Robotics engineered for
real care environments.

Automating the repetitive support work that pulls staff away from care.

Venture Robot Solutions · the film
The bottleneck

Robots can navigate hospitals.
Adoption still stalls.

01

Robots still behave like machines

They hesitate, block the way and pull staff over to help.

02

Healthcare workflows are not generic

Real routes run through lifts, busy corridors and hand-overs, not a straight line.

03

Staff need automation, not another system to manage

The robot should take errands off the ward, not add a screen to watch.

Navigation gets a robot from A to B. Reliable behavior and voice decide whether people use it.

“We did not underestimate the robots. We underestimated what it takes to make them work inside a hospital.”
Facility Manager, Swiss hospital – Kanton Aargau
The system

One system, engineered across three layers.

Hospitals receive an operational robot. VRS controls the layers that decide how it behaves around people.

Current deployment platform Delio is the first physical platform used to deploy and validate the VRS stack in healthcare environments.
  1. 03 CareOS VRS-controlled

    Behavior Engine · safety · human-aware navigation · interaction

  2. 02 VRS sensing & compute VRS-controlled

    Perception · sensors · edge compute · interfaces

  3. 01 Mobile robot platform Replaceable

    Industrial mobility base. Replaceable by design.

Healthcare deployment

Workflow configuration · site validation · monitoring · iteration

Fits the building as it is

No lift interface, no Wi-Fi build-out, no building works.

  • Lift integration Rides the lifts already installed. No controller interface to buy. Not required
  • Full Wi-Fi coverage Missions run on the robot, so Wi-Fi gaps in lifts and basements don’t stop a delivery. No access points to add. Not required
  • Facility adaptation No construction, cabling or rebuilt rooms before go-live. Not required
≈ CHF 30–100k one-time integration cost a hospital avoids per site

Indicative estimate for a route served by 2 lifts, from public 2025–26 price ranges: lift-controller integration CHF 10–35k per lift; closing Wi-Fi gaps along the route with 10–15 access points at CHF 1–2k each, installed. Where a building has no usable Wi-Fi, a full network build-out alone can cost well beyond this. Varies by building; excludes upkeep of the added equipment.

Applications

Start with repetitive staff-support workflows.

Staff support & internal logistics

Deliveries · errands · internal transport · routine runs

Reduce non-care interruptions and give staff more capacity for care.

01 Conversation

More than a touchscreen: Delio talks in German, French or English.

02 Guidance

Reception, wayfinding and escorting visitors to the right ward.

03 Patient / resident engagement

Light social and cognitive activity on the ward.

Primary deployment KPI → staff time returned through automation

Interactive illustration · simulated hospital
Real deployments
Real-world deployment

From staff request to completed mission.

  1. 01 Request
  2. 02 Mission
  3. 03 Perception
  4. 04 Behavior selection
  5. 05 Navigation / interaction
  6. 06 Completion
  7. 07 Replay
Recorded mission On-robot log

A real mission replayed from on-robot logs: floor geometry, the driven trajectory, people as anonymized geometry, and the live behavior mode with its reason code.

Every mission is recorded decision by decision, with a plain-language reason for each one, and can be replayed in 3D.

Fleet management · CareOS

One delivery, from the nurse’s phone to the director’s report.

Dashboard robot list: each robot with its status and battery level
Staff app: a call with Delio, who asks what to bring and where to collect it

Product screens · simulated data

Staff app and operations dashboard run on the same live data, across every robot, floor and site.

Discuss a deployment →
Field validation

Built in the field, not just in the lab.

Completed deployments
Haus Tabea Switzerland · residential care
✓
Swiss Paraplegic Centre Nottwil, Switzerland · rehabilitation clinic
✓
What the field changed
Cross-floor missions Ramps & lifts

The robot takes ramps and elevators, with door and lift state in the decision loop. Floor transitions are the hardest stretch of a hospital route, and the part we engineer most.

Safety record, 47 missions 0 contacts

No person or wheelchair contact. Six near-misses, each corroborated against LiDAR.

Critical failure mechanism 4 days

Identified from mission logs and corrected in the field within four days.

Technology

The technology behind the system.

CareOS

Behavior Engine

  • Deterministic execution
  • Fail-closed safety logic
  • Human-aware navigation
  • Interaction orchestration
  • Mission replay
  • Explainable decisions
VRS sensing & compute
Deployed today in service
  • Slamware platform abstraction
  • ZED 2i stereo depth with LiDAR fusion
  • Jetson Orin Nano compute on the robot
  • On-robot tablet; voice (DE/FR/EN) is the one cloud-assisted function
Next platform · robot #2 in design
  • Jetson AGX Orin
  • Two additional cameras
  • Modular payload back
Design render of robot #2 with the added camera array
Expanded vision Added camera array for robot #2.
Three planned payload configurations: rail interface, closed bay, shelf rack
Modular payload back Rail interface, closed bay or shelf rack, configured per site without a new robot.

Both renders are design work for robot #2, not the robot in service today.

Learning loop

Every deployment improves the next.

  1. 01 Deploy
  2. 02 Observe
  3. 03 Replay
  4. 04 Diagnose
  5. 05 Validate
  6. 06 Update
01 On-device processing

Perception and behavior run on the robot itself, not in a data centre.

02 Mission-level explainability

Every decision carries a reason code and can be replayed in 3D.

03 Versioned behavior updates

Behavior changes ship as versioned updates, validated against recorded missions before they reach a site.

04 Privacy-conscious architecture

Video and perception are processed on the robot. Voice interaction is the one function that uses the cloud; no video or images leave the building.

Our team

Built in Zürich. Backed by research.

  1. 01Team in Zürich
  2. 02Coached by Innosuisse mentors
  3. 03Research with ZHAW
Mentors · Innosuisse
Prof. Dr. Yulia Sandamirskaya
Prof. Dr. Yulia Sandamirskaya Scientific Advisor · ZHAW Prof. of Robotics & Neuromorphic Computing
Ecosystem
Clinical partners
Academic partners
Programs & infrastructure
Deployment

Explore VRS in your care environment.

We start with your workflows, identify where robotic automation can create measurable value, and define the right evaluation format.

How evaluations work
  1. 01 Workflow review

    A short session on your actual routines, volumes and constraints.

  2. 02 Site assessment

    Floors, elevators, doors and corridor traffic reviewed on site.

  3. 03 Scoped evaluation

    A defined evaluation format with agreed metrics, duration and scope.