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Alation unveils Agent Builder, a comprehensive suite designed to streamline the creation and deployment of autonomous, governed AI agents, marking a significant evolution in enterprise AI platforms amid rising industry competition.
Alation has unveiled Agent Builder, a new suite of features designed to streamline the development and deployment of agentic AI applications using structured data. The announcement came during Alation’s revAlation user conference in Chicago, marking the latest step in the company’s evolution from a metadata management vendor focused on data catalogues toward a broader AI development platform. Agent Builder enables users to draw on a Knowledge Layer within Alation’s Agentic Data Intelligence Platform, which provides agents with essential business context and metadata, underpinning more reliable and governed AI operations.
Agent Builder’s capabilities are extensive, incorporating no-code development tools, prebuilt agents tailored for specific business use cases, integrations via Model Context Protocol (MCP) and REST APIs, as well as security, governance, and accuracy evaluation features. According to Stewart Bond, an analyst at IDC, these functionalities help close the long-standing gap between prototyping and production of intelligent agents that operate on structured data. Bond highlights the importance of trustworthy context, data lineage, policy enforcement, and quality control in enabling these agents to function dependably at scale.
This move aligns with a broader industry trend where enterprises increasingly move from simple chatbot applications toward autonomous agents with reasoning and contextual awareness. Unlike chatbots that primarily respond to human prompts, agentic AI systems can act independently, offering heightened intelligence and operational efficiency. The surge in interest in AI development post-ChatGPT’s 2022 debut has prompted many vendors—including Databricks, Snowflake, AWS, Google Cloud, Microsoft, and rivals like Informatica—to introduce AI development suites geared toward building such agents.
Alation’s Agent Builder distinguishes itself with a metadata-centric approach, leveraging structured data and governance as a backbone for agent development. This strategy supports more accurate, secure, and compliant AI applications—addressing a known challenge where many AI pilots fail to progress to production. The agentic AI platform was further enhanced by Alation’s acquisition of Numbers Station, whose technology underpins Agent Builder’s ability to fast-track agent deployment and facilitate complex workflows typically performed by humans.
The product is undergoing private beta testing, with general availability anticipated in the first quarter of 2026. While agents like Alation’s represent an important step forward, industry experts caution that how enterprises will ultimately utilise these tools remains unclear. William McKnight, president of McKnight Consulting Group, notes that the integration of accuracy, governance, and ease of development in Agent Builder is well-conceived, but the suite’s entrance primarily ensures Alation keeps pace with a competitive market rather than radically differentiates the vendor.
Alongside Agent Builder, Alation has introduced related offerings that complement its vision for AI-driven data management. The Data Products Builder Agent, set for release in the third quarter of 2025, targets the creation of trusted, reusable data products from raw data, automating curation, documentation, and governance adherence while maintaining human oversight. Meanwhile, the AI Agent SDK facilitates third-party and in-house development of AI agents by providing standardised, secure access to Alation’s data intelligence capabilities using protocols like MCP. These augmentations support an integrated AI ecosystem intending to simplify and accelerate agentic AI workflows.
The broader goal, as articulated by Alation’s CEO Satyen Sangani, is to address the high failure rate of AI pilot projects by delivering metadata-grounded, governed, and customisable AI agents that enterprises can confidently deploy in production environments. This reflects a growing recognition that achieving trustworthy AI requires tightly controlled data environments that ensure high quality, lineage, security, and compliance.
Alation’s expansion into agentic AI development underscores the shift from traditional data catalogues to interactive, AI-powered data products and autonomous agents. As such, the company’s approach aligns with a growing consensus among industry analysts that the future of AI depends on integration with reliable data governance frameworks operating within the data control plane—a critical factor in making agentic AI trustworthy and effective in real-world business settings.
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Source: Noah Wire Services
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