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Sep 11
27m 9s

Can You Trust Your AI if You Can’t Trust...

NEIL C. HUGHES
About this episode

We talk a lot about AI as if it can fix broken systems. But what happens when the underlying data is too messy, too slow, or too disconnected to support anything useful? That’s the problem Manish Sood, founder and CTO of Reltio, has spent the last decade working to solve.

Reltio is not your average data company. It sits behind some of the world’s most recognisable brands, helping names like L’Oréal, Pfizer, HP, and CarMax modernise how they manage and activate data across the business. What they all share is a recognition that outdated systems and disconnected records don’t just slow down insights. They actively block innovation.

Manish breaks this down with uncommon clarity. He calls it “data debt”—the invisible burden of stale, incomplete, or fragmented information that quietly kills speed and adds risk. It’s not just a technical problem. It’s a leadership challenge, especially as businesses adopt generative AI tools that rely on clean, contextual data to function reliably.

We explore how real-time intelligence is changing the way companies operate across customer experience, fraud detection, and supply chain resilience. Manish shares examples from enterprise clients who have moved from legacy systems to unified platforms, and how that shift enabled smarter decision-making at scale. From personalised retail offers to proactive healthcare outreach, the stories point to one common truth: if the data isn’t trusted, the AI cannot be either.

There’s also a new role emerging inside many companies—the data steward as AI enabler. These are the people ensuring that data isn’t just stored, but shaped. Human-guided, explainable, traceable. That clarity is key to responsible AI, especially in sectors where compliance and reputation are tightly linked.

Manish also explains how Reltio’s platform helps businesses protect against AI vulnerabilities by enabling resilient data pipelines, consistent governance, and real-time monitoring. In a world where data is created and used simultaneously, batch syncing is not enough. Real-time pipelines give companies the confidence to experiment with AI without falling into chaos.

If your business is chasing innovation without cleaning up its data layer first, this conversation is a wake-up call. Manish shows that the future of AI isn’t about who builds the best model. It’s about who feeds it the best foundation.

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