About my Start-up
Spatialise has developed a soil organic carbon monitor SaaS. The Spatialise SOCMO product estimates topsoil carbon stocks for farmland using satellite data and AI. Customers receive information through an API, along with data visualisations (dashboard) and analytics (standardised reports).
The information benefits various customer segments by reducing project times and costs, minimising the need for physical soil sampling, and providing faster evaluation and decision support for land degradation interventions. Next to that, the information is useful for targeted fertiliser application. Additionally, the data is valuable for carbon insetting and offsetting.
Customer segments include: soil carbon project developers (public and private), farming platforms, and the sustainability reporting industry (Scope 3 emissions).
Spatialise Video: https://youtu.be/vXVUh_tKwt0
Spatialise Leaflet: t.ly/MTYL
Spatialise Pitch deck: t.ly/WROBP
Spatialise Product demonstration: https://youtu.be/Bu0GHab3dqE
Why your idea is a “winner"?:
As an official Wageningen University & Research startup, Spatialise holds a unique position with access to the largest soil sample database through a collaboration agreement, providing a competitive advantage.
Spatialise's Soil Organic Carbon Monitor technology starts with a global base model, trained on all available reference data, and progressively fine-tunes the model in regional zones if sufficient reference data is available. This approach ensures that there is always a base model applicable anywhere while potentially offering locally fine-tuned models that inherit from the base model but are better adapted to local conditions. As such, Spatialise's technology can be applied across different scales, from small farms to entire regions or countries. This enables customers to manage and monitor soil health at the appropriate scale for their needs.
The Soil Organic Carbon Monitor technology's cloud-based application streamlines the process by enabling quick calculations, offering global applicability, and various ways to ensure reliability. With in-house expertise in soil science, remote sensing, and deep learning, Spatialise has developed a powerful data pipeline that can easily incorporate new data sources into our prediction model.
The cutting-edge deep learning techniques, such as Adversarial Learning, Transformers, and Attention, set Spatialise apart in the remote sensing field. The company has also developed a unique solution to address the "black box" issue in deep learning, quantifying uncertainty at the pixel level. These advances in artificial intelligence by Spatialise are a result of 2 years of in-house R&D from scientists affiliated with the renowned CWI.
Spatialise's Soil Organic Carbon Monitor provides reliable information rapidly and flexibly, making it ideal for sustainability reporting frameworks such as ESGs, Scope 3 emissions, or project MRV in regenerative agriculture. The API can connect to any dashboard/platform in a matter of seconds.
What is your current or intended business/revenue model?:
We make money based on pay-per-usage: ≤ 0.30 €/Ha. We still need to develop a value-based price model, however we are very lean and have low marginal costs.
Intended customers are soil carbon projects (private and public), farming platforms and sustainability reporting (Scope 3). The customers' ROI for soil carbon projects is that 'Getting the job done' becomes feasible. Farming platforms ROI: business case to be validated. ESG Sustainability reporting (Scope 3): business case to be validated.
Revenue streams are through API, standardised reports and optionally a subscription to our interface (dashboard).
Current revenue level this year to date is €19000.
Do you have any Patent or IP registered (related to the solution that you are looking for an investment)?:
No.
Has your technology already been implemented in any field/sector?:
Yes.
Yes we have already customers.
Contracts:
– GIZ
– reNature
– Province of Drenthe
– Commonlands
NDA:
– Rabo Carbon Bank
– Kuva Space
Prospects / under negotiation:
– Agreena
– Klim.eco
– Soil Capital
– eAgronom
– Cropin
– CropX
And many more in our customer pipeline ( > 100 prospects).
Customer acquisition currently is organic. We get a lot of request through word-of-mouth, due to publications on Spatialise by externals (LinkedIn posts), events (World Bio Markets, F&A Next) and our (partner) networks.
Which market and customer need(s)/problem(s) is (are) your products(s)/service(s) going to solve?:
Carbon Dioxide Removal (CDR): Efficiently tracking and reporting of the periodical changes in soil organic carbon for customers' fields and project areas: 40x faster and 60x more affordable.
What CDR market problem: Spatialise has found that regenerative agriculture project developers want to measure and report the progress of soil quality through organic matter content.
Project developers cannot achieve this satisfactorily at the moment, because taking soil samples is too expensive and modeling is not scalable. In short, current methods and alternatives are not accurate enough or too expensive to achieve 'getting the job done'.
Based on cost reduction/financial feasibility, prospects are now solving this by taking fewer or no soil samples. The disadvantages of this are that the precision on a large scale does not meet the quality standards to 'get the job done'. As a result, the existence of regenerative agriculture project developers are in danger.
How CDR is enabled: Regenerative farming practices are crucial for decreasing emissions related to agriculture. Spatialise enables them to accurately quantify soil carbon levels that can help companies plan investments and monitor progress by our soil organic carbon monitoring reporting and verification software. In sum, an MRV to create transparency in our industry, validated by soil samples – a lot! Exclusively from our former university (one of our competitive advantages).
Type of CDR we enable: a MRV system. Specifically for land-based emissions and sequestration of carbon, for instance by Nature-Based Solutions and regenerative farming. At any scale, from field to continent.
Team members
Ex-CGI, VanderSat, UNHCR
MSc Geo-Information Sciences & Remote Sensing
BSc International Land & Water Management
Ex-CGI, DB Vision, EagleSensing
MSc Geo-Information Sciences & Remote Sensing
BSc International Land & Water Management
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