Discover new technologies by our partners

Atmospheric conditions are a crucial consideration when undertaking development activities in an area. To determine temperature, wind velocity and direction, ‘linear’ methods such as radar, lidar or sodar are used. In each of these, atmospheric conditions are calculated at particular points within an area and the values are extrapolated to cover the region. Such methods however, are incapable of accurately producing a detailed 3D model of atmospheric conditions.

We are a Singapore technology startup with a focus in creating smart vision solutions at the edge. We have created a technology that enables developers and system integrators to create facial recognition applications with state-of-the-art recognition accuracy of 99.73% on the Labelled Faces in the Wild (LFW) benchmark with Anti-spoofing feature. From aged photos to poorly illuminated captures, our technology offers you options to deal with any kind of challenging scenario. Unlike traditional facial recognition technology, we use the very best, state-of-the art, deep learning models to deliver you best-in-class performance.

We are a French company that has developed an advanced artificial intelligence (AI)-based platform to accelerate R&D projects in Chemistry and Materials industries. The technology is able to learn complex relationships from your historical R&D data and produce recommendations for the best experiments to perform, in order to develop products that satisfy your requirements and to optimize chemical reactions. The development of new molecules, materials, formulations or chemical reactions requires many trial-and-error experiments and informed guesswork. Our AI technology helps you reduce this number of experiments to a minimum, thereby saving you time and money (by cutting down on manpower spent and resource wastage). You can test your experiment ideas with our software before running them in the laboratory. This means that you can make a decision to run the most promising experiments and save time. This also allows you to be faster than your competitors to develop products in order to satisfy the needs of your customers.

Age-related macular degeneration (AMD) is a progressive retinal disease that is the leading cause of central vision loss in developed countries, affecting 1 in 10 people older than 50 years. AMD is characterised by abnormal formation of blood vessels (angiogenesis) at the back of the eye. These leak fluid and blood into the ocular tissue eventually causing retinal detachment and vision loss. The pro-angiogenic vascular endothelial growth factor (VEGF) is a major driver of new blood vessel formation in this disease. Current therapies block VEGF from stimulating pro-angiogenic responses, whereas QM107 directly targets an endogenous cell surface receptor which stimulates an anti-angiogenic response by reducing vascular permeability and endothelial cell migration. Current therapies which target VEGF: 1) Associated with high level of patient non-response and side effects (cardiac infarct, thromboembolic events, micro-angiopathy, etc.). 2) Expensive (£ 1000/ injection of Lucentis) and very invasive: They involve injecting antibodies directly into the eyes of patients on a monthly basis. 3) Evidence that over time (~2 years) their efficacy is lost in 10- 20% of cases and patient’s sight worsens.

Our company is developing a platform to produce next-generation ingredients in a sustainable, cost-effective, and scalable way. We are brewing fungi inside bioreactors to produce different ingredients. Starting with colorants, and more specifically a high-performing red colorant (the most used color in the food and cosmetic industry), we are also producing orange and yellow, to then follow with other colors like blue and green.   

Battery cells must be tested for performance and operational reliability from the design phase to the production process, to safeguard its safety, reliability and cost. As batteries are prone to temperature-related issues, like overheating and overcharging, there can be extreme spikes in temperature known as ‘thermal runaway’. In order to evaluate the thermal performance of the battery, calorimetric testing can produce data that indicates defects at an early stage and thus help to predict a ‘thermal runaway’ at a later stage.  A German research institute has developed a modular, scalable calorimeter to measure the thermal data of batteries of diverse cell sizes. The scalable system is suitable for applications in thermal monitoring from new module designs to new battery materials and quality assurance. The modules are currently in use at the research institute and this calorimeter has German utility model protection. The research institute is searching for partners for the joint further development in research cooperation agreements or for partners interested in a direct license.

The technology is an agile project & team collaboration platform. Collaborative creation, planning and organization in one single place, for every team and any leader. It solves the problem of finding the perfect balance between both autonomy with teams still alignment across the enterprise. 

The proposed technology relates to a battery management system (BMS) equipped with active cell balancing technology and sophisticated state-of-charge (SOC) prediction algorithms. Using this algorithm, faster cell balancing can be achieved during charge and even discharge operations as compared to conventional passive cell balancing technology. This allows the BMS to maximise net energy output from the battery system during its service life. Ultimately, the BMS increases driving range and reduces battery repair/replacement cost. The technology owner is seeking partners to collaborate in various modes including technology licensing, consultancy project, research collaboration, etc. 

The 2 kWh Deep-Water Lithium-ion Battery Power Pack (DLBPP) is a pressure-tolerant lithium-ion battery system that provides a reliable, long-endurance and longer lifetime power solution for underwater systems. Many unmanned or autonomous vehicles requires stable and long battery life for their operations. On-station time needs to be long so that the vehicle can spend more time to carry out its task. The technology relates to a smart battery management system (SBMS) with high efficiency active cell balancing technology, intelligent self-learning state of charge (SOC) and state of health (SOH) prediction for the lithium-ion battery. The active cell balancing technology leads to 15% longer endurance and lengthens the lifetime of the battery for underwater applications. In addition, the 2 kWh battery stack module with SBMS is scalable and swappable to provide higher power capacity and increase flexibility in usage. A built-in pressure-resistant enclosure is included to increase power system reliability at high pressure conditions, up to 3000 m below sea level. The technology owner is seeking partners to collaborate in various modes including technology licensing, consultancy project, research collaboration, etc.