3250: Couchbase: Overcoming Infrastructure Hurdles in Enterprise AI

Here’s the thing: we all heard Sundar Pichai say that the easy wins in AI have faded and that we may see fewer headline‑grabbing releases from the big players over the next year. That comment feels like a red flag for momentum, but I see it as a green light for action.  In this episode, I chatted with Rahul Pradhan, VP of Product and Strategy at Couchbase, about how teams can take advantage of this pause to move projects from simple experiments into solid, production‑ready services. I ask why many organizations hesitate to send their data to public AI endpoints. Rahul explains that when you’ve invested years building data platforms, handing over your proprietary information—even in encrypted form—can feel like handing over the keys to your kingdom. He walks us through how running models inside your security perimeter keeps private data safe and brings up model accuracy since you can tailor inputs and scrub out noise before it ever reaches the inference engine. Next, we tackle the question of stability. Companies often assume that the path to a live service is straightforward once a pilot works. Rahul warns that managing GPUs, orchestrating models, and serving them at low latency all require skill sets that live at the crossroads of ML engineering and traditional software development. We round out our conversation by shifting focus from tools to teams. Technology alone cannot carry an AI initiative. We need leaders who set a clear vision, data stewards who govern every data flow, and developers who feel as comfortable writing database queries as they define training pipelines. Rahul offers thoughtful advice on building that culture and shares examples of industries—healthcare, financial services, and retail—where the most far‑reaching uses of AI are taking root. If you’re wondering how to push your proof of concept into a robust service that customers depend on, this episode is for you. I promise you’ll come away with ideas you can apply tomorrow and a fresh view of why a little breathing room in AI releases can become the launch pad for your subsequent big success.