capabilities and contextual awareness that enable them to act autonomously to provide organizations with greater intelligence and efficiency than their predecessors.
While Agent Builder provides the crucial missing piece for enterprises seeking to operationalize AI, specifically by providing the accuracy, governance and structural integration necessary for complex actions that rely on trustworthy structured data, it's too early to tell how enterprises will utilize all the agent builders coming their way.
William McKnightPresident, McKnight Consulting Group
To meet the rising interest in AI development, which now includes agents, many data management and analytics vendors have created environments designed to simplify AI development. For example, data platform vendors Databricks and Snowflake, tech giants AWS, Google Cloud and Microsoft, and specialists such as Alation and its rival Informatica, all now provide AI development suites.
In recent months, those environments have grown to include features designed specifically for building agents. Those that have already unveiled such capabilities include Snowflake, Databricks and Informatica.
Now, Alation is joining the fray with Agent Builder. However, whether frameworks such as Agent Builder and those from competing vendors deliver on their intent remains to be seen, according to William McKnight, president of McKnight Consulting Group.
"While Agent Builder provides the crucial missing piece for enterprises seeking to operationalize AI, specifically by providing the accuracy, governance and structural integration necessary for complex actions that rely on trustworthy structured data, it's too early to tell how enterprises will utilize all the agent builders coming their way," he said.
Regarding the impetus for developing Agent Builder, which is built on technology the vendor inherited through its May acquisition of Numbers Station, helping customers more successfully build agents was a motivator, according to CEO Satyen Sangani.
Released in July, MIT's State of AI in Business report showed that just 5% of AI pilots make it to production. Alation aims to improve that with a metadata-driven approach to agentic AI development.
"DIY efforts [are] fragile and slow, vendor tools create lock-in and generic AI lacks accuracy," Sangani said. "Agent Builder solves this with governed, metadata-grounded, customizable agents that enterprises can truly own and trust in production."
Alation's Agent Builder is comprised of components that coherently simplify agentic AI development, according to Bond. In particular, he noted that no-code development capabilities, security and governance features and built-in monitoring tools are important.
Meanwhile, though Alation is now one of many data management vendors providing agentic AI development capabilities, Agent Builder is somewhat unique given its use of metadata, Bond continued.
"Marketwise, agentic capabilities across data intelligence are accelerating, so some follow-the-market is inevitable," he said. "Alation's emphasis on accuracy for structured data via a metadata knowledge layer, evaluation pipeline and governance inheritance is a differentiated angle and is consistent with IDC's view that the data control plane is where agent reliability is made or broken."
McKnight similarly noted that Agent Builder is comprised of "well-thought-out" capabilities that make sense together, with the accuracy and monitoring tools particularly important.
However, from a competitive standpoint, the suite keeps Alation current with the litany of other vendors also providing agentic AI development capabilities rather than meaningfully differentiating the vendor, he continued.
"It's a defensive, table-stakes move, staying relevant as the market shifts toward agentic interfaces," McKnight said. "It's too early to tell if the market will value its potentially innovative angle of having a governance-first, accuracy-validated approach."
Looking ahead
As Alation plots its roadmap, product development will focus on helping users build powerful agents, expanding governance, improving data product management and remaining both sovereign -- so it can operate independently -- and open so customers can integrate other tools, according to Sangani.
"These priorities will drive our innovation through late 2025 and into 2026," he said.
McKnight noted that Alation provides a passive repository for data rather than an active intelligence platform that uses AI to help users take proactive action. Therefore, the vendor would be wise to add capabilities that enable customers to be more predictive rather than reactive.
"They collect this incredible strategic view but don't fully exploit it to drive proactive insights, recommendations or organizational optimization," McKnight said. "Alation could drive the build of agents that act on the catalog's organizational intelligence."
Bond, meanwhile, suggested that Alation could provide additional agents within its own platform as well as add support for unstructured data.
"I would like to see Alation tackle event-driven, real-time agents which can react to data change events -- not just queries -- and broaden multimodal and unstructured integration to complement today's structured focus," he said.
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.
