Natoe AI Reimagines Global Teleradiology with Its AI Co-Pilot, Solving Workflow Bottlenecks and Accelerating Diagnostic Reporting

VMPL

New Delhi [India], October 16: Radiology worldwide is under sustained pressure. More than 3.6 billion diagnostic imaging exams are performed each year, including over 375 million CT scans and 100 million MRIs, yet the supply of qualified radiologists is not keeping pace with demand. The result is reporting backlogs, delayed diagnoses, and operational inefficiencies across hospitals and imaging centers. The gap between clinical need and available reporting capacity has become one of the most persistent challenges in modern care delivery.

Natoe AI is a next-generation teleradiology network centered on an AI Co-Pilot that supports radiologists from study intake to signed report. The approach is simple and pragmatic: keep clinical judgment with the radiologist, streamline the surrounding workflow, and shorten turnaround time without forcing disruptive changes to existing systems. Founded by Indian entrepreneurs and headquartered in the United States, the company focuses on U.S. imaging centers and hospitals that are looking for a faster, more consistent reporting layer.

Rather than operate as a pure software vendor, the team runs a full teleradiology service with licensed radiologists, an intelligent case queue, and integrated reporting tools. Imaging centers connect to a single platform, cases are routed to the right reader, and structured reports are returned quickly and consistently. The Co-Pilot assists with drafting and documentation so specialists can concentrate on interpretation, clinical nuance, and communication with referring physicians. The net effect is shorter turnaround time, fewer manual handoffs, and clearer reports that fit the needs of busy clinical teams.

"We are building the future of teleradiology, where radiologists and AI work together seamlessly," said Herukh Shahani, Co-founder and Chief Business Officer. "Our goal is to make reporting faster and AI adoption effortless for imaging centers. This is not about replacing experts, it is about amplifying them and removing the routine work that slows care."

Leadership experience matters in healthcare infrastructure, and the founding team brings it. Rakesh Deshmukh previously founded Indus OS, a mobile operating system that scaled to more than 200 million users and was later acquired by PhonePe. He is joined by Pragya Goyal, Co-founder and Chief Technology Officer, and Herukh Shahani, Co-founder and Chief Business Officer. Together they combine large-scale software execution, product discipline, and a deep understanding of clinical workflow. The focus is on reliability, operational clarity, and measurable outcomes for providers.

The market need is significant. In the United States, diagnostic imaging services account for more than USD 140 billion annually. A meaningful portion of that value sits in the reporting and workflow layer, the last mile that determines how quickly results reach clinicians and patients. As imaging volumes continue to rise, providers are looking for capacity they can trust, faster report delivery, and tools that reduce administrative burden without creating new complexity. This is where a disciplined, service-led model supported by an AI Co-Pilot can make a measurable difference.

What sets this effort apart is the commitment to integration rather than reinvention. Hospitals and diagnostic centers already run mature systems for scheduling, scanning, and communication. The task is to connect to those systems cleanly, move cases through with minimal friction, and return high-quality reports that are easy to use. By aligning to how radiologists actually work and by focusing on the points of delay that cause most of the frustration, the platform aims to improve throughput while protecting clinical standards.

Industry stakeholders increasingly agree that the answer is not a single breakthrough feature, it is end-to-end discipline. That means predictable case routing, clear ownership, streamlined documentation, and time back to specialists who need it. It also means adopting AI in a way that is transparent and accountable. The Co-Pilot is designed to assist, not overstep, and the final word on every case remains with the radiologist who signs it. This balanced approach reflects where the market is heading and how health systems prefer to adopt new capability.

As the network expands across U.S. imaging centers, the company plans to deepen collaborations with health systems, radiology groups, and technology partners that share a system-level view of reporting. The aim is straightforward: help providers move faster, raise consistency, and reduce the operational drag that slows care. By closing the gap between imaging demand and reporting capacity, there is an opportunity to improve outcomes for patients and day-to-day experience for clinicians.

About Natoe AI

Natoe AI is a teleradiology company built on its proprietary AI Co-Pilot platform, helping radiologists and imaging centers deliver faster, smarter, and more consistent diagnostic reports. Founded by Indian entrepreneurs and headquartered in the United States, the company brings together expertise in artificial intelligence, radiology workflow design, and large-scale software engineering. Learn more at www.natoe.ai.

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