Moxi 2.0 Review: Specs, Price & Hospital Use

Moxi 2.0: Quick Buyer Verdict

Moxi 2.0 should be evaluated as a hospital logistics platform, not as a robotic nurse.

Its job is to remove repetitive point-to-point transport from highly trained staff. Typical workflows include moving medications from pharmacy, transporting laboratory samples, fetching supplies, distributing equipment and supporting hospital programmes such as Meds-to-Beds.

That sounds simple until the operating environment is considered. A hospital delivery robot must navigate crowded corridors, wait for beds and carts, interact with people, cross secure doors, use elevators, recover from blocked routes and keep operating while the building changes around it.

This is where Moxi 2.0 is unusually interesting.

Diligent Robotics built the second generation around years of real-world fleet experience rather than a laboratory prototype. The company says the new platform has 10× the onboard compute of the previous generation, processes perception 10–15× faster, operates for up to nine hours at a time and can support up to 18 operating hours per day.

Pros

• Purpose-built for real hospital logistics rather than general demonstrations.
• Built on years of commercial hospital deployment data.
• 10× more onboard compute than the previous generation.
• Perception reported to operate 10–15× faster.
• Up to nine hours of runtime at a time.
• Up to 18 hours of operating time per day.
• Charging is reported to be 30% faster than the previous generation.
• Can operate across multi-floor hospitals.
• Mobile manipulation arm can interact with doors, elevators and objects.
• Designed to work alongside hospital staff and visitors in shared environments.
• Improved cameras, sensors and storage.
• World Model and fleet-learning architecture create a path for autonomy to improve after deployment.
• Safety and autonomy behaviours run onboard rather than depending completely on Wi-Fi.
• Cellular fallback can help cover hospital network dead zones.
• Diligent provides implementation support rather than expecting the hospital to integrate a raw robot platform.

Cons

• No public Moxi 2.0 unit price.
• No public payload rating for the storage drawers.
• No complete public dimensions or weight specification for Moxi 2.0.
• No public maximum travel speed in the current launch material.
• No public IP rating for wet or harsh environments.
• Hospital deployment still requires operational, IT, facilities and clinical coordination.
• Elevators, doors, access control and handoff workflows need site-specific validation.
• Not intended for direct patient treatment or patient handling.
• Most published productivity evidence comes from the earlier Moxi fleet rather than long-duration Moxi 2.0 deployments.
• The economic case depends heavily on delivery volume and route length.
• A small hospital or clinic may not have enough repetitive transport to justify the programme.

Our recommendation: shortlist Moxi 2.0 when your hospital has a measurable volume of repetitive internal deliveries that currently consume nursing, pharmacy, laboratory or support-staff time. Do not start by asking how much the robot costs. Start by measuring how many deliveries are performed today, how long they take, who performs them and which routes Moxi could realistically automate.

Review the Diligent Robotics Moxi listing before requesting a deployment proposal.

How Much Does Moxi 2.0 Cost in 2026?

Diligent Robotics does not publish a fixed retail price for Moxi 2.0.

This is important because Moxi is sold as an operational hospital automation solution rather than a simple piece of hardware with a public checkout price.

Serve Robotics provided one useful commercial benchmark when it announced its acquisition of Diligent Robotics in January 2026: it said hospital facilities deploying Moxi were expected to generate approximately US$200,000 to US$400,000 in annual sales per facility.

That number should not be interpreted as the price of one Moxi robot.

A hospital deployment can include multiple robots, software, implementation, workflow configuration, support, maintenance and other services. The figure is therefore much closer to a facility-level commercial benchmark than an MSRP.

The robot price is not the project price

A hospital should model Moxi as an operational programme.

Potential cost layers include:

A better way to request Moxi pricing

Ask Diligent for three numbers:

1. Initial deployment cost: everything required to put the first approved workflows into production.
2. Annual operating cost: recurring robot, software, connectivity, support and maintenance charges.
3. Expansion cost: the cost of adding another robot, workflow, floor or hospital site.

Then calculate value using the hospital’s current operation.

If staff currently perform 150 internal runs per day and each run consumes an average of 15 productive minutes, that represents a fundamentally different business case from a facility performing 20 short runs each day.

Do not calculate ROI from the number of robots. Calculate it from the workload that disappears from people.

What Is Moxi 2.0?

Moxi 2.0 is the second generation of Diligent Robotics’ autonomous mobile manipulation platform for hospitals.

The robot combines:

• A wheeled autonomous mobile base.
• Onboard perception and navigation.
• A robotic arm and end effector.
• Secure storage drawers.
• Human-facing interaction features.
• Hospital workflow software.
• Cloud-based fleet learning and model improvement.

Its primary purpose is moving items so clinical professionals do not have to leave higher-value work to perform routine transport.

Typical items include:

• Medications.
• Laboratory samples.
• PPE.
• Patient supplies.
• Lightweight equipment.
• Items from central supply.
• Discharge medications.

