Diligent Robotics

Diligent Robotics builds Moxi, an autonomous mobile manipulation robot deployed inside US hospitals to run non-clinical errands — delivering medications from pharmacy, fetching supplies, picking up lab specimens, and shuttling personal protective equipment — so that nurses and pharmacy technicians can spend more time on direct patient care. Moxi uses a mobile base with a single arm plus social-intelligence behaviors (expressive 'eyes,' gestures, hallway etiquette) and is notable for being one of the most widely deployed mobile manipulator fleets in any commercial setting, with Diligent reporting it has crossed 1 million hospital deliveries and over 100,000 autonomous elevator rides. The company was founded in 2017 in Austin, Texas by CEO Andrea Thomaz (former UT Austin and Georgia Tech robotics professor) and CTO Vivian Chu. Diligent has raised approximately USD 50M+ across seed, Series A, Series B, and a 2024 extension round. The USD 30M Series B closed in April 2022 led by Tiger Global. A subsequent USD 25M round was led by Canaan with True Ventures, DNX Ventures, and Next Coast Ventures returning and Northwestern Medicine Innovation joining as a strategic investor. Moxi is deployed across 25+ US health systems, and in 2025 Diligent unveiled Moxi 2.0 with NVIDIA-accelerated perception.

Diligent is the clearest commercial-traction story in US healthcare robotics: an operating fleet at 25+ hospitals with real volume metrics and strategic backing from a major health system, setting the reference point for any generalist humanoid competing in hospital workflows.

diligentrobots.com Healthcare Robots

United Statesprivate

At a glance

Total raised

$75M

last round series b extension

Headcount

51-200

approximate · public range

Headquarters

Austin, Texas

United States

Founded

2017

9 years active

Status

Private

Healthcare Robots

Patents on file

USPTO grants

For subscribers

Subscribe to see the full profile

Including Funding rounds, Bull / Bear thesis, Stock + earnings, Roster changes, Patents, News, and Open roles.

Founding

50% off

/month

94 of 100 spots left

Full

$10

/month

Available once all 100 Founding Member spots are claimed.

Get full access

Already subscribed? Sign in →

Funding history

Total raised

$75M

Rounds tracked

Latest stage

Series B extension

Date	Stage	Amount	Valuation	Lead investors
Jun 1, 2024	Series B extension	$25M	—	Canaan

Founder backgrounds

Andrea Thomaz

Co-Founder & CEO

Earned a PhD in Media Arts and Sciences from MIT's Media Lab, where she studied socially guided machine learning under Cynthia Breazeal. She then spent a decade as a professor at Georgia Tech, founding and directing the Socially Intelligent Machines Lab and publishing extensively on human-robot interaction and interactive machine learning. In 2016, she co-founded Diligent Robotics with Vivian Chu, a former graduate student from her lab, to spin their research on socially aware robotic coworkers into a commercial product. That product became Moxi — a mobile manipulation robot designed to handle supply runs, medication delivery, and lab errands in hospitals. Thomaz was named to MIT Technology Review's Innovators Under 35 list and Popular Science's Brilliant 10.

Vivian Chu

Co-Founder

Earned a Ph.D. in Robotics at Georgia Tech (2018), where her research centered on human-robot interaction and adaptive autonomy — work that directly informed Diligent's socially intelligent approach. Earlier, she completed an M.S.E. in Robotics at UPenn's GRASP Lab and spent two years on NLP and information integration at IBM Research Almaden, with additional stints at Google[X] and Honda Research. She co-founded Diligent Robotics in 2017 alongside her former Georgia Tech advisor Andrea Thomaz, building Moxi to address hospital staff burnout — a mission shaped partly by watching her grandparents age into long-term care. Recognized on MIT Technology Review's 35 Innovators Under 35 (2019) and Fortune's 40 Under 40 (2022). She serves as Chief Technology Officer.

