In this AI and Data Trust CUBE Conversations segment, theCUBE’s Rob Strechay sits down with Jay Limburn, chief product officer of Ataccama, to unpack the company’s just-launched Agentic Data Trust platform and why data trust is now the prerequisite for enterprise AI at scale. Limburn explains how Ataccama unifies catalog, data quality, lineage, pipeline observability and reference data into a single platform – and layers in a true agent (beyond a basic co-pilot) that plans and executes multi-step work from a simple prompt. The discussion walks through how the agent profiles and classifies tables, documents columns, applies quality checks, flags anomalies, corrects discrepancies and generates business-ready reports – while keeping human-in-the-loop oversight and governance guardrails front and center for regulated industries.
The conversation further explores how Ataccama positions data trust as the foundation for sustainable AI programs, including an MCP integration that lets enterprise agents (e.g., Claude, GPT) tap a “trust layer” so they operate only on explainable, high-quality data. Use cases span data-hungry sectors such as financial services, insurance, manufacturing and pharma, with examples like autonomous credit risk assessment, fraud claims detection and quality assurance. Echoing insights from Ataccama’s Data Trust Report, Limburn notes that organizations racing ahead with AI often do so on shaky governance foundations, making leadership buy-in, cross-functional alignment and culture change essential to avoid failure modes and realize autonomous data operations.
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Jay Limburn, Ataccama
In this AI and Data Trust CUBE Conversation, Larry Hunt, field chief data officer at Ataccama, joins theCUBE’s Rob Strechay to unpack why trusted data, not just tools or talent, is the critical path to real AI adoption. Citing Ataccama’s Data Trust Report and his financial services background, Hunt highlights the gap between ambition and outcomes: while ~99% of firms are piloting AI, only ~3–4% are seeing results, with data trust as a primary blocker. He explains how governance succeeds when it’s “compliance by design,” tied to CEO/board-level KPIs, and focused on enabling business outcomes, rather than “selling governance.” He also notes where leadership buy-in and cross-functional alignment matter most, and why 46% of leaders call out data quality as a top priority.
Hunt gets candid about today’s hybrid reality: legacy debt is worsening at large, federated institutions, making sustainability and scale the hardest challenges. He outlines how data products/domains can help de-risk modernization while balancing the CDO’s defensive mandate (regulatory compliance, risk) with offensive value creation (improving efficiency ratios). The takeaway: we may be in an AI hype cycle, but value will arrive faster than past waves – for organizations that ground their programs in trusted data and embed governance from the start.
In this AI and Data Trust CUBE Conversations segment, theCUBE’s Rob Strechay sits down with Jay Limburn, chief product officer of Ataccama, to unpack the company’s just-launched Agentic Data Trust platform and why data trust is now the prerequisite for enterprise AI at scale. Limburn explains how Ataccama unifies catalog, data quality, lineage, pipeline observability and reference data into a single platform – and layers in a true agent (beyond a basic co-pilot) that plans and executes multi-step work from a simple prompt. The discussion walks through how the...Read more