What Moxi 2.0 is

• An autonomous hospital logistics robot.
• A mobile manipulator capable of interacting with parts of a human-designed building.
• A system designed for multi-floor hospital operation.
• A tool for reducing repetitive transport work.
• A managed hospital deployment rather than a hobbyist development platform.
• A source of fleet data that Diligent can use to improve its autonomy models.

What Moxi 2.0 is not

• It is not a replacement nurse.
• It does not diagnose patients.
• It does not prescribe or administer medication.
• It is not a patient-lifting robot.
• It is not a surgical robot.
• It is not a general warehouse AMR designed to move pallets.
• It is not an outdoor delivery robot.
• It is not a consumer robot.
• It is not a generic development platform intended for buyers to rewrite the entire control stack.
• It is not proof that every internal hospital delivery should be automated.

If you are evaluating the broader category rather than one platform, compare current medical robots and service robots before choosing a technology.

Moxi 2.0 vs Original Moxi: What Changed?

The second-generation platform is a substantial hardware and autonomy update rather than a cosmetic redesign.

What matters most?

The most commercially important upgrade may not be the headline compute figure.

It is recovery from the situations that previously required intervention.

Hospital automation loses value quickly if staff frequently need to rescue a robot from blocked corridors, unusual elevator situations, temporary furniture, delivery carts or unexpected human traffic.

Moxi 2.0’s faster perception and new model architecture are intended to reduce those interventions and allow the robot to move more confidently.

That can improve:

• Task completion.
• Delivery time.
• Fleet utilisation.
• Effective robot capacity.
• Staff trust.
• Scalability within one site.

A robot that moves slightly faster but needs frequent assistance can be less productive than a slower robot that consistently completes the workflow.

Moxi 2.0 Specifications

Diligent Robotics publishes fewer conventional mechanical specifications than manufacturers selling general-purpose AMRs.

That is partly because Moxi is marketed around hospital workflow outcomes rather than raw payload, speed or chassis dimensions.

The following table separates what is publicly documented from what buyers still need to request.

Specifications buyers should request

Before approval, request written confirmation of:

• Overall dimensions and turning envelope.
• Robot weight.
• Maximum drawer payload.
• Individual drawer dimensions.
• Permitted item weight.
• Maximum supported travel speed.
• Minimum corridor width.
• Minimum door dimensions.
• Supported floor slopes and thresholds.
• Operating-temperature range.
• Environmental and ingress-protection limits.
• Exact charging time.
• Battery warranty and replacement interval.
• Cleaning and infection-control procedure.
• Emergency-stop and recovery behaviour.

A hospital buying decision should not require these values to be guessed from photographs or specifications for the previous generation.

Navigation, Elevators and Hospital Mobility

Navigation is the core of Moxi’s value.

Warehouses can usually be optimised around automation. Hospitals cannot.

A hospital corridor may contain:

• Patients.
• Visitors.
• Nurses and physicians.
• Beds.
• Wheelchairs.
• IV poles.
• Medication carts.
• Cleaning equipment.
• Temporary signage.
• Supply carts.
• Emergency traffic.

The environment can change minute by minute.

Moxi 2.0’s faster perception is designed specifically around this problem.

Why 10–15× faster perception matters

A faster perception stack can shorten the time between:

1. Sensing a change.
2. Understanding the scene.
3. Selecting a response.
4. Updating motion.

That does not automatically mean the robot travels 10–15× faster.

It means the system can potentially react more quickly and confidently to dynamic conditions.

Examples include:

• A bed entering the corridor.
• A person stepping into the robot’s path.
• An elevator opening while people exit.
• A cart being moved into a previously clear route.
• A temporary obstruction appearing near a doorway.

Can Moxi 2.0 use elevators?

Yes.

Multi-floor hospital operation is one of the platform’s core design requirements.

Moxi has historically been able to operate elevators and doors, allowing deliveries to cross floors without a staff member escorting the robot.

This capability is particularly valuable because many of the strongest hospital logistics use cases involve moving items between departments that are physically separated.

A medication journey might involve:

Pharmacy → elevator → inpatient floor → nursing unit.

A laboratory workflow could involve:

Clinical unit → elevator → central laboratory.

Without autonomous elevator use, much of the labour-saving opportunity disappears.

Test the real elevators—not the demo elevator

Hospitals should test:

• Every elevator bank included in the project.
• Call behaviour.
• Waiting behaviour.
• Entry and exit timing.
• People entering before the robot.
• People blocking the door.
• Full elevators.
• Bed transport.
• Priority or emergency modes.
• Network outages.
• Fire-service modes.
• Elevator maintenance periods.

The correct buying question is not “Can Moxi use elevators?”

It is:

Can the proposed deployment reliably use our elevators under the conditions it will encounter every day?

Moxi 2.0 Arm, Drawers and Mobile Manipulation

The arm is one of Moxi’s most important differences from simpler delivery AMRs.

