Implementing Innovative and Efficiency Systems across diverse sectors.

With carbon reduction in focus, we offer tailored AI modelling for businesses and governments.


BCG studies show that the potential overall impact of applying AI to corporate sustainability amounts to $1.3 trillion to $2.6 trillion in value generated through additional revenues and cost savings by 2030.

Energy and Fuel Economy

In a thoughtful analysis, the team from the Allen Institute for AI proposed floating point operations as the most universal and useful energy efficiency metric for researchers to track. Another group created a Maching Learning Emissions Calculator that practitioners can use to estimate the carbon footprints of the models they build (based on factors including hardware, cloud provider, and geographical region). Along these lines, it should become best practice for researchers to plot energy costs against performance gains when training models. Explicitly quantifying this tradeoff will prompt researchers to make more informed, balanced decisions about resource allocation in light of diminishing returns.

Infrastructure and Supply Chain

A significant portion of global greenhouse gas emissions comes from freight transportation. Transportation can also drain a company’s financial resources, such as inefficient shipping routes or vehicles driving empty.By using our bespoke AI platform, we can help reduce these impacts by enabling teams to calibrate production according to fluctuations in variables like weather and continually updated demand forecasts. In addition to charting efficient transport routes, AI-enabled logistics platforms can make recommendations for other ways to improve efficiency, such as consolidating shipments.

Avation and Motorsport

Our bespoke AI platform strives to help your fleets best suited to the changing environmental regulations and thuse streamline processes. Flight data have been used to save major airlines such as AirFrance in excess of US$150 million and 590,000 tonnes of CO2 in 2020.


We are working on yield mapping for agricultural optimisations to find patterns in large-scale data sets and understand the orthogonality of them in real-time – all of which is invaluable for crop planning.