Key people
In the news
- Proud to share that we've successfully closed out the first stage of the Astromechatronics project with Astrofood, made possible by an ESA Space Solutions Belgium Spark Funding. Over the course of this project, we took important steps toward automated, intelligent systems for space-based microalgae cultivation, combining mechatronics, control theory, and data science to push this technology forward. Grateful for the collaboration and the trust from ESA Space Solutions Belgium, and looking forward to future opportunities to take this
- The real AI advantage in industry isn't always the algorithm: it's often the people who know the process better than anyone else. Our co-founder Tom Staessens shared his take with Agoria on the future of industrial AI in Belgium. Check it out below👇
- Most machine teams have someone like this: the person who just knows how to get the machine right. Everyone is glad they're there, and nobody enjoys the week they're on holiday. When a machine leans on one person's feel, that dependency turns up in more places than you might expect. We put three of them in the carousel below. Do you have a person like that on your floor? Which of these three worries you most?
- Our co-founder Tom was interviewed by Agoria, check out his take on industrial data in Belgium below 👇
- On most machines, the settings that decide the outcome live in one person's head. That works, right up until they're on holiday, or a new variant shows up, or the material starts behaving differently than it did last month. Meanwhile the machines get more configurable and the jobs more variable. More knobs, less time to turn them. So we put together a primer on how much of that a machine can work out for itself. What gets called setting automation mostly comes down to three moments: what past jobs tell you before a run, what
- When a controller needs retuning on every new machine variant, the cost shows up in two ways: the hours it takes, and whose hours they have to be. We worked on a project where both constraints were compounding each other. The parameter space was too large to sweep quickly, and navigating it required someone with real feel for the system. That combination made every new variant a significant claim on a specific person's time. Bayesian optimization gave us a way to separate those two problems. The expert's knowledge stayed in the loop,
- Satisfying flight back after deploying an advanced control project in the USA. What started as an innovative R&D project has now been successfully deployed at a customer’s site. Proud to partner with Belgian machine builders to innovate and create smarter machines. Now just waiting for the jet lag to deploy as well 😄
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