Objectives of the service
Tesselo’s long-term ambition is to accelerate the world’s transition toward environmental sustainability through geospatial intelligence. We believe geospatial intelligence can efficiently contribute to preserve the planet and fight climate change, through its great potential impact on our production and consumption systems.
Our initial focus is on the timber industry. The timber sector combines serious environmental challenges and untapped business opportunities. Most timber companies are aware of the potential of satellite imagery; however, only very few of them have in-house expertise in this area and remote sensing is not their core business. Due to the technical barriers related to AI and data analysis, it is difficult for them to tap into the potential of remote sensing.
This is where our main value proposition lies: we facilitate the use of artificial intelligence and remote sensing, so that our customers can benefit from the wealth of information within satellite data.
Users and their needs
Our core technical challenge is to run artificial intelligence on top of earth observation data and apply it to business efficiency and environmental sustainability.
Through our platform, we ingest, clean and analyse satellite data. Then, we package it into business insight, immediately actionable by our customers.
For companies in the timber industry, we make it easy and affordable to access and gain insight from earth observation data. Our products and services create value for all the stakeholders of the timber value chain.
We have identified 3 target customers segments:
- Timber producers and transformers
- Timber-based product distributors
- Insurance companies covering the timber sector
We have global reach and are already working with customers in South America, Africa, the United States and Europe.
Service/ system concept
The basis to deliver our services is a cloud based platform that allows to train and run machine learning algorithms at scale and cost efficiently. This platform is agnostic to what the specific applications are and is kept at a general purpose level. It ensures that we are not limited to a single sector or a specific application, but rather that we can scale our approach across sectors.
Our platform is cloud based and has a distributed processing chain that can handle very large volumes of data. This allows us to run our machine learning algorithms over entire countries or even continents.
To adopt the generic part of our platform to our customers, we develop specific application layers. Application layers represent the part of the platform that is specific to one sector, or sometimes one client. This layer is more lightweight and can be developed quickly on top of the base platform.
Illustration: A screenshot of our visualization interface showing one of our cloud-free composites over Lake Tahoe, USA.
Space Added Value
Space assets are the fundament on which we build our business. We process remote sensing information collected by satellites in space. Without these space assets Tesselo would not exist.
Our strength lies in regional analysis, for which we need to access large amounts of satellite imagery covering vast areas. We are using Sentinel-1 and Sentinel-2 data to analyse areas spanning millions of hectares. By combining our cloud based image processing platform with our in-house environmental expertise we are able to deliver unique products to customers with natural resource management challenges.
We strongly benefit from the full and open data policy of the European Union. The cost of doing regional analysis using proprietary imagery is prohibitive for a small company like Tesselo. We could not have gotten our company off the ground without the full and open data from the Copernicus program.
Tesselo has participated in the ESA Business Incubator in Portugal during 2018 and has completed an ESA Kick-start feasibility study in February 2019, and is about to enter the Copernicus Incubation Programme.
The great support Tesselo has received from the ESA community has allowed us to build a MVP which we successfully took to the market.