Despite the explosion of 'talk to your data' agents, most fall short of production-grade accuracy — here's why the problem is architectural, not just about better LLMs.
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Three forces — the complexity of production-ready data agents, the unsolved challenge of context engineering, and the lack of open architecture choices — are converging to demand a fundamentally new approach to...
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Promethium Mantra™ lets analysts talk to all their enterprise data — across warehouses, SaaS apps, and on-prem systems — to get fast, trusted answers grounded in real business context.
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Former 3x CDO Kjersten Moody shares hard-won lessons from Unilever, State Farm, and Prudential on why thinking local unlocks global impact, how governance enables speed, and why AI is reshaping enterprise leadership....
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Why most “talk to your data” initiatives stall — and what it actually takes to break the metadata bottleneck and deliver production-grade, trustworthy AI analytics.
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AI accuracy doesn’t fail because models can’t write SQL — it fails because enterprises underestimate the cost and complexity of engineering business context at scale.
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AI initiatives aren't stalling because the technology isn't ready — they're stalling because most enterprise data architectures were designed for centralized warehouses and predictable questions, not distributed data...
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2026 is when AI pilots have to become production systems — here are the five infrastructure shifts that separate the companies who scale from those stuck explaining why their AI investments haven't delivered ROI.
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Self-service data management is no longer optional — here's what separates the organizations getting it right from those falling behind.
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On the latest episode of The AI Data Fabric Show, Generac CDO Neil Bhandar joins Promethium CEO Prat Moghe to discuss navigating data leadership across industries and why CDOs must speak the language of business, not...
Continue Reading » Despite the explosion of 'talk to your data' agents, most fall short of production-grade accuracy — here's why the problem is architectural, not just about better LLMs.
Continue Reading »
While 77% of organizations prioritize AI-ready data investments, most struggle to define what 'ready' actually means — and that gap is why 60% of AI initiatives fail.
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AI-ready data isn’t achieved through fabric or mesh alone — it’s the synergy between unified data access and distributed ownership that makes self-service and trustworthy AI possible.
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