Applications for DIHNET’s 1st open call for tech transfer and funding was closed on 15th of September, 2020. In total 79 applications located in specific regions of Norway, Latvia, Poland, Czech Republic, Romania an Bulgaria were submitted in different areas of technology with AI being the top choice for the applicants. From these 79 applications, only 24 of them got the chance to become part of the DIHNET project and receive up to €60,000 each in equity-free funding, alongside technical support from industry experts and business mentoring. The aim of the experiments is to refine new digital solutions that afterwards will help the companies to reach new market potential and scale and increase their region’s digital innovation level.
Romania’s winners
RF Meters was founded in 2019 and is an active member of Transilvania IT cluster, participating in different events organized by the cluster. The company also participated and reached the national final phase at two acceleration programs: InnoEnergy, supported by EIT, and InnovX, where RF Meters is currently in the post acceleration phase. Company’s experiment consists of building a solution to deliver the latest demands in smart metering infrastructures by attaching a module to a smart meter who collects the data from the meter and transmits it through a wireless communication protocol developed by the company to a gateway.
Stressless is a hardware startup, founded in 2017, which in the last 3 years has developed TULLY – a wearable device for monitoring and emotional control for children diagnosed with ADHD. They are focusing on wearable devices for children affected by ADHD or autism, with the aim of helping them cope better with their daily schedule and improving their self control. Shortly described, the experiment Machine Learning for Emotion Regulation (MLER) helps at improving the accuracy and feasibility of emotional flares detection and intervention for emotions regulations, by integrating ML algorithms.
Rofinntech 3D SRL, based in the North-West region of Romania, is a start-up company and a spin-off of the Romanian Institute of Science and Technology (RIST).The company has developed and validated the Artificial Intelligence technologies needed to build an application that can automatically render furniture layout into 2D images of empty rooms (virtual staging). The company’s experiment is a software solution that provides virtual staging services by using artificial intelligence. Rofinntech plans to use the DIHNET support to assemble these blocks into a SaaS application available for end user beta testing.
Solistron is an innovator in the application of technologies that use solar energy. Company’s goal is to provide the correct utility of photovoltaic systems, adapted to client needs. The integrated solutions they offer include both the possibility of the company’s own electricity production and optimal consumption, all of which are carefully coordinated and monitored. By using the latest technologies of Computer Vision and Artificial Intelligence, Solistron develops a system that continuously ensures quality control in real time for printers.
Latvia’s winners
WinGO Deposit was found in 2020 and is a team of green-minded IT specialists and engineers. They were united by the fact that there was no technology in the world capable of collecting not only crushed bottles and cans in a deposit system, as well as other waste, so they created WinGO. Under the tagline „Bins with brains – reverse vending machine (RVM) upgrade for quicker and more precise packaging processing”, WinGO Deposit is developing a new type of RVM to collect all types of used packaging in any condition to boost recycling rates. WINGO Deposit’s solution is part of the CE technical cycle, for instances, when beverage packaging can’t be reused but materials have to be efficiently recovered for recycling.
Semantic Intelligence is an AI-tech company aiming to impact the biopharma value chain and accelerate biopharma’s digital transformation. The company is developing AI-driven state-of-the-art technology, which would be one of the first industry-level solutions for automatic information retrieval and data curation in biochemistry. Their solution enables research-intensive industries, such as chemical and pharmaceutical, to switch from a human resource-intensive to a more automated linguistic-driven data processing model. The solution aims to substantially enhance text mining quality while providing high-level topic-independent linguistic features without relying on high cost GPU-clusters.
CENOS was founded in 2017 by 3 PhDs in physics and mathematics who committed themselves to democratize simulation software by making it easy, affordable, and secure to use by every engineer. They believe the adoption of simulation should go beyond R&D centers of corporates and help engineers at production plants and small manufacturers to bring their engineering to the new level. Given the fact that simulation tools in the manufacturing process are very difficult to use, CENOS company aims to help their customers to calibrate and operate their systems in the most optimal way. CENOS app is an easy to use software that innovates on the manufacturing processes design in software and hardware simulations.
Exponential Technologies Ltd. was founded in 2019 by the 3 co-founders Pavel Cacivkin, Matthias Kaiser and Girts Smelters to further develop and market the AI/ML algorithms developed by Pavel Cacivkin. During this experiment they plan to finalize the development of key functionality and usability features, expand their professional network to attract potential clients, and deploy the AI platform in realistic situations together with research and industrial partners. Company’s product, currently at a prototype stage, is an active learning AI-based cloud platform for bioprocess optimization and management, that enables bioengineers to find novel parameters (bioreactor process configurations, growth media, time dependent variables).
Norway’s winners
VNNOR’s purpose is to bring Artificial Intelligence and Machine Learning (AI & ML) technology advantages to their customers and community through its solutions and services. Company’s mission is to focus on AI & ML for better solutions in healthcare and environmental issues, such as in combating micro-plastic issues and climate changes. Through the experiment, VINNOR AS aims to test out and develop further their new Artificial Intelligence System for Healthcare Workforce Planning that would help municipalities, hospitals and healthcare institutions.
Sensor Innovation is specialising in sensor-based moisture monitoring of new and existing buildings. The company originates from experienced competence environments in the construction industry and leading technology environments. Together with partners and the company’s customer portfolio, they have developed adaptable sensors and associated control systems that continuously monitor and warn of abnormal moisture conditions. Shortly described, the company will develop an intelligent solution based on machine learning to give accurate alerts of water leakages based on sensor data.
Mode Sensors AS is a digital healthcare company redefining the way hydration is clinically diagnosed by combining their wearable biosensing technology with cloud-based data analytics and machine- learning capabilities. Company’s goal is to be the leading provider of hydration monitoring solutions for patients at risk for dehydration/overhydration. The company is developing Re:Balans, the first medical-grade sensor-patch for the non-invasive and real-time monitoring of hydration. The product consists of a connected sensor-patch, advanced signal processing, and an IoT-platform to retrieve, process, and visualize data from the sensor-patch.
Q-free was founded in 1984 and has offices in 16 countries. Company’s mission is creating intelligent solutions for efficient, safe, and environmentally-friendly transportation based on innovative technology and open platforms. The company’s project aims at exploiting full custom integrated circuit building blocks consisting of combinatorial circuits and memory operating in the subthreshold domain, for ultra low power operation.