At the heartbeat of machines
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How AI helps to make production lines more reliable
Young startup Novo AI aims to prevent unplanned machine failures that cause manufacturers significant losses of revenue. “It needs a change of mindset”, says Novo AI founder Hemanth Mandapati, addressing the industry’s hesitancy in the face of innovation. If he and his team can convince companies of their product, they will not only make their customers’ production more efficient but also help to clear the way for a new era of digitisation. Hemanth adds, “People need to stop working hard and start working smart.”
How do you feel when looking back at the last two years since the Young Entrepreneurs in Science workshop?
A lot has changed. It has been a long journey from ideation to prototype, from finding the funds to starting a company, building a team, and ultimately testing the product and getting feedback from customers. I am a completely different person today than I was two years ago!
What are you most confident about?
I am very happy to have built a well-functioning team. Believe me, building a team is harder than finding a spouse! Having a complementary skill set in your team and sharing the same kind of tenacity and motivation is very hard to find, but essential. I am more of a dreamer – I have a lot of those non-feasible ideas and my teammates remind me to stay realistic. They tell me straight up if something is not going to work. All in all, building a product is easy, and even easier with the right team.
From your personal journey to your idea’s journey: How has your idea developed over time?
We address the unplanned downtime of machinery that production and manufacturing businesses experience. This means: Any time a machine does not work as planned, businesses lose valuable time and revenue. Unplanned downtime is such a big issue, that companies even integrate it into their business models! We help tackle that. In the beginning, we only focused on collecting data for AI based analytics. As we consulted potential customers about our idea, we realised that they didn’t know what to do with such data. We then started to develop a solution to also provide the analytics and reliable predictions with the data. The problem stayed the same, but our product now solves more of our customers’ problems.
How does it work?
We are creating plug-and-play sensors for machines. One is designed to collect time-series data, like vibrations and acoustics. The other is a vision system that observes the production line and identifies any disturbances. Via a dashboard, supervisors can track every machine from their desks. We use our in-house-developed algorithms to classify and predict failures. This allows companies to plan ahead of time.
Is the market ready for AI-based predictive maintenance?
This is a matter of mindset. Our solution works, but it needs a change of mindset. I can recall many times when I’ve heard “if it is not broken, do not fix it”. Fellow YES alumna Mina Kolagar mentioned in your interview, that it is hard to sell predictive maintenance solutions. Our experience confirms this: companies are still sceptical about predictive AI. I am convinced that once we kick in this door, many more will open.
How has the Young Entrepreneurs in Science workshop inspired your entrepreneurial journey?
It was the first workshop that taught me the basics of lean business development and Design Thinking. I had read many books, yet those concepts were completely new to me. It was at that moment that I understood how to view research from an entrepreneurial point of view. In the workshop, I learned how to move from the initial idea towards setting up a business model.
In the years before, you worked for different companies in India, among them the Indian Space Research Organisation, ISRO, in 2015. Did you want to become an astronaut?
Who doesn’t want to be an astronaut? [laughs] I did my best to get close! In all seriousness, I didn’t train to become one. I was part of a team designing a functional and cost-efficient apparatus that could prevent rockets from superheating when re-entering into the atmosphere.
What experiences in the industry prove valuable for you as a startup founder?
At ISRO, I had a great time working on inventions. They gave me a task, but I had the freedom to fulfil it in a way that matched my skill set. It helped me understand what working environments suit me best. I am very idea-driven, and I have an urge to bring these ideas forward. I cannot stop. When people do not acknowledge this, I get the sentiment that I don’t belong there. Now, when somebody on my team has an idea, I will hear them out. Every person has a perspective that is unique and valuable.
Moving on from the past to the future: What is next for Novo AI?
We have successfully completed the EXIST programme, which means we are losing our free office space. Now we are a part of an accelerator programme at Venture Villa in Hanover. They provide us with a workspace until market entry, and are helping us with planning the product launch, creating investor pitches, and making industry contacts •