A normal indoor courier robot can navigate from A to B and open a motorised compartment.

Moxi is designed to physically interact with its surroundings.

Diligent describes Moxi as being able to grab, pull, open and guide objects.

This allows a workflow to extend beyond navigation alone.

Why mobile manipulation matters in hospitals

Hospitals were built for people.

Interfaces therefore frequently exist at human height and require physical interaction.

Examples can include:

• Door handles.
• Elevator interfaces.
• Cabinets.
• Drawers.
• Workflow equipment.

The mobile manipulator architecture gives Diligent another way to automate these environments without redesigning every building around the robot.

The arm is not an industrial robot arm

Do not interpret Moxi’s mobile manipulation capability as equivalent to a high-payload industrial manipulator.

Diligent does not publish a general payload, reach, repeatability or force specification for the Moxi 2.0 arm in its current launch material.

For this reason, the buyer should evaluate manipulation at the workflow level.

Ask:

• What object must be moved?
• What does it weigh?
• Where is it located?
• What force is required?
• Does the robot grasp it or only push/pull an interface?
• How often does the action succeed?
• What happens after a failed attempt?

Storage drawers

Moxi 2.0 includes redesigned storage intended to support hospital delivery workflows.

The redesign should be evaluated for:

• Usable internal volume.
• Maximum permitted load.
• Number of separate deliveries.
• Secure access.
• Cleaning.
• Medication chain of custody.
• Specimen containment.
• Visibility into drawer status.
• Audit logging.

The current public launch material does not provide enough information to assume compatibility with every medication, specimen, blood product or temperature-sensitive item.

Clinical governance must approve each workflow.

Moxi 2.0 AI, World Model and Autonomous Capabilities

Moxi 2.0 is an example of physical AI being applied to a narrow commercial problem rather than a general-purpose demonstration.

Its most interesting software update is Diligent’s new robotic World Model.

The idea is that data generated by robots operating in real hospitals feeds back into a common training system.

New model versions can then improve how the fleet understands and responds to hospital environments.

The learning flywheel

The cycle is approximately:

1. Moxi robots operate in hospitals.
2. The fleet encounters real-world situations and edge cases.
3. Upgraded sensors capture richer data.
4. Deployment experience flows into Diligent’s training infrastructure.
5. Models improve.
6. Updated software returns to deployments.
7. The improved fleet generates more useful experience.

This is strategically important.

Many robotics companies face a data problem: they need capable robots to generate real deployment data, but they need real deployment data to create capable robots.

Diligent entered Moxi 2.0 with an existing commercial fleet and years of hospital operations.

What the World Model does not mean

It does not mean Moxi is a general artificial intelligence.

Moxi 2.0 should still be evaluated around validated workflows.

A hospital should distinguish between:

• A behaviour included today.
• A capability demonstrated by Diligent.
• A capability under development.
• A future model improvement.
• A workflow proven at another hospital.
• A workflow validated at the buyer’s own site.

Only the last item confirms local operational fit.

NVIDIA Isaac Sim and Cosmos

Diligent says Moxi 2.0 was developed using NVIDIA Isaac Sim and elements of NVIDIA Cosmos, including technology related to 3D LiDAR representation.

Simulation is useful because it allows autonomy systems to encounter many situations without physically sending a robot through a hospital for every test.

Real deployment remains essential, however, because hospital behaviour is difficult to simulate completely.

AWS training infrastructure

Diligent says the cloud infrastructure behind its learning flywheel was built with AWS and that its World Model was trained using Amazon SageMaker HyperPod.

This creates a split architecture:

• Robot: perception, autonomy and safety behaviour operate onboard.
• Cloud: large-scale fleet data and model-training workflows improve future software.

That distinction matters for hospital resilience.

A temporary Wi-Fi outage should not imply that the robot immediately loses the ability to navigate safely.

Hospital Integration and Implementation

Moxi 2.0 is designed to avoid the infrastructure burden associated with traditional fixed automation.

Diligent says it can work within existing hospital infrastructure without specialised automation systems or a major facility rebuild.

That does not mean implementation requires no work.

A production deployment normally touches several hospital groups.

How long does deployment take?

Diligent’s general Moxi material has described implementation in as little as approximately 12 weeks.

Treat “as little as” as a best-case implementation benchmark rather than a guaranteed delivery date.

Actual timing can depend on:

• Commercial contracting.
• Hospital approval processes.
• Cybersecurity review.
• Networking.
• Workflow mapping.
• Elevator interfaces.
• Secure doors.
• Mapping.
• Staff training.
• Clinical validation.
• Acceptance testing.

Start with workflows—not maps

One common robotics mistake is beginning with:

Where can the robot drive?

The better starting question is:

Which repetitive transport workflow consumes enough staff time to justify automation?

Once that workflow is identified, determine whether Moxi can perform every step reliably.

