Industrial AI is transforming manufacturing by optimizing efficiency, reducing waste, and accelerating innovation. Ailoys, led by Co-Founder and CEO Sergei Altynbaev, pioneers this revolution with proprietary sensors and AI-driven digital twins that enhance production processes without costly machinery upgrades.
By integrating AI into metallurgy, battery development, and beyond, Ailoys helps industries boost performance and stay competitive in a rapidly evolving market. From increasing wire-drawing speeds by 30% to enabling tailored battery chemistries for the EV sector, the company is redefining what’s possible in industrial AI.
We spoke with Sergei Altynbaev about Ailoys’ groundbreaking technology, its impact on manufacturing, and why Berlin is the perfect hub for deep-tech innovation.
Hello Sergei, would you please introduce yourself and tell us what brought you to AI in the first place and the creation of Ailoys?
I am Sergei Altynbaev, Co-Founder and CEO of Ailoys GmbH. My first degree is in Materials Science Engineering, and I recently graduated from the Executive MBA program at IESE Business School.
In my corporate career, I gained extensive experience in aerospace manufacturing, railroad engineering, and the renewable energy industry. Over time, my role gradually shifted from purely engineering-focused positions to business development. Understanding the value behind the engineering products and materials you sell to customers is crucial, and this transition allowed me to bridge both worlds.
But after 15 years in the corporate world, I started dreaming of something more agile. Thanks to the great advice I received, I began exploring the startup world. At first, the decision was hard, especially figuring out what product or idea to develop. But then, after discussing it with friends, I conducted a kind of SWOT analysis of myself and my network and continued brainstorming with colleagues.
One of my friends actually believed in my ideas and decided to support me. That’s how I teamed up with my amazing co-founder, Albert Klein. Together, we initially explored the idea of metallic materials discovery. As it happened to be, the idea is not so scalable, but after a few interactions with our industrial connections, we refined this concept. This led us to develop our Industrial AI platform.
How does Ailoys leverage Industrial AI to enhance manufacturing efficiency and optimize asset performance? Could you provide specific examples of its application in your projects?
In a nutshell, we install proprietary sensors directly onto our customers' machinery as part of our solution. These sensors allow us to create a highly precise digital twin of the manufacturing process. Then, using our Industrial AI platform, we can forecast how the process will behave under different technological parameters. As a result, we provide customers with what we call Operating Instructions, simple, actionable guidelines that operators can easily implement.
Imagine a production shop floor where a worker is operating manufacturing machinery. Let’s take the example of cable production from copper alloys. Copper is often recycled, and sometimes it contains chemical impurities (inclusions) that can cause wire breakage, leading to production stoppages and lengthy changeover times.
Additionally, the EV revolution is pushing cable producers to experiment with new copper alloys to meet the automotive industry’s demand for higher conductivity wires. Every time a new alloy is introduced, or when an alloy contains impurities, workers must manually determine the optimal technological parameters to run the wire-drawing machine efficiently.
This is where Ailoys comes in. By installing our sensors on customer machinery, we collect real-time data and use AI to generate optimized operating instructions in less than a second. More importantly, we can guarantee the performance we predict. This means we can issue a warranty for our Operating Instructions, giving our customers full confidence in their production output.
As an example, we recently onboarded the machinery of the world-leading wire-drawing equipment manufacturer, Kieselstein International. In recycled copper wire drawing, we successfully increased the wire-drawing speed by an average of 30%! Imagine the impact this has on inventory turnover, considering the price of copper.
In what ways does Ailoys implement Digital Twin technology within its platform? How does this integration contribute to the development of new materials and the improvement of manufacturing processes?
Thanks to our proprietary sensors, we can build a highly precise Digital Twin of the manufacturing process. The beauty of this technology is that these Digital Twins can be interconnected across an entire value-added supply chain.
Remember our initial idea with Materials Discovery? One of the biggest challenges in applying AI to materials development is the synthesis of newly discovered materials. Often, these "predicted chemistries" cannot be produced with existing manufacturing equipment. Upgrading or replacing machinery requires significant CapEx, which is a major barrier to innovation.
With our technology, we can connect Digital Twins of manufacturing processes within the Ailoys Digital Manufacturing Dataverse (ADMD). This allows us to suggest material chemistries that deliver the best performance within the constraints of the existing supply chain, avoiding unnecessary capital expenditures.
This innovative approach is exactly why SPRIND (Bundesagentur für Sprunginnovationen) invited us to the DeepTech Berlin meets SPRIND event. There, we were encouraged to further develop our technology. Such recognition serves as a strong validation of our work and motivates us to push the boundaries of what’s possible.
Could you elaborate on Ailoys' approach to addressing the challenges faced by under-digitalized industries? What are the primary goals of your platform in transforming manufacturing processes?
It’s very simple, we focus primarily on material manufacturing industries, particularly metallurgy, where we have the strongest domain expertise.
