Universities
This section describes research with Universities

Brussels University's IRIDIA
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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
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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
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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
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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
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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
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MecaTech cluster helped us as a regional partner for long term development in applied industrial research.

Wagralim
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As former members, we are investigating future project coordination with industrial partners

Logistics in Wallonia
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With WiL we have investigated development programs with traceability and hardware interfacing.

Research Centers
Ajinomatrix's cooperation with Research Centers

Fraunhofer
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With the Campus of the Senses, Ajinomatrix is investigating the future of sensory science measurement.

Certech
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With Certech, we are investigating the future of AI in sensory research.

Cetic
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In the framework of the DigiAccelerator, we instanciate a first collaboration contact with the Cetic.

Sirris
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In the framework of CAP IA, we instantiate a first collaboration contact with Sirris.
Projects
Ajinomatrix's Spinoff Projects
Black Swan PreCog
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In order to improve our algorithms, and because in the food business data is relatively scarce, we decided to train our algorithms with unprecedented prevision capabilities. Try it out! Here.

