We use IoT smart sensor networks and machine learning to generate highly accurate and valuable environmental data to help people to live healthier lives

The Problem

Air pollution is the single biggest environmental health risk.

7 million premature deaths annually linked to air pollution. In 2012, an estimated 6.5 million deaths (11.6% of all global deaths) were associated with indoor and outdoor air pollution together1. Air pollution in the United States costs more than $200 billion annually in lost work days and hospital costs2.

1. Source: WHO | 7 Million Premature Deaths Annually Linked To Air Pollution". Who.int. N.p., 2016. Web
2. Source: https://www.idtechex.com/research/reports/environmental-gas-sensors-2017-2027-000500.asp

Our Solution

CleanSpace is an IoT sensor network to monitor air pollution that uses machine-learning to create hyper-local air pollution information to enable people to “see the air they breathe” and to help enterprises and governments improve public health.


Sensyne is our proprietary machine learning software to calibrate sensor networks ensuring data remains accurate and reliable over time, which is critical for environmental monitoring. Sensyne also automates sensor networks to optimise performance and conserve power.