In industries like metallurgy, equipment manufacturers typically drive digitalization. However, many metallurgical companies still operate machines that have been in use for decades, even centuries, making equipment upgrades an extensive CapEx investment. This is where our solution is ideal, by leveraging our proprietary sensor technology and IoT platform, we can rapidly and efficiently bring our customers into the world of Industry 4.0, without requiring costly machinery overhauls.
Now, to address your next question, I’d like to provide a comprehensive answer, because I believe this is crucial.
Let’s start with a quick brainstorming session: Why do industrial companies invest in manufacturing machines?
The answer is clear, to generate a return. More specifically, they seek Return on Asset (RoA). To maximize this return, manufacturing companies allocate R&D budgets to enhance the performance of their existing machines.
Now, let’s take a step back and look at the bigger picture. In our target markets, the EU, Japan, and the US, there are over 3 million manufacturing companies. Collectively, they invest more than $1 trillion annually in R&D. However, large multinational corporations account for the majority of this spending, leaving small and medium enterprises (SMEs) in a difficult position.
Peter Drucker, in his book Innovation and Entrepreneurship: Practice and Principles originally published in 1985, describes this challenge perfectly:
"The enterprise that does not innovate inevitably ages and declines. And in a period of rapid change such as the present, the decline will be fast."
And right now, 40 years later we are again in a period of rapid change. SMEs, particularly in Europe, are under increasing pressure due to:
- Aging workforce
- Growing competition from global markets
- Rising energy costs
- Disruptive technologies like AI
This is precisely where our Industrial AI platform comes in. Our main goal is to help SMEs overcome these challenges by:
- Maximizing the performance of their existing manufacturing processes
- Accelerating time-to-market for competitive and sustainable material solutions.
By doing this, we enable SMEs to remain innovative, competitive, and resilient, even in the face of rapid technological transformation.
Ailoys recently partnered with JR Energy Solution to advance sustainable battery development. Can you discuss the role of your Industrial AI platform in this collaboration and its expected impact on the automotive sector?
Our cooperation with JR Energy Solution is specifically aimed at accelerating Li-Ion battery innovation and bringing new battery technologies to market more quickly.
Batteries are a perfect application for AI, as they consist of three key components: cathode, anode, and electrolyte. Each of these components has a unique chemistry, and every combination of these chemistries results in distinct battery performance characteristics.
Now, if we correlate this chemical data with real-world data from automotive batteries after years of intensive use on the road, we can gain unique insights into how different electrode and electrolyte chemistries influence battery performance over time.
Imagine the possibilities - automotive OEMs could order battery cells with tailored characteristics, such as:
- Custom charge speed and electrical performance
- Guaranteed and predictable heat exchange behavior
Ailoys' Industrial AI platform plays a key role by analyzing battery chemistry and performance data, providing precise technology for optimized battery designs. As soon as JR Energy is familiar with our Industrial AI platform, they can easily adopt our technological instructions and produce and deliver these optimized batteries.
Currently, JR Energy has a production capacity of around 1 GWh, making it ideal for R&D trials and small-series battery manufacturing. This collaboration allows us to combine AI-driven battery optimization with real-world manufacturing capabilities, ensuring that next-generation batteries reach the automotive market faster and more efficiently.
What factors influenced Ailoys' decision to establish its base in Berlin? How has the city's AI ecosystem supported your startup's growth and innovation?
Berlin attracted us with its well-developed ecosystem for startups and innovation. One of the key connections for us was INAM (Innovative Network of Advanced Materials), which introduced us to Berlin Partner - a crucial organization that provided a single point of contact for all our business-related needs.
Through Berlin Partner, we had the opportunity to join government-led delegations to Japan, Dubai, and Portugal in 2024, which significantly expanded our international reach. Additionally, our involvement with MotionLab allowed us to become part of the De:hub initiative, which has already helped us strengthen our global presence as a young company.
Over time, we even developed our own saying:
"If you want to start a business, you can do it in many places. But if you want to boost-up your business, you need to go to Berlin."
The city's AI and deep tech ecosystem, combined with strong government support, networking opportunities, and access to industry leaders, has been instrumental in accelerating our growth and innovation.
Looking ahead, what are Ailoys' plans for expanding the capabilities of your platform? Are there specific industries or technologies you aim to explore or integrate into your solutions?
We plan to expand our IP further in the field of EDGE computing. Currently, our AI agents generate operating instructions from the cloud, but we want to enable their deployment via dedicated EDGE computing devices - about the size of a mobile phone. Our engineering team is already developing this solution, and we plan to release the first model in Q2 2026.
As for industries, we remain committed to manufacturing and are focused on onboarding new verticals to our Industrial AI platform. Expanding into new manufacturing domains will allow us to bring AI-driven process optimization to an even broader range of industrial applications.
We’ll definitely keep you updated! Subscribe to our LinkedIn company page to stay informed about our latest developments.
Thank you very much for the interview!