Oceanbolt is data-as-a-service company delivering real-time intelligence for the dry bulk commodities and shipping operations market. The company leverages AIS data, geospatial analytics, third-party data, and machine learning to generate a comprehensive, real-time view of seaborne dry bulk commodities.

As a data business, Oceanbolt is highly focused on data quality and data delivery. Smart algorithms and integration with third-party data sources ensure the most accurate real-time picture of dry bulk trade available today. These insights are delivered via a web-based dashboard or seamlessly via a collection of modern APIs and SDKs.

Oceanbolt was founded in 2019 and is operating as a distributed organization.

Space technology meets aquaculture. Dynaspace advances the transparency of aquaculture by utilizing satellite imagery to provide a cloud based platform with the most comprehensive map of aquaculture operations. This empowers farmers to gain access to the resources they need to ensure environmental and sustainable production.

Dynaspace turns raw data into actionable insights through our cloud-based platform InsightSPHERE. Our insights enable global environmental and sustainable monitoring, directs suppliers of carbon-neutral feed, life improving technology, renewable energy and antibiotic-free health products to farmers, and helps governments to effectively improve food security and resource utilization. InsightSPHERE technology can leapfrog the aquaculture industry by improving farmers’ access to financial and insurance products by providing the critical data needed to de-risk investments.

Floating solar is the next revolution in energy, providing clean energy without using precious land. Glint Solar is are accelerating the growth of floating solar by streamlining the project development process for lake owners and solar developers. Glint Solar uses satellite altimetry and multispectral imagery along with machine learning to find and evaluate the best sites for floating solar, taking into account engineering criteria, local climate conditions, logistics considerations and more.

Glint Solar’s vision is to use the increasing availability of high quality data to reduce the soft costs of renewable energy, starting with floating solar, and thereby accelerating the shift away from fossil fuels

Vake’s vision is to perform ship detections in real-time onboard a network of satellites. This requires a high degree of both innovation and research in order to achieve, both in the machine learning domain and in terms of putting this kind of algorithm onboard satellites.

Vake uses machine learning in satellite imagery to find and classify ships in these images, paying particular focus to those ships that are not voluntarily reporting/disclosing their location. The AIS system is commonly used to track ships worldwide, but it can be easily manipulated or switched off if you have the intention to perform some illegal, illicit or grey area activity at sea. Vake looks at multispectral satellite images made available through the European Space Agency’s (ESA) Sentinel programme. These images contain more information than what is visible to the naked eye.

uSEA is leveraging on satellite communication and autonomous technologies to develop a totally unmanned, all-weather subsea survey system. With their technology they will provide customers with subsea survey at a fraction of the market price, minimal emissions and maximised safety.

With uSEA’s unique concept, they have attracted interest from major industry players and secured support from the Norwegian Council of Research, Innovation Norway, ESA BIC Norway and GCE Ocean Technology. They have also built a growing team and attracted private investors with extensive experience in their domain..

Ntention works with human-machine interaction, and their vision is to capture human intention. Ntention utilize sensor gloves and advanced software, which translates motion data into machine command. In other words, they are not trying to solve a well-defined problem, but rather create a whole new way of interacting with the technology we surround ourselves with, and in this way disrupt the market.

In 2019 Ntention established a research collaboration with NASA HMP (Haughton Mars Project), SETI Institute and Mars Institute. The project “Astronaut Smart Glove” and the collaboration are considered very successful (https://www.marsinstitute.no/astronaut-smart-glove). They are co-authoring research papers following the experiments, due to relese in spring 2020. Ntention have been shortlisted for further research collaboration through NASA HMP 2020.

Orbital Machines develops electric propellant pumps (turbopumps) for small launch vehicles. The electric turbopump has recently become a viable solution for small launchers due to progress in electric motors and battery technology. Compared to the traditional gas turbine pump the electric turbopump is safer, easier to handle and brings the opportunity of standardization which cuts costs significantly.

Orbital Machines vision is to help cut cost and friction in the development/operation of small launchers in order to meet the huge demand for placing small satellittes into orbit. Orbital Machines intends to be a leading supplier of a standardized electric turbopump, cutting cost for the whole industry.

HSAT was founded with the objective of using the very latest satellite technology together with cutting edge data analytics to help business make better decisions.

Their objective is not to simply provide access large volumes satellite data, but to use this data combined with advanced analytics and subject matter expertise to understand and resolve real-world business problems. Hsat aim to provide insights in the form of dashboards, or alerts, or even custom APIs, so that businesses have the right information at the right time – be it traders, insurers, farmers or NGOs

DigiFarm is developing machine learning models to help farmers in the Nordics optimize their crop production. Analyzing crop yield data from over 14,000 active producers in Norway over a period of 11 years, our model helps farmers increase crop yield through optimizing soil-type to crop-type, crop circulation and near real-time yield predictions (NDVI) for individual fields.

Their vision is to become the Nordic’s leading provider of AI based crop production recommendations and data.

The DigiFarm core team’s strengths span from deep agricultural and crop production experience, data science and machine learning to GIS and Remote Sensing engineering, presenting the necessary skills and level of execution in order to be able to complete the project successfully.