AI bull / bear

Bull case

Diligent Robotics has achieved what few manipulation-focused robotics companies can claim: real commercial scale. With over 1 million hospital deliveries, 100,000 autonomous elevator rides, and deployment across 25+ US health systems, Moxi has demonstrated repeatable value in one of the most regulated, risk-averse environments. The $75M raised (including a $25M Series B extension in 2024) and strategic backing from Northwestern Medicine Innovation signal investor and customer confidence. The 2025 unveiling of Moxi 2.0 with NVIDIA-accelerated perception positions the platform to tackle more complex tasks as AI capabilities improve. In a sector where humanoid robot makers promise hospital deployment but lack field data, Diligent owns the reference dataset and operational playbook. Serve Robotics' $29M acquisition suggests consolidation is creating exit opportunities even for assets with mixed signals, and Diligent's fleet economics and workflow integration learnings are valuable IP for any acquirer targeting healthcare logistics at scale.

Bear case

The discontinuation of Moxi at two Washington hospitals exposes a fundamental risk: deployment success depends less on robot capability than on hospital workflow readiness and unit economics. If facilities with early access are walking away, it suggests the value proposition—freeing nurses for patient care—may not translate into defensible ROI or sustainable adoption. Hospitals operate on thin margins; a robot that requires workflow redesign, dedicated support staff, or unclear payback periods will struggle to expand beyond pilot-friendly early adopters. Serve Robotics' $29M acquisition of Diligent—at a steep discount to the $75M raised—signals that investors see limited standalone upside. The deal implies Diligent's technology may be worth more as an acqui-hire or platform component than as an independent growth story. With 25+ deployments over seven years, the pace of expansion has been slow relative to capital deployed, and the pivot to Moxi 2.0 suggests the first-generation product faced adoption headwinds that even NVIDIA acceleration may not fully resolve.

Generated by claude-sonnet-4-5-20250929 · April 25, 2026Refreshes quarterly · see disclosures

In the news

Diligent Robotics · last 30 days

No articles ingested yet for Diligent Robotics. Once the hourly news pipeline is live, every article the classifier tags as mentioning this company appears here with its one-line AI summary and sentiment.

Watch

Leadership

Andrea Thomaz

Co-Founder & CEO

Vivian Chu

Co-Founder

Products

Moxi (hospital delivery and errand robot)
Autonomous mobile manipulator robot with an articulated arm and gripper hand designed to navigate hospital hallways and deliver supplies. Currently operating in over 25 U.S. hospitals, Moxi uses social intelligence to open elevators and doors autonomously while avoiding people and objects, paired with human-guided learning that allows the robot to adapt to each facility's workflows. Distinctive to Moxi is its socially intelligent design that avoids making staff uncomfortable. The fleet has completed over 1.25 million deliveries, creating a dataset of real-world human-robot interaction that feeds continuous improvement. The robot assists nurses and pharmacy staff with routine tasks such as delivering medications and lab samples.
Moxi 2.0
Next-generation mobile manipulation robot built with AI from the ground up, succeeding Diligent's earlier Moxi platform. Powered by NVIDIA Thor compute, Moxi 2.0 deploys an end-to-end action model optimized for enhanced dense navigation behaviors and high-precision, complex manipulation. Built on three years of real-world data collected from over 1.25 million deliveries in hospital environments, the platform is designed to scale within single hospitals. Moxi 2.0 has 10x the compute of Moxi 1.0, and Diligent plans to send out the first upgraded robots to hospitals in the first half of 2026.

Most recent patents

Diligent Robotics, Inc.·2025-01-21
Systems, Apparatuses, And Methods For Robotic Learning And Execution Of Skills Including Navigation And Manipulation Functions
US12202142
Abstract
Systems, Apparatuses, And Methods For Robotic Learning And Execution Of Skills Including Navigation And Manipulation Functions
US12202142
Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to execute skills and/or behaviors using cached trajectories or plans. In some embodiments, the processor can be configured to execute skills requiring navigation and manipulation behaviors.
View on Google Patents
Diligent Robotics, Inc.·2024-12-24
Systems, Apparatus, And Methods For Robotic Learning And Execution Of Skills
US12172314
Abstract
Systems, Apparatus, And Methods For Robotic Learning And Execution Of Skills
US12172314
Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.
View on Google Patents

Open roles

We don't have a live feed for this company's ATS. Their careers page has every open role.

View all careers ↗