Meeshkan allowing machine learning predictions on all type of infrastructure

Meeshkan allowing machine learning predictions on all type of infrastructure .,

Participating in Accelerace is more than accelerating your business. It is a community where you get access to a broad network of inspiration and knowledge. You can become part of it too! The next deadline for our Open Call is coming up. Therefore, we have interviewed three alumni about what Accelerace has meant to them. The second founder in our mini-series is Mike Solomon from Meeshkan.

What has been the biggest aha moment participating in Accelerace?

By far when we had our first lab. It was supposed to be about marketing. I came in knowing that wehad more or less changed our beachhead completely the week before and did not know if the lab would still be useful.  On top of that, everything I had done the week before was completely linked to the new beachhead and had nothing to do with marketing. I felt like a student who didn’t do their homework! The coaches quickly picked up on this shift, but their reaction was one of elation, not of disappointment. To them, pivoting meant we were in touch with our customers and willing to let go of ideas that don’t work.  In school, you learn to solve the assignment one has given to you, but that is the quickest way to fail as an entrepreneur. The “aha” moment was realizing, in a very tangible and visceral way, the difference between academia and entrepreneurship.

If you could only share one radical learning what would it be?

Picking only one is tough! One radical learning is how important it is to get the right team behind your project, from your board to your investors to your advisors to your employees.  In other settings I was in, the team grew out of a long-standing organic collaboration or was decided for me. Here, the process has been different, and it has helped me learn the value of spending time building the right team and creating a healthy company culture.  This requires constant communication with the entire team as well as a big dose of humility regarding your own strengths and weaknesses. One fun outgrowth of this learning is that we have a coach that helps us run our team meetings, which means instead of people exchanging monologues about what we did last week, we have someone that comes in and provokes us to really communicate.

Which challenges did you struggle with that made you choose Accelerace?

My main struggle was that I was a first-time founder. When I applied to Accelerace in November 2017, it was only a few months after having written the initial code for Meeshkan.  It seemed like a natural and obvious choice given how founder-centric they are in their approach, and I’d recommend it for anyone in that position.

How did Accelerace help you overcome the challenges?

I got an MBA at the University of David Ventzel. He gave me a solid understanding of the fundamentals of the startup world and tailored his approach to fit my needs.  He also gave painfully honest feedback when necessary, which helped the project grow immensely. I also met so many fantastic people and companies through Accelerace, for which I am very grateful.

Which other ideas or innovations from the other alumni have you been impressed by?

I like Amie and the fact that they’re a strong tech team and have high ambitions building a platform for collecting and structuring data for science and research purposes. Also, the founder of VI.ER.AKVAVIT, Frederick-Sebastian, is a good friend of mine now. I’m very impressed with the way he has pivoted to a new business model.

What is your best tip for application?

To be completely honest. Everybody wants to get in, so some try to make their own business look better or more mature than it is. But if you have a mature business, you don’t need to be in an accelerator. Accelerace is looking to accelerate startups so be honest with where you’re at and impress them with your potential. Interested? Apply and join our startup family:

About the founder

Mike Solomon is the founder of Meeshkan. Meeshkan is a network where you can train and test Machine Learning models in a massively parallel way on distributed nodes comprised of participating host devices. Edited September 26, 2018]]>