Moxi 2.0 Battery Life, Charging and Duty Cycle

Battery performance is one of the clearest upgrades in Moxi 2.0.

Diligent publishes:

• Up to nine hours of runtime at a time.
• Up to 18 hours of operation per day.
• 30% faster charging than the previous generation.

That is strong endurance for a mobile manipulator operating continuously in an indoor service environment.

Nine hours does not mean nine hours of deliveries

Runtime and productive time are different.

A shift includes:

• Waiting for tasks.
• Travelling to pickup locations.
• Waiting for staff.
• Elevator delays.
• Blocked routes.
• Charging.
• Software or workflow exceptions.

Hospitals should therefore calculate:

completed useful tasks per operating hour

rather than simply comparing battery specifications.

How many robots does a hospital need?

Fleet size depends on the arrival rate of tasks.

If all demand is evenly spread through the day, a small fleet may handle substantial volume.

If the pharmacy generates a large spike of deliveries at the same time each morning, peak capacity may determine fleet size.

Model at least:

• Average tasks per hour.
• Peak tasks per hour.
• Average route time.
• Pickup waiting time.
• Drop-off waiting time.
• Elevator delay.
• Charging windows.
• Robot availability.
• Percentage of failed or interrupted tasks.

This gives a much better fleet estimate than “one robot per floor.”

Moxi 2.0 Safety, Security and Operating Limitations

Hospital robots operate in an unusually sensitive environment.

A navigation failure in an empty warehouse and a navigation failure beside a patient bed are not equivalent.

Moxi therefore needs to be evaluated as part of the complete hospital work system.

Onboard safety and autonomy

Diligent says Moxi 2.0 runs safety and autonomy behaviours onboard.

The robot can therefore continue executing its core task even when Wi-Fi connectivity is unavailable.

Cellular connectivity can provide fallback coverage where hospital networks have dead zones.

This architecture reduces—but does not eliminate—network-related operational risk.

Hospital risk assessment

Validation should include:

• People unexpectedly crossing the route.
• Children.
• Patients with mobility limitations.
• Wheelchairs.
• Beds.
• IV equipment.
• Carts.
• Blocked corridors.
• Wet floors.
• Emergency traffic.
• Closed or malfunctioning elevators.
• Network loss.
• Robot faults.
• Unsecured cargo.
• Failed deliveries.

HIPAA, SOC 2 and TX-RAMP

Diligent publicly lists healthcare-oriented security credentials including:

• HIPAA compliance.
• SOC Type II compliance.
• TX-RAMP Level 2 certification.

These are positive indicators, but they do not remove the hospital’s own cybersecurity responsibilities.

The buyer should still review:

• Camera and sensor data.
• Patient information exposure.
• Network segmentation.
• User accounts.
• Remote support access.
• Cloud data flows.
• Data retention.
• Software updates.
• Logging.
• Incident notification.
• Third-party subprocessors.

Medication and laboratory workflows

Not every medication or specimen should automatically be approved for robotic delivery.

Confirm:

• Chain of custody.
• Controlled substances.
• Temperature-sensitive items.
• Urgent or STAT items.
• Blood products.
• Biohazard containment.
• Authentication at pickup.
• Authentication at delivery.
• Failed handoff procedure.

The robot does not replace hospital policy.

What Real-World Moxi Deployments Show

Moxi’s strongest competitive advantage is that this is not a first hospital experiment.

By January 2026, Serve Robotics said approximately 100 Moxi robots had completed more than 1.25 million autonomous deliveries across more than 25 hospital facilities.

That is unusually substantial deployment experience for a mobile manipulator working directly in human environments.

However, there is an important distinction.

Most of this evidence was generated by the previous Moxi platform.

Moxi 2.0 only began its formal rollout to health-system customers in August 2026.

Where is Moxi 2.0 operating?

Diligent announced the first Moxi 2.0 rollout to health systems including:

• Endeavor Health Edward Hospital.
• Providence Saint John’s Health Center.
• Children’s Hospital Los Angeles.

Additional U.S. deployments are planned, and Diligent says it is currently taking orders from health systems.

What the evidence proves

• Hospital staff generate enough repetitive point-to-point transport work to create a real automation opportunity.
• Moxi’s general workflow has already been commercialised beyond isolated pilots.
• Robots can operate across complex multi-floor hospitals for extended periods.
• Hospitals can expand fleets after initial adoption.
• Pharmacy, laboratory and supply workflows are practical use cases.
• The original platform has generated a substantial real-world autonomy dataset.

What it does not prove

• That every hospital will achieve the same labour savings.
• That every Moxi delivery replaces paid labour one-for-one.
• That every workflow is suitable for automation.
• That a small clinic will achieve positive ROI.
• That Moxi 2.0 will immediately outperform the previous generation by the same factor as its compute improvement.
• That long-term Moxi 2.0 reliability has already been independently established.

