Achieve 99% accuracy in air quality monitoring with supervised learning
To address flaws of air sensor systems, Gemmo AI have created an API to accurately monitor air quality autonomously.
De-risk your AI investment and have a working solution
in less than six months.
Gemmo streamlines AI integration ensuring that each step from readiness evaluation and use cases identification to feasibility assessment is precise and value-driven, laying the groundwork for successful AI deployment
We craft custom solutions tailored to specific business needs, developing end-to-end pipelines for seamless data flow, creating bespoke algorithms for unique challenges, and managing cloud deployments for scalability and accessibility.
We ensure the longevity and success of AI model with steadfast post-deployment support, routine model maintenance, efficient troubleshooting, and continuous optimisation for peak performance.
Computer vision powered by deep learning help you gain valuable insights from images and videos.
Support your workforce with assistive technology that speeds up every day activity across every department.
Deep Learning combined with proprietary, unique and large-scale datasets unlock value like nothing else.
We sell exclusive licenses, so that our clients fully own the technology. You pay a once-off fee, instead of an ongoing payment.
You will receive measurable results within 2 weeks of starting your AI project.
Our PhD level engineers not only deploy AI but transfer AI know-how to teams, in order to maintain and nourish AI systems in-house.
To address flaws of air sensor systems, Gemmo AI have created an API to accurately monitor air quality autonomously.
Machine Learning is becoming especially relevant in the fight against climate change.
Noise pollution monitoring devices manufacturer Sonitus Systems partnered with Gemmo to design a noise API for sound classification, which automatically
designed and deployed
in the last 4 years
filed by
our Team members
funded by
the European Union
among top
European Universities
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