How do you move AI from a flashy demo on a conference stage to something that can handle real customer pressure on a Monday morning when the tickets are piling up? In this episode of AI At Work, I sit down with Niraj Ranjan Rout, Founder and CEO of Hiver, to unpack what it really takes to build AI that works inside high-volume support environments. With more than 10,000 teams using Hiver, including brands like Flexport, Capital One, and Epic Games, Niraj has had a front-row seat to both the promise and the pitfalls of AI in customer service. We talk about the difference between “slapping a chatbot” onto an existing problem and rethinking the entire support workflow. Niraj makes a compelling case that AI should function as infrastructure, embedded across triage, routing, drafting, summarization, quality assurance, and insights. Rather than replacing agents, the goal is to remove the repetitive, manual work that drains time and energy, so humans can focus on solving real problems and understanding how customers actually feel. Our conversation also gets into the uncomfortable but necessary topics many leaders underestimate. Data hygiene. Governance. The reality that 98 percent accuracy is sometimes still not good enough. Niraj shares why clear handoff protocols between humans and AI are essential, and how organizations can avoid measuring ROI through surface metrics like deflection rates alone. Instead, we explore more nuanced signals, from sentiment shifts to long-term customer outcomes and team productivity. We also discuss Hiver’s own journey from an email collaboration tool to an AI-native customer service platform. Niraj is candid about the noise in the market, from overblown promises to doomsday narratives, and how founders must stay close to customers while remaining hands-on with emerging models and agentic capabilities. Culture, he argues, is as important as code. Customer stories need to flow directly into product and engineering teams if AI investments are going to remain grounded in reality. And yes, we even end on a musical note, with a nod to Jimi Hendrix and a reminder that creativity, whether in music or software, still comes down to craft and feel. So here’s the question I’ll leave you with. As AI becomes embedded into every workflow, are you treating it as a shiny add-on, or are you redesigning your foundations so it can truly perform under pressure?
