AI-powered dirt & hazards detection

Contact us

What IT is

CleanAI is the breakthrough platform for automated dirt & hazards detection.

Combining Machine Learning algorithms with advanced sensors, CleanAI enables our customers to identify issues remotely and respond in real-time.  


CleanAI uses deep neural network models capable of detecting dirt, rubbish, lost belongings, spills and other hazards in different environments.

The extensive data models and custom approach to dirt & hazards detection are unique and result in very accurate detection.


While our detection models can be applied to different imaging sources, we have also created a bespoke sensor that combines 4K image capture with air monitoring to detect harmful particles.

Low-powered and with local processing onboard, the Cleanedge sensor can be deployed in a diverse range of environments.

Battery or mains powered, daylight or low light, it's ready for anything.

Learn More


Shared car fleets


Public transport

Detect dirt, rubbish and belongings left behind in shared cars and corporate fleets. For the shared cars of today and the autonomous vehicles of tomorrow.

With shuttle services becoming increasingly popular, CleanAI provides a smart solution for clean cabins and detecting lost belongings.

Real-time monitoring of rubbish and other hazards in public buses and trains. Enables targeted cleaning for a more enjoyable journey for everyone.

Facilities & hospitality

Robotic sensing

Need a tailored solution?

From corporate & rental properties to factories, construction sites and restaurants - the possibilities for AI to help you maintain cleaner & safer spaces are endless.

CleanAI can be combined with robotics to identify types of dirt & stains and to enable automated & predictive cleaning in the most demanding of environments.

Contact us now to discuss how CleanAI can meet your needs.

Contact us

Contact us

Please enter your email address. Or follow us to learn more.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.