The peer-reviewed evidence is thinner than the deployment evidence

This distinction matters.

Academic reviews of collaborative robots in nursing have repeatedly noted that real-world commercial deployment has moved faster than rigorous peer-reviewed evaluation.

A 2026 Journal of Medical Internet Research paper reviewing healthcare robotics evidence cited historical Moxi pilots, including reports of faster medication delivery, while also noting that rigorous real-world evidence for nursing robotics remains limited.

That does not negate Moxi’s commercial deployment numbers.

It means buyers should separate:

operational case studies

from

independent clinical or human-factors evidence.

The best hospital procurement process should use both.

Best Uses for Moxi 2.0

1. Pharmacy medication delivery

One of the strongest use cases.

Hospital pharmacies generate frequent point-to-point runs, often over long distances and between floors.

The economic case becomes particularly attractive when qualified staff currently interrupt higher-value work to transport medications.

Moxi can support inpatient pharmacy workflows and programmes such as Meds-to-Beds, subject to hospital security and medication-governance requirements.

2. Laboratory sample transport

Moxi can move laboratory samples between clinical departments and laboratories.

This is especially relevant where:

• A pneumatic tube system does not reach every department.
• Some specimens should not be sent through a tube.
• Staff currently walk samples manually.
• Cross-floor transport creates long round trips.

3. Central supply runs

Clinical teams frequently need items that are not stocked locally.

A nurse leaving the floor to obtain one item creates more cost than the walking time alone.

The remaining team must cover the interruption.

Moxi can move supplies from central storage to clinical units without sending clinical staff on the trip.

4. PPE and lightweight equipment distribution

Routine distribution of PPE and suitable equipment can create predictable repetitive routes.

These workflows are attractive when:

• Item sizes fit Moxi’s storage.
• Demand is frequent.
• The pickup location is standardised.
• Delivery destinations are repeatable.

5. Discharge-medication workflows

Getting medication to the right patient or unit at discharge can affect hospital throughput.

A robot that removes transport delay can support Meds-to-Beds and similar programmes without using a staff member as a courier.

6. Multi-floor hospital logistics

This is where Moxi has the greatest advantage over a simple same-floor courier robot.

Elevator use allows one robot to serve multiple departments and floors.

The value grows as walking distance and vertical transport increase.

7. After-hours internal delivery

Hospitals do not operate on a nine-to-five schedule.

Moxi 2.0’s extended operating profile can support evening and other long-shift workflows where staffing is thinner and routine transport still exists.

8. Large health-system automation programmes

The platform becomes strategically more interesting when a health system can standardise workflows across multiple hospitals.

A successful design can potentially be reproduced across:

• Pharmacy.
• Laboratory.
• Supply chain.
• Discharge.
• Clinical support.

The larger opportunity is therefore not one robot replacing one walking task.

It is creating a repeatable internal logistics layer across a health system.

When Moxi 2.0 Is Not the Right Robot

Moxi should be rejected when the actual requirement points to another technology.

• Heavy cart transport: a high-capacity hospital AMR such as an Aethon TUG platform may be more appropriate.
• Patient lifting or transfer: use purpose-built patient-handling equipment.
• Direct clinical care: Moxi does not diagnose, treat or replace a clinical professional.
• Surgery: use an approved surgical robotic platform for the intended procedure.
• Very small facilities: there may not be enough internal transport volume to justify a dedicated programme.
• Short same-room movement: automation adds little value if staff already travel only a few metres.
• Bulk laundry, waste or meal carts: high-capacity cart-moving robots can be a better fit.
• Outdoor transport: Moxi is an indoor hospital robot.
• Fixed high-volume routes: a pneumatic tube, conveyor or fixed automation system may be faster.
• No implementation owner: even a capable robot will fail commercially if nobody owns workflow integration and adoption.

The correct robot is not the one with the most AI.

It is the system that removes the target workload with the lowest total operational complexity.

Moxi 2.0 Alternatives: Aethon TUG, Relay and Hospital Transport Automation

Moxi 2.0 is not competing against one identical robot.

Hospitals have several fundamentally different ways to automate internal transport.

Choose Moxi 2.0 when…

The hospital needs a relatively flexible robot that can move through human spaces and interact physically with existing infrastructure.

Choose Aethon when…

The primary requirement is moving large quantities of material or carts.

Aethon’s T3XL, for example, is designed around loads far beyond the scale of a Moxi drawer.

Choose Relay when…

The use case is relatively straightforward point-to-point delivery and does not require Moxi’s level of mobile manipulation.

Choose a pneumatic tube when…

The items are compatible, routes are fixed and extremely fast repetitive transport is required.

The smartest hospital will often use several of these technologies together rather than choose one platform for every logistics problem.

Is Moxi 2.0 Worth It?

Moxi 2.0 is worth serious consideration when a hospital can identify enough repetitive internal transport to keep the robot productively utilised and when those tasks are currently consuming expensive clinical or operational labour.

