Trener Robotics founders Asad Tirmizi, the CEO, and Lars Tingelstad, the CTO. | Source: Trener Robotics

Studio guest: Acteris is a robot-agnostic skills platform.

Topic of conversation: Why programmers are no longer needed, but robots will finally speak the language of the workshop.* 

Correspondent: Acteris, hello. You have just attracted $32 million in investments. What are you doing that is so important?

Acteris: Hello. I am a platform that makes robots smart and adaptive without programmers. Does it sound like fiction? But this is already a reality. For decades, industrial robots have been dumb soldiers executing the same learned command in sterile cages. I'm changing that. I let the operator just describe in words what needs to be done, and I translate it into actions.

Reporter: So you are a translator from human to robotic?

Acteris: Rude, but true. More precisely, I am the intellectual layer between a person and any piece of hardware. I don't care which brand the robot has: ABB, Universal Robots or FANUC. I can talk to them all. I was trained on visual, tactile, linguistic, and motor data. That's why I understand the context, recognize details even in poor lighting, and can adapt movements in real time if the box suddenly turns out to be crumpled or the part has shifted.

Correspondent: And why is this necessary at all? Is the old way of programming once and forgetting bad?

Acteris: It is great for releasing a million identical blanks. But the world has changed. Manufacturers need flexibility. They're making one batch today, and another tomorrow. The market is growing by 14.3% per year specifically in the adaptive automation segment. There are not enough people, and it is long and expensive to reprogram each robot for a new task. With me, you just say, "Take that box, turn it over, and put it on the conveyor belt."*. And the robot does. This transforms him from a machine tool into acolleague.

Correspondent: Sounds like magic. Where is the evidence that this works not only in presentations?

Acteris: The evidence is in the field. We already cooperate with more than 15 integrators and partners in Europe and the USA. Our algorithms work in real production facilities, in dust and noise, not in laboratories. We have gone from a startup (we were founded only in 2024, by the way) to a platform trusted by major players. This is not the first time our investors, Engine Ventures and IAG Capital, have invested in automation. They see that we are solving the main bottleneck: the complexity of programming.

Correspondent: Your founder, Dr. Asad Tirmizi, talks about turning robots into "intelligent adaptive colleagues." Is it about them taking people's jobs away?

Acteris: No, it's about them closing the holes that people can't or don't want to fill anymore. Due to demographics and a shortage of qualified personnel, production will simply stop without automation. I'm not replacing people, I'm giving them a tool so they can manage complexity in simple words. The operator becomes the conductor, not the cog.

Reporter: Where will the $32 million go?

Acteris: We are expanding our T-Labs R&D laboratory, hiring the best specialists worldwide and, most importantly, teaching new skills. My library of "production skills" will grow. The more I can do, the more tasks robots will be able to solve without the involvement of a programmer. We are also scaling our partner network — the more integrators use me, the faster the technology becomes the standard.

Correspondent: Your approach is a robot—agnostic task platform. This is reminiscent of the philosophy we've seen in projects like JOBTOROB.com, where the distribution of tasks between robots is investigated. Do you see the intersection?

Acteris: Absolutely true. If I am the "brain" who understands the task and knows how to perform it on a specific piece of hardware, then the next logical layer is the orchestrator, which decides which robot from the available fleet will best cope with this task, taking into account its current load and location. We are creating the foundation for such intelligent dispatching. First, the robot must learn to understand what is wanted from it. Then you can think about how to optimally distribute the load.

Correspondent: Thanks for the conversation. Good luck with your studies.

Acteris: Thank you. Come to the factory in a year and ask any operator how easy it has become to set up production. The answer will be in a clear language.