ThinkData Podcast · 2026-05-12 · 34 min
Most enterprise AI isn’t failing because of the models… It’s failing because no one trusts the output. In this episode of the ThinkData Podcast, we’re joined by Uri Knorovich, CEO of Nimble, to unpack the growing trust gap in enterprise AI and why bad, delayed, and fragmented data is becoming the biggest blocker to real AI adoption. We explore: • Why AI works in demos but breaks inside enterprises • The hidden risk of AI outputs without traceable data lineage • Why trusted, live data infrastructure matters more than model speed • The shift from “is the AI fast?” to “can we trust the decisions?” • Real-world examples where AI and live data are already driving value A great conversation on the future of enterprise AI, data infrastructure, and building systems companies can actually rely on.
S4 | E19 | The future of software engineering teams with Scott Breitenother - Co-Founder @ Kilo64 / 100
S4 | E18 | Rebuilding Post-Discharge Care With Clinician-Led AI & Dimer Health
S4 | E17 | The Future of Finance Teams in an AI-Driven World with Deepak Bapat @ Tabs
S4 | E15 | AI, X-Rays & The Future of Dentistry with Overjet - Sadegh Salehi - Director of Research
S4 | E14 | The Missing Layer in AI: Why “Humaneness” Changes Everything with Vishnu - Founder @ ego AI