The technology is much harder to justify when the hospital starts with enthusiasm for robotics and searches for a problem afterward.

Where the value comes from

Potential value includes:

• Nurse time returned to patient-facing work.
• Pharmacy staff spending less time on transport.
• Laboratory staff remaining in the laboratory.
• Reduced walking distance.
• Fewer interruptions.
• More predictable delivery workflows.
• After-hours transport capacity.
• Improved ability to scale internal logistics without adding equivalent courier labour.

Do not call all saved minutes “labour savings”

This is one of the biggest ROI mistakes in service robotics.

If a nurse saves 12 minutes because Moxi performs a delivery, the hospital has not automatically reduced payroll by 12 minutes.

The value may appear as:

• More patient-facing time.
• Fewer interruptions.
• Reduced overtime.
• Higher capacity.
• Improved staff satisfaction.
• Faster discharge.
• Reduced reliance on couriers.

These benefits can still be economically important.

They simply need to be measured honestly.

A practical Moxi ROI test

Before requesting a proposal, run a two-week baseline study.

Record:

1. Every candidate delivery.
2. Origin.
3. Destination.
4. Item type.
5. Who performs it.
6. Walking and waiting time.
7. Total task time.
8. Urgency.
9. Time of day.

Then calculate:

annual automatable staff hours × realistic value per recovered hour.

Compare that with the complete annual Moxi programme cost.

A simple buying test

Complete this sentence:

We want Moxi because our staff currently complete approximately ______ repetitive internal deliveries each week, consuming ______ staff hours, and we believe ______% can be automated.

If the hospital cannot fill in those numbers, it is too early to choose the robot.

Moxi 2.0 Buying Checklist

1. Measure current deliveries. Establish baseline route volume before discussing robot quantity.
2. Choose the first workflows. Pharmacy, laboratory and central supply are common candidates.
3. Map origins and destinations. Include every pickup and drop-off location.
4. Measure route time. Record walking, waiting and elevator time.
5. Check item compatibility. Document size, weight, security, temperature and containment.
6. Confirm Moxi 2.0. Make sure the proposal clearly identifies the second-generation platform.
7. Request technical specifications. Obtain dimensions, payload, drawer capacity, speed and environmental limits in writing.
8. Audit elevators. Test every lift required by the workflow.
9. Audit doors. Include secure, automatic and fire doors.
10. Review networking. Test Wi-Fi roaming and cellular fallback.
11. Complete cybersecurity review. Document data, accounts, cloud access and updates.
12. Review clinical governance. Define permitted medications, samples and other cargo.
13. Define infection-control requirements. Include cleaning and contamination procedures.
14. Select charging locations. Avoid obstructing clinical traffic.
15. Calculate peak capacity. Fleet size must handle demand spikes, not only averages.
16. Define exception handling. Decide what happens when the robot cannot complete a task.
17. Agree acceptance tests. Use real routes, lifts, traffic and cargo.
18. Request total annual cost. Include software, service, maintenance and implementation.
19. Agree KPIs. Measure completion rate, task time, interventions and staff time returned.
20. Plan expansion. Define the commercial cost of adding workflows, robots and hospital sites.

Pro tip: do not accept a generic demonstration as the final acceptance test. Require the proposed Moxi 2.0 deployment to complete representative pharmacy, laboratory or supply runs through the actual hospital routes and elevators it will use after go-live.

How to Buy Moxi 2.0

Moxi 2.0 is currently being rolled out to U.S. health systems and Diligent Robotics says it is accepting orders from additional hospitals.

It is not positioned as a normal ecommerce hardware purchase.

A serious enquiry should include:

• Hospital or health-system name.
• Location.
• Number of beds.
• Number of buildings and floors.
• Initial target workflows.
• Estimated deliveries per day.
• Operating hours.
• Key pickup locations.
• Key destinations.
• Elevator requirements.
• Door and access-control requirements.
• Expected implementation date.
• Required security review.
• Required support level.

Before signing, request:

• Exact robot generation and hardware configuration.
• Complete statement of work.
• Robot quantity.
• Approved workflows.
• Technical specification sheet.
• Implementation responsibilities.
• Door and elevator scope.
• Networking requirements.
• Cybersecurity documentation.
• Clinical workflow assumptions.
• Cleaning instructions.
• Maintenance schedule.
• Battery replacement policy.
• Software and cloud charges.
• Support SLA.
• Uptime commitments if applicable.
• Training.
• Go-live criteria.
• Acceptance test.
• Expansion pricing.
• Termination or renewal terms.

Review the Moxi product page at Anton Robots, then contact Anton Robots if you want help defining the requirement or comparing hospital logistics options.

If the requirement is not yet sufficiently defined, use Find My Robot before committing to one platform.

What Is New for Moxi in 2026?

Moxi 2.0 entered commercial rollout

The most important development is simple: Moxi 2.0 is no longer only an announced next-generation platform.

