The United States is the second largest manufacturing center in the world (after China). With the growing trend of reshoring manufacturing operations, companies are increasingly looking for automation solutions.
Micropsi Industries' moves HQ from Berlin to the U.S.
Q&A with Gary Jackson, CEO | Micropsi Industries
Tell us about yourself and your role with Micropsi Industries.
I joined Micropsi Industries as the CEO, working closely with Ronnie Vuine, Founder and Chief Product Officer.
My primary responsibility is to manage the financial and operational aspects of the business, while shaping the future vision of the product and aligning it with the company's long-term strategy. Ronnie continues to oversee all aspects of the product's technical evolution, making sure its development aligns with our goals.
As for my background, my career began in 1982 in B2B enterprise software sales, where I spent nearly a decade in sales roles with increasing responsibility. In 1992, I reached a turning point when I assumed the role of Vice President of Sales at Vantive, one of the first CRM applications, and then later as EVP International Operations. As the 11th employee, I played a key role in growing the company from $0 to $200 million in revenue in just six years.
Vantive was later acquired by PeopleSoft, which was subsequently acquired by Oracle.
Since then, I have held several CEO positions at companies specializing in B2B enterprise software, including four AI platforms, and most recently focused on manufacturing shop floor solutions.
This combination of experience made me the right person to join Micropsi Industries and meet the needs of both the board and the company at this stage of growth.
Why did Micropsi Industries' HQ move from Berlin to the U.S.?
Our goal has always been to grow the business, and that plan has been driven by two key factors.
The first was the ability to attract and retain top technological talent. The U.S. offers a large talent pool, and a workforce with experience running large tech companies as well as turning start-ups into global success stories.
To attract and retain these types of workers, we needed to offer an equity-based stock option plan. While this is standard practice in the U.S., it is far less common in other parts of the world. Initially, we were headquartered in Germany and operated as a GmbH (Gesellschaft mit beschränkter Haftung, roughly equivalent to an LLC). However, implementing and administering an equity-based stock option plan under this type of corporate structure — and within a U.S. governance framework — proved to be very challenging.
The second factor was access to capital markets, which are predominantly located in the United States. If you look at global investment in technology companies, about 65% to 70% comes from the U.S.
Has the move to the U.S. helped to better serve customers? If so, are there concrete examples of this you can tell me about?
Building on the previous point, one of the immediate benefits of moving to the United States was the ability to fill key roles, including the hiring of our new VP of Customer Success, Jessica Yen.
In a remarkably short time, Jessica has completely transformed the way our deployment teams work with customers. Her efforts have made it easier for customers to start using our product, which has laid a stronger foundation for long-term success.
Jessica brings a unique background, starting as an aerospace engineer in the manufacturing industry before transitioning to lead the customer success team at a software company founded out of MIT. Her experience and perspective are exactly what our customers need, and hiring her was an opportunity that wouldn't have been possible without moving our headquarters to the U.S.
In addition, the United States is the second largest manufacturing center in the world (after China). With the growing trend of reshoring manufacturing operations, companies are increasingly looking for automation solutions. This market requires support from automation partners located near their facilities to enable effective deployment and reduce the delays often associated with international collaboration.
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What are some recent advances in AI/vision technology, and how can Micropsi Industries be seen as a leader in this field?
Recent advances in Large Language Models (LLMs) have been impressive, but the technology is not effective today in every application. These models rely on massive datasets and enormous computational resources to function effectively.
When we apply this concept to manufacturing, it becomes clear that training a reliable AI for specific tasks — such as testing refrigerator pipes for coolant leaks — would require the collection of millions of data points. This is neither practical nor feasible for many real-world problems.
Instead, we use a technique called imitation learning. By demonstrating the desired task to the machine, we eliminate the need for large data sets and avoid working with negative examples. While this limits the AI's ability to think creatively or solve problems independently, it simultaneously keeps the AI's actions within what's predictable and eliminates unexpected behavior in manufacturing environments.
Our approach requires only about 30 data samples to train an effective skill, significantly reducing the time and resources required. By contrast, attempting to build an AI similar to ChatGPT for manufacturing tasks would take many years to develop and deploy and is currently not doable with today's technology. With imitation learning, on the other hand, we can typically deploy a solution in around 10 days, depending on the complexity of the task.
Again, to answer your question more clearly, we've established ourselves as a leader in the field by offering a unique AI solution tailored to the manufacturing industry. Our innovation, speed of execution, and ability to rapidly deploy modules on the factory floor far exceeds what is currently available in this space.
Does industrial automation differ in Europe compared to the U.S.?
Yes, but only in the way decisions are made – mostly due to cultural differences. The problems manufacturers are facing are the same, regardless of their location. Currently, the largest problem we face globally, whether the plant is located in Asia, Europe, or the United States is the labor shortage.
Most industrial automation initiatives are currently aimed at eliminating or reducing the amount of labor needed for traditionally manual tasks. These are positions in assembly and testing that are difficult to keep filled.
These problems are all relatively consistent. If we go back to the cultural differences in decision-making, we find unique labor requirements and expectations in each country and region. There are also regional and industry-specific IT and security standards.
