Universities
This section describes research with Universities
Brussels University's IRIDIA
At the University of Brussels, the IRIDIA Lab of Hugues Bersini associated with Ajinomatrix within the framework of a regional cluster project MecaTech based on AI development.
Hebrew University
We received and inherited our IP through global exclusivity contract for digital gastronomy and remastered the RecipeAnalyzerTM now integrated in our AjinoVerse suite.
University of Helsinki
We have worked out an EU project in the collaboration with EIT Digital with the Open Innovation Factory framework for a budget of 400.000€ in total and developed our TasteTunerTM with this and wired out the SensoryOS framework, presented at TheEgg at the same date as Apple's VisionOS.
UMons' Numediart
With Pr. Dutoit's Numediart, we are looking into possibilities to develop our proof of concept as of the requirements for the initial specifications of our app's framework.
SeAMK University
With SeAMK we helped prepare a digitization initiative supplying useful texture data for the F3Lab's digitization effort.
Clusters
This section describes regional cluster cooperation
MecaTech
MecaTech cluster helped us as a regional partner for long term development in applied industrial research.
Wagralim
As former members, we are investigating future project coordination with industrial partners
Logistics in Wallonia
With WiL we have investigated development programs with traceability and hardware interfacing.
Research Centers
Ajinomatrix's cooperation with Research Centers
Fraunhofer
With the Campus of the Senses, Ajinomatrix is investigating the future of sensory science measurement.
Certech
With Certech, we are investigating the future of AI in sensory research.
Cetic
In the framework of the DigiAccelerator, we instanciate a first collaboration contact with the Cetic.
Sirris
In the framework of CAP IA, we instantiate a first collaboration contact with Sirris.
Projects
Ajinomatrix's Spinoff Projects
Black Swan PreCog
In order to train our algorithms, and because in the food business data is relatively scarce, we decided to train our algorithms with unprecedented prevision capabilities.