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With the level of excitement around, AI is clearly not a passing fad, but it is here to stay. So the growth potential of what Lymbyc is doing is enormous. Check out Satyakam Mohanty's interview with The Global Analyst magazine on his journey, trends and challenges facing the industry and the road ahead.
It was in 2012 that I decided to start something of my own.
In 2012, I had more than a decade of experience in this space, and I could see the burgeoning gaps in this sector around emerging technologies (Big Data, AI) and shifting business/consumption models (from partner based to self-service), and I wanted to address those gaps.
As a first-time entrepreneur, the first challenge was how does one even set up a company? Fortunately, our seed investors/partners had a lot of experience in that and that helped immensely. Beyond those first days, the two fundamental challenges were, 1. How does one build a team with the right set of individuals? and 2. How to build a minimum viable product before one could talk to customers?
We were trying to solve major twin problems in the data analytics space. One being – multiple data siloes with different tools and methodologies providing multiple truths. So we wanted to kind of solve this by providing a single version of truth. Second, almost all the tools out there are focused towards experts and practitioners, and, therefore they need multiple human interventions to create final insights for decision making. This eventually slows down the process of insight generation and creates a bottleneck on the number of decisions for which one can create insights.
To address these challenges, we created the world’s first virtual analyst, by combining the scale and speed of machines with the cognitive ability of human analysts replicated through AI.
Our business is a SaaS based model, available both in license based fee and a subscription model. We also have an additional one-time implementation service fee.
Getting customers is always challenging in a start-up. Given the limited access to markets and customers, it remains to be a challenge even as we go further. When you are new to the market and when people don’t know what exactly the product is, it becomes even more difficult to pitch to customers. However, our experience was not so bad. Because, having spent more than a decade in this industry, both I and my co-founders had a strong professional network who had faith in our capabilities and understood the problems we were trying to solve.
Innovation occurs in several ways. In recent years innovating in business models has been very popular, but the hardest (but also most effective) way is when we create breakthrough technology or solution IP. Since we wanted to focus on the fundamental process of insight generation itself rather than solving for point problems – we looked to solve the fundamental process of how analytics and insights are created and consumed. We had to therefore create new methodologies and technologies. This subsequently led us to create Leni that has been recognized as the world’s first virtual analyst which is capable of approximating a human data scientist. Currently, there is no exact parallel to it in the whole world and that makes our solution stand out from the overall competing solutions.
Our vision is to cut down time to insight for organizations by 90%, at a cost similar to, or less than what they currently bear and make the insight generation process more autonomous. To achieve that we created the world’s first virtual analyst, Leni, by combining the scale and speed of machines with the cognitive ability of human analysts replicated through AI.
Leni curates embedded intelligence across all data sources and provides predictive insights driven by its adaptive ML engine. Our proprietary NLP based querying language allows business users to ask questions in plain English and receive actionable insight in real time, within seconds. Leni can be trained/configured to respond to questions across the entire insight spectrum – exploratory/descriptive, diagnostic, and predictive.
Leni maintains an institutional library while fine-tuning her domain expertise and knowledge which in turn acts as a recommendation engine for new users in the organization. In line with the current standard practices, Leni ensures to have the repository updated and dynamic in the form of stock reports for business users to access anytime, anywhere.
With all these capabilities, Leni becomes a more intelligent, agile and dynamic virtual analyst with domain knowledge and analytics prowess to solve complex business ambiguities.
Yes. Apart from a small amount of seed investment, we have largely bootstrapped our venture. Now having built the world’s first virtual analyst, we are seeing a lot of interest and for us to capitalise on that, we need to focus more on growth activities like sales and marketing. So we will be looking to raise growth capital possibly.
The overall space of data science is still a sunrise sector. Within that, AI is even more nascent. As you can see, with the level of excitement around AI, it is clearly not a passing fad, but is here to stay. So the growth potential of what we are doing is enormous. The potential for our solution is literally equivalent to every business decision that is made today.
Now, that we have our world’s first virtual data scientist, Leni, our plans are centred on taking it to as many clients around the world as possible and as fast as possible. So we will be looking to do it both organically as well as through select industry partners.
We have a twin strategy – one to create opportunities organically through our established professional network, and second – through few, select, deeper partnerships with firms that are adjacent to us in this space. For e.g. firms that provide consulting or data services.
This is not a key concern for us right now because we are in a space that is still nascent and expanding. So the opportunity far exceeds the competitive threat. Also, we have created a breakthrough IP, for which, we do not have a like-to-like competitor. There are few substitutes but we still believe that we have a distinct advantage with the solution that we have created.
Our challenges would be similar to any start-up in the growth phase - Having built a significant and differentiated solution, our major challenge would be being able to translate it into corresponding client adoption. This translates into individual challenges on sales, marketing, and ultimately our capabilities to deliver on the vision for Leni.
I would like to keep it simple. The key takeaways for me so far has been:
1. Stay the course – Stay true to the vision that you have laid out for yourself, if you truly believe in it.
2. Regardless of what a start-up is trying to do, it starts with people. It becomes essential to have a very strong core team as early on as possible. The team should be able to not just help translate the vision into reality but also bring the right values to create, expand and build the team.
This interview was originally published in The Global Analyst Magazine July 2018 Startup Special issue.
Lymbyc, being the world's first virtual analyst has proven its mettle in the industry . Be it the "Most innovative Data science Product" by Aegis or "the top 10 emerging Analytics startups in India to watch out for in 2018" by Analytics India Magazine, Lymbyc is making heads turns and making headlines