ManSciTech is seeking to join FutureFoods consortia as an agile SME technology partner to provide cutting-edge solutions in food digitalization, omics sciences, and authentication. We are highly interested in collaborating on projects focused on food fraud prevention, smart traceability, and the sustainability of agri-food supply chains. To these projects, we bring advanced analytical capabilities that combine Nuclear Magnetic Resonance (NMR) technology—utilizing our high-throughput 400 MHz Food Screener—with Artificial Intelligence to create the "Digital Print" of foods. This allows for the unequivocal identification of origin, purity, and composition in complex matrices such as oils, wines, beers, fruits, and cereals. We are ready to take on or support Work Packages focused on advanced chemical-analytical validation, metabolomics, and the development of digital tools for food verification, leveraging our proven research record with major industry players to ensure integral quality and consumer trust.

ManSciTech S.L. is an entity specialized in big data analytics and the development of advanced digital solutions for the agrifood sector. ManSciTech S.L. was founded with the mission of bridging the existing gap between cutting-edge scientific research and the operational needs of the industry. ManSciTech S.L. centers its strategy on the "Digital Food Fingerprint" initiative, an operational framework designed to assign a unique digital identity to each agrifood product with the aim of verifying, ensuring quality, and guaranteeing total traceability from the origin to the final consumer. This activity is based on the integration of Nuclear Magnetic Resonance (NMR) and Artificial Intelligence (AI). To this end, we identify characteristic patterns from the modeling of the recorded NMR spectra, allowing us to use AI to generate a simulated reference spectrum for each product that captures its distinctive characteristics; in short, the fingerprint of each product.

In addition, we create predictive models capable of learning from feedback and classifying, allowing us to accredit the product (at the brand, origin, or PDO level...), identify contaminants (toxins, additives, antibiotics, pesticides...) and control traceability (from the raw material to the packaged/bottled product).

The technological capacity of ManSciTech S.L. is sustained by a solid high-performance computing infrastructure optimized for the processing of large datasets and the training of Machine and Deep Learning models. On the other hand, ManSciTech S.L. was the beneficiary of a contract for the training of doctors in companies (Industrial Doctorates, Ministry of Science, Innovation and Universities) whose purpose is to promote the implementation of industrial research or experimental development projects to favour the labour market insertion of research personnel. Furthermore, it was also the beneficiary of a Torres Quevedo Contract.