Hospitals face growing pressure from rising demand, aging populations, chronic disease, and surgical backlogs worsened by COVID-19. At the same time, they struggle with workforce shortages, outdated infrastructure, and slow-moving procurement systems. Infection prevention remains labour-intensive and inconsistent, and most existing UV or HPV disinfection systems are impractical; they require empty rooms and offer no visibility into performance.
Digital infrastructure is also limited. Key processes like disinfection, scheduling, and room tracking are often handled manually, leaving hospitals without reliable data to identify inefficiencies or evaluate improvements. This is especially problematic in operating rooms, where up to two hours per day are commonly lost to avoidable delays.
AVRICS was launched to address these issues by developing and commercializing a CE-marked UV disinfection robot, Violet, designed for safe use in occupied rooms. It delivers traceable, measurable disinfection through AI-powered dose control and optimized navigation. The project also developed foundational infrastructure involving hardware, software, user interfaces, and integration pathway to enable scalable adoption of autonomous systems in hospitals.
Five core objectives guided the project:
(1) Product Development: Deliver a hospital-ready, compliant robot.
(2) Evidence Generation: Validate safety, traceability, and efficacy.
(3) Market Discovery: Identify early adopters and refine GTM strategy.
(4) Adoption Pathway: Build a repeatable pilot-to-procurement model.
(5) Strategic Positioning: Prepare for global scale through team, partners, and investment.
During US market engagement, the team identified a broader need: hospitals lacked objective visibility into workflows. In response, AVRICS developed a privacy-preserving thermal AI sensor that runs all inference at the edge, providing real-time room activity insights without capturing or transmitting identifiable data. Initially built to support the robot, the sensor evolved into a standalone product for measuring baseline inefficiencies and informing operational decisions.