To give an example, at Micropsi Industries, we got our start in the automotive sector in Germany. If you’re not familiar with German automotive standards, then I would describe them as some of the most demanding requirements for manufacturing operations on the planet today. Of course, starting here and satisfying German requirements made it easier to navigate less complex manufacturing markets like those in the United States, which are more willing to take risks.
So, if you’re looking to get into industrial automation in Europe or the United States, you can expect the Europeans to be much more careful and make decisions more deliberately. You’ll be asked for a lot more evidence and proof that your solution is reliable and robust enough to meet their demands.
Manufacturers in the United States are much more willing to try something new, take risks, and move quickly with new technology. Still, the problems that need to be solved are essentially the same.
Has Micropsi Industries managed to start disrupting the industrial automation market in the U.S.? What are the early signs?
We’re already disrupting the market by automating manufacturing tasks that no robot could previously accomplish. We also were able to automate unergonomic tasks for human workers, saving them from doing repetitive, difficult tasks.
It might help if I provide an example to explain how significant this disruption is. I was speaking with one of my investors the other day, and I said there are approximately 200 million manual assembly and testing jobs in manufacturing. He’s also a professional in the field, and he said that my estimate was much too conservative and that I had missed an important element.
He estimates that of these 200 million manual jobs, 20 million are left unfilled due to the labor shortage. That puts manufacturers under pressure to find, hire, and retain new workers in an already-stressed labor market. This was historically easy to do, but that’s no longer the case today, which is impacting every aspect of the industry.
We see this even in low-cost labor markets. In one of our recent deployments in China, we worked with a contract manufacturer supporting a major consumer electronics brand. When we arrived, around 20% of the factory was sitting idle. They explained that it’s becoming increasingly difficult to find people to fill these positions, which is forcing them to shut down portions of the factory.
They’re not alone, either. If we can’t quickly implement robust, reliable industrial automation, manufacturing as an industry won’t be able to advance.
Let’s take this example back to the United States. Manufacturers are choosing to reshore or keep operations in the country instead of trying to take advantage of these low-cost labor markets, which are also slowly becoming less viable.
With this in mind, let’s take one of our customers who has a factory in one of the most expensive cities in the world. These are well-paid assembly workers, which means higher overall production costs.
They approached us to automate a part of the production line for seat assembly, which would reduce the number of workers needed. We were able to automate a specific function in one of their cells for bolt torquing and testing. MIRAI ended up saving them over $250,000 per year for each cell function they automated.
With that success, we’ve been able to move into other areas of the business and start exploring other functions that could potentially be automated.
How has Micropsi Industries helped to push new industrial automation applications in the automotive industry? Which parallels can be drawn with other industries based on prior successes?
We are proving that manual tasks can be automated or improved using existing robots thanks to AI. While we’ve primarily been focused on automating tasks in the automotive industry, we also have customers in the appliance and electronics industries. Recently, we’ve been actively exploring applications in the medical technology industry as well.
When you look at the types of tasks manufacturers do, most of them tend to be similar, regardless of the industry. Take, for example, screw driving or cable handling, which you’ll find in essentially all areas.
Because the tasks are so similar, it also means that many of the challenges faced by one manufacturer will likely be the same for another simply due to the state of current technology.
Adding to this, industrial automation moves at a slow pace – regardless of the industry. A manufacturing line will have, on average, several years of useful life. You might see a new model for a car, toaster, or refrigerator come out each year, but the actual assembly line doesn’t change very much to accommodate these new updates unless they are releasing the next generation version of the product.
The slow rate of innovation is a natural byproduct of an assembly line’s long life. Still, due to how the world has been moving at an ever-faster pace, manufacturers are facing increased pressure to design their factories for only the next 2-3 years. MIRAI is supporting this change by enabling flexible assembly lines that can react quickly to meet new consumer demands.
For example, one automotive manufacturer we work with designed a next generation motor for high-performance electric vehicles. They quickly realized that they wouldn’t be able to manufacture this with existing robotics technology, or with manual assembly. The situation escalated to the point where they were going to redesign the engine to make it easier to manufacture. This might push back the model release plan, which is a very expensive problem.
However, I knew that it was a challenge we could overcome. During our initial collaboration, we were able to show that our software could meet their accuracy and precision requirements. Thanks to this, MIRAI will now be supporting them to produce this next generation motor at scale next year.
Similar to other new markets I’ve tackled, innovation is always seen as impossible until the first company does it. After that, it is our job to inform the market of the potential.
Is there anything else you’d like to add before we end the interview?
I’d like to emphasize that MIRAI is unique in what it can do, which makes it hard for some manufacturers to understand the range of automation tasks for assembly and production it can perform effectively. Our software goes beyond what standard vision systems in the industry offer to industrial robots.
To fully understand it, we need to take a closer look at the broader use of AI. We see just as many scary stories about how it will impact our lives and society as positive ones. Still, MIRAI’s AI is different. We are putting intentional limitations on how the AI makes decisions. This allows manufacturers to access a more reliable AI that is held within the bounds of a task it’s taught to do.
So, instead of giving an AI massive amounts of data and training it to understand something complex, we only provide MIRAI with what’s necessary at a given moment. For manufacturers, this is a huge benefit because the AI won’t do unexpected things.
Based on our straight-forward approach for practical, applied AI, we’ve deployed in over 30 factories with another 20 following soon.
The content & opinions in this article are the author’s and do not necessarily represent the views of RoboticsTomorrow
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