Founder Institute HQ Palo Alto journalist Dustin Betz interviewed Ajinomatrix.org Founder and CEO François Wayenberg. Here is the full transcript.
Dustin Betz: Introduce yourself – speak a little about your own background, professional and/or personal experiences and motivations that led you to founding Ajinomatrix.
François Wayenberg: I’m graduated from the university of Brussels, economist, and industrial collaborator at the AI lab at the polytechnics institute there (ULB). My initial career involved working for Mitsui, a Japanese trading company est. 1620AD, as an European food dept manager with extremely organized and stringent approach to food quality for export in Japan, and in large part educating the suppliers in Europe to be able to export their produce in Japan. This later allowed me to even collaborate with NASA through what I had learned at Mitsui.
When I worked at Mitsui, I explored what was feasible as most advanced with Deloitte and we made a plan to digitize the senses of taste and smell for the food industry.
This really kept me going for a long time and got me thinking especially:
- Developing the project at Microsoft speech recognition L&H incubator Flanders Language Valley
- Meeting Joel Bellenson who just had made the cover of Wired magazine, in London
Dustin Betz: Next, by way of introduction, I’ll ask you to give us your quick elevator pitch.
François Wayenberg: AJX digitizes the measurements of the senses of taste and smell for the food industry through an AI open source B2B app, allowing a food company of any size to implement AI and sensory digitization within their facilities, either for QC or product development.
It solves the problem that nowadays even in the 21st century, the digitization of the senses for smell and taste is still a very artisanal process even in medium to large companies – and even in majors, the digitization level of facilities is not complete or generalized .
Dustin Betz: For those sitting far enough removed from the food sciences industry, they may be totally unaware of the level of testing and data analysis, from the test kitchen to the lab bench, all the things that go into any any big food industry player’s decision-making around the products that they ultimately put on the supermarket shelves.
Some may have heard of a concept of ‘taste testers’ or have some inkling, but I get the sense that this is a pretty impenetrably industry for most consumers—so please explain some of the scope of the complexity here, in the ‘problems’ that you are solving for?
François Wayenberg: The players in the industry have to make decisions on how to organize the tests in order to measure the taste and aroma – they can do it internally or delegate it to an external lab. Obviously, inviting competent tasters as mouths and noses is not only very troublesome during the covid pandemic, but it already is normally: it’s costly, not so easy to organize and it takes considerable amounts of time. How does it work? People as tasters give notes on different attributes, on a scale from 1 to 10 for instance, and the results are being encoded. This is, in addition to some lab equipment and maybe a few sensors, how the data is currently being recorded.
But how this is being recored is generally happening in a still very old fashion way – in such a way that the different experiments are not standardized from one to the next, and as a consequence, the results are not being comparable.
Dustin Betz: Why Ajinomatrix / why digitization of sensory data as a key solutions for addressing these challenges?
François Wayenberg: Well, the problem then is that because of the organization of how these tests are being recorded, is that there is no modern data analysis possible on the results of the tests, and what the players in the industry generally have in their hands are a large set of dark data.
Ajinomatrix brings in an easy framework in order to have these data standardized and to help implement data mining and AI in order to make sense of the accumulated data, in order to not only interpret it in a classical data mining way, but to overcome limitations of classical sensory science in terms of data interpretability.
Dustin Betz: I understand your software already interfaces with these emerging sensors such as e-noses or e-mouths—what little I have heard about those new kinds of sensory technologies sounds very interesting, and promisingly aligned with your own tech—are there other key features that we haven’t yet talked about / that you want to highlight here?
François Wayenberg: It’s a delicate matter or issue: we have for instance a giant in flavor and fragrance coming to us asking openly how they could use our technology to basically get rid of all of their panels. Their ideal would be to simply work without those.
I would say we develop the tools. Also when it comes to interfacing the sensors, we are not quite there yet, it’s projected in phase 2 of our development but it is not what we are focusing on right now, because the reality in the industry is that these technologies are in their birth phase for industrial applications, and that they don’t really replace the human senses yet.
So there’s indeed an alignment and a promise, but we will move on to this type of proposal when there is a set of agreements that we will conclude with sensor makers in order to implement interfacing, as at the moment we are dependent on data exports for our software to include sensors.