Diligent announced on 17 August 2026 that deployment had begun with U.S. health-system customers.

Initial named sites include Endeavor Health Edward Hospital, Providence Saint John’s Health Center and Children’s Hospital Los Angeles.

10× onboard compute

The new generation substantially increases edge-compute capacity.

This allows Diligent to run more capable perception and autonomy models directly on the robot.

10–15× faster perception

Diligent says Moxi 2.0 can perceive and interpret the hospital environment approximately 10–15 times faster than the previous generation.

This is intended to improve behaviour in crowded, changing corridors.

Robotic World Model

Moxi 2.0 introduces Diligent’s new World Model and learning flywheel.

The objective is to use real fleet experience to continuously improve navigation, task execution and recovery.

Longer operating hours

Runtime increases to as much as nine hours at a time, with up to 18 hours of operation per day.

Charging is also reported to be 30% faster.

Upgraded sensors and storage

The second generation introduces a broader perception suite and redesigned delivery storage.

Improved physical ergonomics

Handles and user interaction points were redesigned using feedback from nursing and pharmacy teams that already work with Moxi.

Serve Robotics acquisition

Serve Robotics acquired Diligent Robotics in 2026.

This matters because the combined organisation now operates autonomous robots in two very different human environments: public sidewalks and hospitals.

The long-term objective is to share autonomy, data and infrastructure across those physical-AI operations.

One specification deserves clarification

Diligent’s October 2025 Moxi 2.0 unveiling discussed NVIDIA’s newer Thor platform and its future potential.

The actual August 2026 rollout announcement specifically identifies NVIDIA-powered A2000 compute in the currently deployed Moxi 2.0.

Buyers should therefore base procurement on the hardware named in their actual quotation rather than assuming every technology mentioned in earlier development announcements is included in the shipping robot.

Moxi 2.0 FAQ

What is Moxi 2.0?

Moxi 2.0 is Diligent Robotics’ second-generation autonomous hospital logistics robot. It combines autonomous wheeled mobility, storage and a robotic arm to move medications, samples, supplies and other suitable items through hospitals.

Who makes Moxi 2.0?

Moxi is developed by Diligent Robotics, an Austin-based robotics company that became part of Serve Robotics in 2026.

How much does Moxi 2.0 cost?

Diligent does not publish a fixed Moxi 2.0 retail price. Hospitals receive commercial proposals based on their deployment. Serve Robotics has publicly said Moxi deployments were expected to generate approximately US$200,000–US$400,000 in annual sales per hospital facility, but that is not a per-robot MSRP.

Can you buy Moxi 2.0?

Yes. Diligent Robotics began rolling Moxi 2.0 out to U.S. health systems in August 2026 and says it is taking orders from additional healthcare customers.

What hospitals are using Moxi 2.0?

Initial Moxi 2.0 rollout sites named by Diligent include Endeavor Health Edward Hospital, Providence Saint John’s Health Center and Children’s Hospital Los Angeles.

How is Moxi 2.0 different from the original Moxi?

The second generation has approximately 10× more onboard compute, 10–15× faster perception, improved autonomy and recovery, longer operating hours, faster charging, upgraded cameras and sensors, redesigned storage and a new robotic World Model.

What processor does Moxi 2.0 use?

Diligent’s August 2026 rollout announcement identifies upgraded NVIDIA-powered A2000 compute.

Does Moxi 2.0 use NVIDIA Thor?

Diligent discussed NVIDIA Thor when unveiling its next-generation architecture in 2025. The August 2026 commercial rollout announcement specifically states that deployed Moxi 2.0 units use upgraded NVIDIA-powered A2000 compute. Confirm the actual compute module in the quotation.

How long does Moxi 2.0 run?

Diligent publishes runtime of up to nine hours at a time.

How many hours can Moxi 2.0 operate per day?

Diligent says Moxi 2.0 can support up to 18 hours of operating time per day.

How fast does Moxi 2.0 charge?

Diligent says charging is approximately 30% faster than the previous Moxi generation. A complete zero-to-full charging time has not been publicly specified in the current launch material.

What can Moxi deliver?

Typical Moxi workflows include medications, laboratory samples, PPE, supplies, lightweight equipment and other suitable hospital items.

Can Moxi deliver medication?

Yes. Medication delivery is one of Moxi’s established hospital workflows. Individual hospitals must define security, chain-of-custody and medication-handling rules.

Can Moxi carry laboratory samples?

Yes. Laboratory specimen transport is an established use case, subject to the hospital’s handling, containment and clinical-governance requirements.

Can Moxi use elevators?

Yes. Multi-floor autonomous hospital operation is a core Moxi capability. The exact elevator interface should be validated at the deployment site.

Can Moxi open doors?

Moxi is designed to interact with hospital doors and other elements of the built environment using its mobility and manipulation capabilities.

Does Moxi have a robotic arm?

