In our quest to identify and share with our community some of the unique stories, we interviewed yet another passionate entrepreneur and data scientist, Muktabh Mayank co-founder at ParallelDots. His startup is an AI-first company, which works with Consumer Packaged Goods companies globally to improve their retail execution. Let’s read more about Muktabh’s exciting journey, way forward and his advice for others!
Excerpts from our exclusive interview with Muktabh:
Tell us a little bit about yourself and your journey, please;
I come from a middle-class family from UP consisting of my parents, my wife Anshita and my brother.
Professionally, I completed my graduation from BITS Pilani in 2012. My majors were in Information Systems. I then joined Opera Solutions as a Data Scientist and that’s where I met Angam, my cofounder. Ankit my other co-founder was Angam’s friend from IIT Kharagpur who came back from Australia to start our company. We founded our first startup in 2013.
At ParallelDots, My task is to solve complicated problems in CPG-Retail computer vision using state of the art Artificial Intelligence algorithms. Bringing these algorithms from labs into the real world where they can help enterprises enhance their sales execution is exciting and challenging at the same time. Apart from developing the AI and product, I was also tasked with building ParallelDots’ ace data science team. I am proud to say that ParallelDots’ Data Science team has published research work infamous AI conferences and our alumni are doing AI research in topmost universities worldwide.
I also answer questions on Quora for the community on Data Science, Machine Learning and Programming and my answers have been viewed over 2.5 Million times there.
Why did you choose entrepreneurship over a job?
Many factors contributed to the decision. First was I wanted to work with cutting edge technology. The type of deeptech systems you can work on as a startup can otherwise be done only at R&D divisions of big companies or by research labs in universities. Both of them require a lot of luck and time to get into, while a startup gives you a sure chance to prove your mettle. The second is the sense of ownership a startup offers. It is a great feeling when the technology you have conceptualized and built from scratch is used by businesses and enterprises. The third reason is the thrill. While people wait for a chance to make a dent in their regular jobs, in startup your actions can make or break a deal and sometimes the entire company. I love the feeling. It’s like the adrenaline rush you feel riding a jet ski.
How do you find the industry/niche that you’re in?
That is a question I can write a whole story about. We, three co-founders, were sure that we wanted to build a Deep Tech company right from the start. Our first product (in 2014) was around news business where we built a timeline of events surrounding online news articles using Machine Learning. Monetization in online publishing is hard and thus we had to shut the idea down. We also launched a consumer app Cornea.ai, which allowed users to use any art and natural photo as a filter instead of fixed filters like Instagram and Prisma. This app also had a virality prediction AI algorithm to suggest user what pic to upload for most likes. Over 50000 downloads by the time we decided to shut it down. We also developed our inhouse R&D team and did some groundbreaking research work in Deep Learning. While all these are cool technologies, we kept hitting walls. We then decided to take a break for over half a year and decide what we wanted to do with the cool technology capability we had developed. The answer came to us by itself as enterprises, especially from CPG (Consumer Packaged Goods) space were approaching us, interested in our technology. We decided to take advantage of the opportunity and the current version of our business around CPG Computer Vision started taking form in 2018. We converted this capability into product and as of now, our company has grown its ARR by 5X in just a year and have a team of around 50 people.
What gets you out of bed in the morning i.e. what’s your source of motivation?
Mark Twain once said,
“Find a job you enjoy doing, and you will never have to work a day in your life.”
This is true. I always wanted to work on cutting edge engineering and my company offers me exciting opportunities in the field. So there are no need-some-motivation-to-drag-yourself-to-work days. But that does not mean all is milk and honey, a techie wants a peaceful life to write complicated code, but as a co-founder, you are expected to write code along with working on open-ended business decisions. This going out of comfort zone requires motivation and there I think my family is my motivation. My family has always encouraged me to not run away from challenges and put up a good fight.
What challenges/obstacles did you face in your journey so far?
Many. A startup’s journey is a challenge every day as you are trying to create a path in uncharted territory. I was just another Data Scientist in 2014 who was tasked to build this product with most cutting edge technology and create one of the best AI R&D teams in the country. This requires to solve many things, like recognizing, attracting and retaining talent and staying abreast of the latest research going on in Deep Learning. You can also add on top of it struggling to find a product-market fit and adapting strategies according to the market. It took us years of perseverance as a company to build what we have today and we are proud of it.
What comes first for you – money or emotions?
I think emotions come first for me. However, I would not say that money is not a driver for me and I am not affected by the thought of making good money. I think money comes best when it comes as a cherry on top of the cake of self-satisfaction.
How do you handle the pressure and manage stress?
I have gotten into mindfulness recently and it helps to diffuse stress when one is having a tough day. I am trying to make it a more regular part of my life. The other way to lessen the stress is what I think David Goggins calls “Mental Callus”. Just the memories of previous times one succeeded out of their comfort zone can give one confidence to get through the pressure. In the end, there are times where one has to just talk and vent out in front of their family.
What is one strategy that you believe has helped you grow as a person?
I think that I have tried to develop more empathy towards other people and learnt to look at both sides of the argument. I always wanted not to be the a-hole in the discussion and this has helped me become better at my objective.
In your opinion what are the keys to success?
I think it will be better to answer this question when I am like really successful. But I know a few things that I am sure without which success is not possible: hard work, good planning and adaptability.
What advice would you give to someone starting out?
Sort out the basics first. A startup has to meet some very essential set of criteria to be successful:
1 – Focussed offering
2 – A large market
3 – A product-market fit and
4 – Good usage(B2C)/revenue(B2B) growth
There are 100s of other metrics besides this like number of GitHub stars, a number of papers/patents, breadth of offering, flexible HR policies etc., which might look good for a large company, but they are just like extra-curricular for the startups (you still need passing marks in your courses). So if you are starting out, be paranoid about the thought of not getting these basic criteria right. Also, do read Paul Graham’s essays.
BrilliantRead is committed to bringing stories from the startup ecosystem, Stories that reshape our perspective, add value to our community and be a constant source of motivation not just for our community but also for the whole ecosystem of entrepreneurs and aspiring individuals.
Note: If you have a similar story to share with our audience and would like to be featured on our online magazine, then please write to us at [email protected], we will review your story and extend an invitation to feature if it is worth publishing.