This said we are in discussion for a large joint venture in the output device area, which is something our team has previous experience with, namely with Joel.
Dustin Betz: If I am a food scientist hearing this now and interested, how can I get started with Ajinomatrix?
François Wayenberg: If you are a food scientist hearing this and interested, we are actively looking for more use-cases involving sensors, so I invite you to contact us to organize a demo and showcase of our technology.
Dustin Betz: How will data technologies ultimately change food science, over the next ~10 years?
François Wayenberg: We are clearly at the start of a revolution of how data is being integrated into food production. This can be a very positive change, because there is a real promise of how customization and transparency and a booming in the different niches of products being offered to the populations, with as many diets and dietary customs that there are groups of people, people suffering from food-related diseases, people with special diets, different religious habits, are all sources of so many different niches the food producers have to learn to address.
Just look at how burger king for instance offers a wonderful choice of vegan plant based burgers, I was amazed to taste one of those, because you can feel there is more engineering of how it tastes than a flagship regular meat burger. The taste palette is wonderful, very vegetable-based, and the plant-based burger homogenizes in there with a very tasty palette.
I think it is just a beginning and we will see much more of those more refined tastes appearing. It is clear also that with my experience of working with Japan and Asian taste palettes, our traditional food is booming with a creativity that is unmatched compared to the past.
So to answer the question, it is clear that technologies helping to reduce fat content, sugar and salt, for a determined taste envelope today will, with the help of AI, achieve unpredictable and great developments in terms of the variety and customization of the food we eat, and also produce greater adaptation and requests from customers as the choice we offer them expands, so this trend will produce great changes in the future. Data will serve these developments, because in the end it’s the consumer that has fixed ranges of how he tastes and smells food, and the offer of new food will be constrained by that – therefore data will be instrumental in fine-tuning and better satisfy the customer in terms of how he is served.
Dustin Betz: I’ll ask you about the biggest challenges you’ve faced in building the company so far, and how you’ve overcome them.
François Wayenberg: Having worked for 20 years on a theoretical convergence of AI and sensory science, I can tell that there were a lot of barriers for a long time to enter the industry in terms of the maturity and availability of the data analysis tools – such as mature AI toolboxes, and also a maturity of the market in order to invite the technology with AI to enter the factory. I have struggled for this to happen for years, but the place has suddenly become mature and hence we decided to found first in Israel and then in Belgium.
Dustin Betz: I’ll ask you about your general advice for would-be entrepreneurs or those very early stage founders just getting started.
François Wayenberg: First of all, never give up on your idea once it gets to some level of validation. Second, you have to consider tools like the Founder Institute to help you reach your goals in entrepreneurship, because it is such a prone environment to manage all of the early challenges you are confronted with while creating your company that, by the time you graduate, you basically do everything by instinct and you get used to make your way towards success.
Finally, I think it gets to a very particular environment nowadays where it becomes more and more natural to network with people and to achieve most of your desires in entrepreneurship through dedication, I really encourage anyone wanting to make his/her idea real to consider to become an entrepreneur and to found a business in order to make it real.
Dustin Betz: Finally, we’ll conclude with me just asking for any other final updates you have to share with the FI community (where you’re headed next, any planned new releases; if you want to elaborate about your current fundraising; and/or if you have a generic ask for the FI global audience!).
François Wayenberg: We are today after less than a year already operating from 8 different locations around the world on a daily basis, and as we don’t have sales we are launching our first 2M€ straight to A round.
This is very ambitious, and it corresponds to our ambition to propose a sensory file standard, like a photoshop file of the sensory kind, that is digitally modifiable but implementable as a recipe in reality eventually even with a cost estimate.
We operate also in a hybrid mode between a startup and a research foundation, comparable to Canonical with Ubuntu, and this is something that makes us special in the way we protect the consumer: we have an ethical manager in the organisation, and we want our clients to visit us to achieve better results in offering healthy products to consumers. In this instance I would see a possibility of AJX in the future to interface with apps such as BetterMeal.AI in order to offer by sensory preference more adapted and healthy diets to the consumers. I think there are an amazing set of possibilities that are just being defined now of how taste, smell digitization and digitization of the experience of eating will interact with us in the metaverse.
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