Mudit Garg

Every hospital Mudit Garg visited during his years at McKinsey told the same story. The equipment was state-of-the-art. The clinicians were exceptional. The therapy was evidence-based and precise. Then he looked at how the place actually ran - how a patient got from admission to a bed to surgery to discharge - and the picture shifted. "It was just unbelievable," he said. The burden of coordination fell entirely on staff. The logistics were, in his words, held together by duct tape and fax.

That observation was not a metaphor. It was a product specification. Garg, who studied electrical engineering at IIT before earning dual degrees at Stanford, saw the problem the way an engineer sees a broken system: as something that could be redesigned. So in 2012, he co-founded Qventus.

Thirteen years later, Qventus sits at the center of one of the most pressing economic problems in American medicine. Operating rooms that run at 70% capacity. Discharge bottlenecks that stretch two-day stays into five. Staff managing patient logistics through phone calls, spreadsheets, and institutional memory. The costs are staggering. The waste is invisible to patients and only partially visible to administrators.

Garg built a platform to make it visible - and then to fix it automatically.

Garg describes Qventus's AI evolution using a personnel analogy that cuts straight to the point. An early AI system tells a nurse: there's a problem. A better one adds: here's what you might do. Better still: this is the best option - I'll do it unless you say otherwise. And the real goal: there was a problem. There is no longer a problem.

That last rung is where Qventus is headed. The platform has evolved from a data-display tool into what Garg calls an "AI operational assistant" - a system that takes autonomous action on discharge planning, surgical scheduling, OR utilization, and inpatient capacity without requiring a clinician to interpret a dashboard.

The operating room is where this matters most. Even in primetime, hospital ORs run at roughly 70% utilization - 30% empty despite patients and surgeons who can't get appointments. Qventus's surgical growth module works to release blocked OR time, and the results are measurable in hours, not percentages: hundreds of OR hours freed per month, per hospital.

Garg is deliberate about what Qventus is not. "We are not an AI scribe company," he said plainly. AI scribes - tools that transcribe clinical notes - have become a crowded commodity. Qventus operates in a harder, less glamorous, and more valuable layer: the operational logic that determines whether a hospital runs efficiently or hemorrhages cost.

His product philosophy reflects his engineering background: the best tool is invisible. "Like a really good assistant," he has said - one that delivers the right insight at the right moment without adding cognitive load to an already-stretched clinical team. The nurses he spoke with early on were direct: "I don't have time to figure out 30 percent chance do this, 40 percent chance do that." So Qventus stopped showing probabilities and started giving recommendations. Then it started acting on them.

The January 2025 Series D - $105M led by KKR - accelerated that trajectory. Three of Qventus's own hospital customers joined as strategic investors: Northwestern Medicine, HonorHealth, and Allina Health. That's not just a vote of confidence. It's a signal that the people running hospitals believe this platform is becoming infrastructure.