Hospitals are increasingly searching for ways to reduce staff workload while maintaining quality care, and robotics is gaining ground as a solution. Diligent Robotics has announced Moxi 2.0, a significant update to its mobile manipulator platform operating in healthcare environments. As hospitals struggle with burnout and staff shortages, automated assistants handle the everyday logistical tasks, offering relief for medical teams. The new system reflects lessons learned from millions of autonomous deliveries, and the company aims to broaden its reach not only in hospitals but also in senior living communities to support staff and interact with residents on a daily basis.
Reports about Moxi’s early versions highlighted modest adoption in hospitals, relying on NVIDIA‘s Jetson computing, and primarily focused on routine supply and medication delivery. Those initial deployments faced limitations in navigation and adaptability, with data indicating a need for more intelligent real-time responses in crowded, unpredictable settings. Current developments now reveal a leap in computational abilities and learning capacity, addressing previous bottlenecks identified by medical staff and robotics analysts.
What Improvements Define Moxi 2.0?
Moxi 2.0 introduces a suite of hardware and software upgrades. The robot leverages NVIDIA Thor for AI processing, offering ten times the computing performance of its predecessor, which enables higher-speed inference and more sophisticated behavior. Its enhanced design aims for easier manufacturing and greater durability, supporting the company’s plan to expand rapidly across healthcare settings. With ongoing feedback from hospital deployments, the engineers improved user interaction points and servicing panels for easier operation.
How Does Data Drive Moxi 2.0’s Capabilities?
By maintaining one of the largest datasets on human-robot interaction, Diligent Robotics feeds vast experience back into its systems. With every delivery, data from dynamic hospital environments trains the robot’s navigation and manipulation algorithms. This information loop lets Moxi anticipate and adapt to real-world complexities, including moving around hospital beds and equipment in busy corridors.
“We’ve collected millions of examples of Moxi operating in dynamic human environments, now built into Moxi 2.0, the first system to truly reflect that lived experience and everything we have learned,”
explained Andrea Thomaz, co-founder and CEO.
When Will Hospitals See Moxi 2.0 In Action?
Diligent Robotics expects to begin deploying Moxi 2.0 robots in the first half of 2026, following current rounds of rigorous hardware and software testing. The company has also signaled its intention to expand into senior living, guided by participation in the AgeTech Collaborative.
“The hardware is going through rigorous testing as we approach manufacturing. In parallel, we continue to iterate the build models to run inside the robot once the hardware is ready,”
stated Vivian Chu, co-founder and chief innovation officer.
Diligent’s approach aims to overcome the common robotics challenge of scaling before robust learning, using its growing fleet to feed valuable data back into development and propel rapid improvement. The introduction of an AI Advisory Board further contributes technical oversight and ensures the latest advances in machine learning are reviewed for application to the Moxi platform. With IGX Thor technology from NVIDIA powering both real-time sensor processing and advanced manipulation, Moxi 2.0 is built for higher-volume, more complex hospital deployments, with the company projecting the number of robots to scale significantly by 2030.
For healthcare professionals and technologists, the implication of Moxi 2.0’s launch is twofold: it signals a step forward in practical AI robotics supporting daily medical routines and highlights the importance of ongoing field data collection for improvement. Hospitals interested in robotics-assisted workflow should consider the adaptability and data-driven development demonstrated in Moxi 2.0. As the field of healthcare robotics matures, platforms like this are poised to become routine collaborators in care teams, not just for efficiency but for consistent human interaction in sensitive environments.
