Alation launches enterprise AI platform to enhance structured data accuracy and governance

Alation Inc. unveils Agent Builder, a no-code platform aimed at scaling AI agents for structured data in business contexts, promising over 90% accuracy and robust governance to accelerate enterprise adoption.

Alation Inc., a company specialising in data intelligence, has announced the launch of its latest AI platform, Alation Agent Builder, aimed at enabling enterprises to develop and deploy production-ready AI agents that work with structured data. According to the announcement, this platform focuses on delivering higher accuracy and governance in AI agents that act on structured datasets, which are fundamental to financial and operational reporting in businesses.

The new tool addresses a noted challenge in the AI space, where prototypes for agents handling structured data exist but scaling these for reliable production use demands rigorous accuracy and oversight. The firm said that Alation Agent Builder leverages its Knowledge Layer, which provides curated and governed data products, drawing contextual metadata from the overarching Alation Agentic Data Intelligence Platform to ensure responses from AI agents are contextually accurate. The platform includes a no-code interface and prebuilt tools, allowing integration with over a hundred data sources and deployment via popular API standards. Embedded evaluation and monitoring tools are designed to maintain the agents’ reliability in a production environment.

The company cited Jones Lang LaSalle (JLL), a global real estate firm, as an early adopter utilising the platform to query structured lease and property data for lease renewal advice. JLL’s Chief Product Officer described the technology as a way to augment human expertise by enabling AI agents to guide decisions and uncover opportunities in real time. The CEO of Alation highlighted that this innovation could move AI applications beyond experiments into enterprise-grade deployments, particularly where precision with structured data is critical.

Supporting the launch, additional capabilities of the platform include a library of ready-made agents and tools for common data tasks, built-in accuracy evaluation mechanisms aiming for over 90% accuracy before deployment, and strong data governance protocols with fine-grained access controls. The platform supports vendor neutrality, enabling businesses to choose from popular AI models or bring their own, thus avoiding vendor lock-in.

This launch follows recent product expansions by Alation, including tools such as the Data Products Builder Agent, which automates transforming raw data into trusted data products to ease workloads for data teams, and the Documentation Agent, which automates metadata documentation for improved searchability and usability. Together, these products illustrate Alation’s broader strategy to streamline data management and enhance AI integration for enterprise clients.

Alation introduced its Agentic Platform earlier in the year, which includes the AI Agent SDK supporting advanced protocols to facilitate AI innovation across its data intelligence ecosystem. The new Agent Builder can be seen as an extension of this platform, focusing on translating AI capabilities for structured data applications.

While the company emphasises accuracy and governance as differentiators in moving towards production-grade AI, industry experts note that the challenge remains in fully bridging prototype capabilities and enterprise adoption due to evolving AI governance standards and complexities in data environments. Nonetheless, tools offering no-code interfaces and embedding rigorous evaluation frameworks align with broader market trends seeking to democratise and secure AI usage in critical business functions.

The private beta for Alation Agent Builder is currently available, with the company inviting organisations to participate in initial testing phases.

📌 Reference Map:

• Paragraph 1 – ^[1], ^[6]
• Paragraph 2 – ^[1], ^[7]
• Paragraph 3 – ^[1]
• Paragraph 4 – ^[1]
• Paragraph 5 – ^[2], ^[4], ^[5]
• Paragraph 6 – ^[6], ^[7]
• Paragraph 7 – ^[1], external industry context

Source: Fuse Wire Services