Glint Solar uses satellite data and machine learning to identify and analyze the best greenfield sites.Identify the best sites now
Instead of using GIS tools on one site at the time, our tool allows you to quickly filter through thousands of sites.
Obtain in-depth analysis on the specific site to understand the overall attractiveness. Rate and share with colleagues.
We aggregate up to 40 years of satellite data to give you the most comprehensive insight in your early-stage prospecting.
There is a race to identify the best project sites for the fast-growing floating solar market. In this race, you need the best tools available to gain the competitive edge.
We introduce the world’s first automatic site identification and analysis tool.
Using a combination of satellite data, machine learning and public data, we scan large regions to identify thousands of water bodies.
The interactive product allows you to easily filter sites based on numerous layers such as lake size, distance to grid, installed capacity, land use and many more.
There has never been a better way to do site identification.Request a demo
By drawing upon up to 40 years of satellite data, we provide remote feasibility analysis to help you gain early insight and de-risk greenfield projects.
Among the parameters we analyze are irradiation, wind, waves, temperature, water level fluctuations, water presence, far shading, precipitation, high-level bathymetry and more.
We help you obtain high quality site information from the inception.Book a meeting
To mitigate climate change, the world needs to accelerate the adoption of renewable energy sources like wind and solar.
The UN IPCC report states that 70-85% of the world’s electricity must come from renewable sources by 2050 to avoid the worst impacts of climate change.
At Glint Solar we believe that advanced data science is one of the keys to reach this target.
Lack of knowledge of the project site is a big risk factor that can be very costly.
Every so often truly innovative companies emerge.
Changing the status quo of the industry. Through their novel approach of combining satellite data and machine learning, Glint Solar is one of those companies.
The World Bank assisted the Government of Bangladesh on a feasibility study for floating solar. Having seen many projects start off with poor input data.
The World Bank turned to Glint Solar to obtain the necessary data.
That would ensure the right insight from the project’s inception. Analyzing historical water presence, water level variations, waves, extreme wind and more provided us with significant value in proceeding with the project.
The World Bank
Glint Solar is addressing a major challenge: obtaining reliable data early in the project phase.
We were very impressed with the remote analyses they delivered to us in South America that helped us gain a much deeper understanding of the potential floating PV project sites in that region