Incubator 1871 | Interview of Leonardo Zubalich

Leonardo had a coffee with Rebecca Haass, Director of Business Development of Entrigna. RTES – Real Time Expert System is a platform that analyses big data and enables real time decision. The technology allies are Rules Engine, Complex Event Processing, Machine Learning, Artificial Intelligence, Optimization, Clustering/Classification.

What inspired you to start this company?

One of our founders, Murali Kashaboina, was working as the Managing Director of Enterprise Architecture at a major airline. His team needed to create a solution that would use several different machine learning functions. However, he soon discovered that there were no products on the market that would perform the functionality his team needed. As a result, they ended up buying two AI platforms, connecting them and creating a custom solution. His team spent almost 2 years creating the solution, and since the two platforms weren’t meant to work together, there were many compatibility issues.

In addition to the high implementation cost and ongoing full-time staff necessary to support this hybrid solution, the airline also had to pay for two licenses every year since two platforms were used. Overall, this was an extremely costly and complicated project. After this experience, Murali thought other companies must be having similar challenges so he and the other 3 co-founders founded Entrigna.

Entrigna’s AI platform, the Real-Time Expert System (RTES) contains all of the major machine learning tools along with a rules engine and an optimizer. So ultimately, solutions built on RTES can grow and change seamlessly with a company’s needs. 

In a few sentences, what do you offer to whom? 

Entrigna’s Real-Time Expert System (RTES) is an AI-powered platform that includes all the major machine learning and deep learning algorithms along with an optimizer and a rules engine. Our platform lets companies not only predict when events will occur but also lets them take actions on those predictions in real-time. Entrigna also licenses the Data Science Canvas, which is a visualization tool that let’s users create data models with all of RTES’ pre-built algorithms and connectors.

What are your immediate goals?

Our immediate goal is expanding into new regions and industries. Last year we released the Data Science Canvas, a data model visualization tool, and are focused on increasing it’s adoption.

Product-wise, what are the biggest challenges?

Our AI platform has the potential to be revolutionary for companies. However, as with many new cutting edge technologies, AI solutions can be slow to adopt. Also, since all of our solutions are custom, it’s challenging to get business users to visualize what a solution would look like and how to calculate how much value it would bring to the company.

What will the company look like in a year from any and all perspectives — product, people, team, revenue?

We’re expecting high levels of growth over the next year.  We recently became partners with Amazon, Hortonworks and Intel and have several potential partnerships in the pipeline. We are also releasing an out of the box scheduling optimizer for the healthcare industry. This product is our first “out of the box solution” and basically it gets patients to the right healthcare professional faster, which leads to happier patients and also more revenues for providers. We are also on-boarding our second sales person – doubling our sales team in less than a year!

How about in five years?

Companies are becoming more comfortable with adopting AI solutions every day – and fact McKinsey Global Institute expects that by 2030 70% of companies will adopt at least one AI solution. Because of this, demand for products like ours will increase significantly. In order to keep up with demand we plan on increasing our application development and sales teams. Also, to make sure that our product continues to be on the cutting edge, we are planning on exponentially expanding our data science team.

What’s the origin of your company name?

Entrigna’s name is based in Latin – “En” means “to do” and  “Trigna” is based on trigonometry representing something 3 dimensional. So overall, Entrigna means doing something multi-dimensional. Also, it sounds like “Intrigue”.

What are the advantages of being in an incubator?

One of the best things about being at 1871 is the amount of energy you feel when you walk in. 1871 is full of people with brilliant ideas and they’re hungry to succeed.  Also, there is an unbelievable amount of workshops and mentor sessions to attend. When you’re working in a start-up you wear many hats and it’s challenging to be a jack of all trades – especially in areas where you have limited experience.

Speaking for myself, it been incredibly beneficial to attend workshops that let me keep up with the latest marketing trends and tools and also to have industry leaders be a sounding board for different strategies.

How critical is the business model in a technological startup? How can the best business model be identified?

The business model is extremely critical for success. When Entrigna started, the team mainly focused on consulting work – we would create an end to end custom AI solution for a customer and store that solution on the cloud. However, in technology — especially in something as cutting edge as AI, if you want to succeed you have to adapt and adapt quickly to your customer’s business needs.  Two examples come to mind in how we had to adapt our business model in order to survive. First, when we were founded three years ago, it was rare for a company to have an IoT solution, much less an AI powered one.

However, as time has progressed AI-powered IoT solutions are becoming “less scary” to corporations and many are adopting them. But the power of an IoT solution comes when actions or insights are made the moment an event is detected. As a result, today there is more demand for data models to be run on the device, or “The Edge,” rather than on the cloud.

In order to meet this demand,  we not only had to tweak our product to run on the edge – it now can be run on something as small as a Raspberry Pi — but we also had to create a different pricing model for Edge based solutions. Another example where our business model was critical was in our ability to scale.

When we first started we were only doing consulting work. However, last year, we realized that if we were to scale as quickly as we wanted, we needed to offer an option to license our product and let companies develop a solution in-house. Because of this, we created and released our Data Science Canvas which is a GUI based data modeling visualization tool that let’s users create data models and connect to their data sources without having to write code. This option has been extremely appealing to larger companies and also to consulting firms that want to offer AI products but don’t want to develop the algorithms in house.

What “doing startup” means for you?

Startup life is fast-paced, energizing and not for the faint of heart. I love going to work every day knowing that my day will more likely than not be different than the day before. One morning I’ll be doing demos with our sales team, that afternoon working on cash flows and the next day scheduling our communications for the month.  At a startup you’re constantly learning and implementing – so even though the hours may be long, the work is extremely rewarding, because you’re seeing the results of your actions every day.

What hints can you give to those who would like to start a business?

If someone told me that they were starting a business I would recommend that they put together an experienced, diversified and direct “board.” When you’re involved in a start-up there are so many decisions to be made, not just about the product, but about marketing, sales, accounting, staff, and inventory management.  If you’re going at it alone or with a small team it’s unrealistic to think that all of your needs will be met internally. It’s critical to have a group of people who are not afraid to tell it like it is and who can be a sounding board especially in areas in which you’re not strong. 

What is “innovation”?

Innovation is coming up with a USEFUL idea that no one has implemented and articulated.  True innovation is all about providing value in a way that hasn’t been thought of before and effectively communicating that to users.