We have developed ScienceRouter (SR), a AI/machine learning web-based platform that will bridge the gap between industrial companies and academic researchers by enabling the best match between them, 14 times faster than current solutions, and at a comparatively lower cost. Through the implementation of machine learning algorithms, SR analyses open data research articles, patents, university and corporate websites to automatically create knowledge profiles for individual researchers, and knowledge-need profiles for companies. Our profile database enables searches based on keywords and also on free text. SR then facilitates communication and agreement between both parties, simplifying the process of signing contractual agreements, payment and collaboration initialisation.
Improving knowledge transfer from universities to society is important. Despite the substantial investment of public resources in academic research in Europe, there is still a lack of systematic commercial exploitation of knowledge, as demonstrated by the scarce production of innovations and patents. SR can facilitate and enhance applied research and technology transfer, thus impacting positively on Europe’s competitiveness.
The objectives for the project is to verify the business assumptions around the ScienceRouter platform. This includes
- researchers willingness to work with industry
- industries interest in working with researchers
- compliance with GDPR and international employment law
- analyse the market
- create a technical roadmap and goto market strategy