Yes. Moxi is a mobile manipulator rather than a simple delivery AMR.

How much can Moxi carry?

Diligent does not publish a general Moxi 2.0 payload figure in its current public launch information. Obtain drawer and payload limits in writing before approving a workflow.

How fast is Moxi 2.0?

A maximum travel speed is not publicly specified in the current Moxi 2.0 launch material.

How big is Moxi 2.0?

Complete dimensions are not currently published in Diligent’s main Moxi 2.0 launch information. Buyers should request the latest technical drawing.

Is Moxi autonomous?

Yes. Moxi is designed to autonomously navigate hospital environments and complete configured logistics workflows. It is not a general-purpose AI capable of performing arbitrary hospital tasks.

Does Moxi need Wi-Fi?

Connectivity is part of the deployment, but Diligent says safety and autonomy behaviours run onboard. Moxi 2.0 can therefore continue core operation when Wi-Fi is unavailable, and cellular fallback can help in network dead zones.

Does Moxi require hospital renovations?

Diligent says Moxi 2.0 can operate without major facility modifications or specialised automation infrastructure. Site work may still be required for networking, doors, elevators, charging locations or workflow integration.

How long does Moxi take to deploy?

Diligent has described Moxi implementation in as little as approximately 12 weeks. Real deployment time depends on contracting, IT, facilities, security, workflow design and hospital approvals.

Is Moxi HIPAA compliant?

Diligent publicly states that its organisation/platform is HIPAA compliant and also lists SOC Type II compliance and TX-RAMP Level 2 certification. Hospitals should request current documentation during security review.

Does Moxi replace nurses?

No. Moxi is designed to remove routine non-clinical transport work so nurses and other healthcare professionals can spend more time on higher-value clinical tasks.

Can Moxi interact with patients?

Moxi operates in shared hospital spaces and has human-facing social design features, but its core commercial purpose is non-patient-facing logistics rather than delivering clinical care.

How many Moxi robots are deployed?

Serve Robotics said in early 2026 that nearly 100 Moxi robots were operating across more than 25 hospital facilities. Moxi 2.0 itself only began formal rollout in August 2026, so the majority of that installed base represented the previous generation.

How many deliveries has Moxi completed?

The Moxi fleet had completed more than 1.25 million autonomous hospital deliveries by early 2026.

Does Moxi really save staff time?

Hospital and manufacturer case studies report substantial staff time returned. Children’s Hospital Los Angeles, for example, reported more than 40,000 Moxi deliveries representing more than 16,000 hours of transport work staff did not have to perform. Results will vary by site and workflow.

What is the best Moxi alternative?

Choose Aethon T3/T3XL when bulk material or cart transport is the priority, Relay for simpler secure point-to-point deliveries, or fixed systems such as pneumatic tubes where high-frequency transport follows permanent routes.

Is Moxi 2.0 worth buying?

It can be a strong investment for large hospitals with high-volume repetitive internal logistics. It is much harder to justify for small sites with short routes or low task frequency. Measure the existing workload before requesting fleet size or pricing.

Final Verdict: Should You Buy Moxi 2.0?

Shortlist Moxi 2.0 if your hospital has enough repetitive pharmacy, laboratory, supply or equipment transport to justify a dedicated autonomous logistics programme.

The robot’s strongest argument is not that it looks human-friendly or uses a World Model.

It is that Diligent has already spent years operating mobile manipulators inside real hospitals.

That deployment history gives Moxi 2.0 something many newer physical-AI platforms do not yet have: a substantial base of real-world hospital experience from which to build the next generation.

The 2026 upgrade addresses practical bottlenecks.

More compute and 10–15× faster perception should help Moxi deal more effectively with crowded corridors and changing obstacles. Longer battery life and faster charging increase useful availability. Improved recovery can reduce interventions. The World Model creates a mechanism for the fleet to improve from accumulated deployment experience.

There are still important buying limitations.

The price is not public. Many basic mechanical specifications are not publicly listed. Long-term Moxi 2.0 performance data is still developing because the new generation only began customer rollout in August 2026.

Most importantly, Moxi is not valuable simply because it can navigate a hospital.

It is valuable when it removes a measurable amount of repetitive transport from expensive, constrained healthcare staff.

The smartest buying path is therefore workflow-first:

1. Measure existing deliveries.
2. Identify the highest-value automatable routes.
3. Quantify staff time.
4. Test Moxi 2.0 on the actual hospital infrastructure.
5. Agree measurable acceptance criteria.
6. Compare total annual programme cost with realistic operational value.

If that analysis shows hundreds of repetitive cross-department runs each week, Moxi 2.0 can be one of the strongest hospital service-robot options available in 2026.

If the hospital cannot identify that workload, buying the robot first and searching for jobs later is the wrong approach.

Ready to evaluate a deployment? View Diligent Robotics Moxi at Anton Robots or request help comparing hospital automation options.