Anyone who has been in the spotlight will know that once the lights dim, the silence that follows can be quite as disconcerting as the furore before. Firmly in the media and industry glare during his tenure as the managing director and CEO of Infosys for three years, where he was the subject of constant scrutiny and evaluation, for Vishal Sikka life after Infosys has not been quite so befuddling.

It’s been a little over two years since he left the hot seat at India’s second-largest IT services firm, but life hasn’t changed much for Sikka, 52. Since then, his time has been spent on a well-deserved break, teaching assignments, consulting work, and a focussed commitment towards building his venture Vianai Systems, an artificial intelligence (A.I)-based enterprise platform. The Palo Alto-based startup has already secured $50 million in funding. In an email interview with Fortune India, Sikka, founder and CEO, Vianai Systems, talks about his latest venture, the changing global landscape in A.I., and his learnings from his past roles at SAP and Infosys. Edited excerpts:

What made you start Vianai Systems? What was the rationale behind it?

I have always been passionate about technology being a human amplifier. Technology is something that can improve our ability to see more, do more, and be more. It allows us to do greater things.

After Infosys, I had just turned 50, and thought 25 years ago some of the biggest most impactful technologies and organisations of today didn’t even exist (Google, Amazon, Facebook, Tesla, and Uber). Steve Jobs had not returned to Apple yet. Then, I thought 25 years from now when I’m 75, new technologies and organisations will have come into existence that don’t even exist today but they will be the ones that change the world.

So, given my professional experience of having held leadership positions at two big companies, my unique domain expertise (Ph.D. in A.I. from Stanford University), and prior experience with transformations with enterprise software and services and with A.I., I believed it was time to go back to the drawing board and create something new. After all, as my friend, mentor, and now an adviser to Vianai, Alan Kay once said, “The best way to predict the future is to invent it.”

Vianai Systems recently raised $50 million. Could you share who are your key investors?

We have not made the identity of our investor group public at this time.

Our advisors include: Henning Kagermann, former chairman and CEO of SAP and chairman of Acatech; Alan Kay, Turing Award winner and computer science pioneer; Divesh Makan, founder of Iconiq Capital; Indra Nooyi, former PepsiCo CEO and member of the boards at Amazon and Schlumberger; Sebastian Thrun, CEO of the Kitty Hawk Corporation, and co-founder and chairman of Udacity; and John Etchemendy, former Stanford University provost and co-director of its Human-Centered Artificial Intelligence Initiative.

How are you looking to utilise the funds?

We will continue to recruit the top tech, sales, delivery, and design talent in order to build out our platform, close deals with marquee names, and deliver customer success. With our funding, I was able to take financial uncertainty out of the equation. Startups typically don’t do $50 million seed rounds, but with this, we don’t have to spend our cycles worrying about funding. Beyond our funding, we also are already generating revenue. So we are in good shape.

Was it easy for you to raise a large seed round? Was your past background helpful in convincing investors?

I know it is not easy for most companies to get $50 million in seed funding. I did not want to spend too much time raising funds, and I was fortunate that I was able to quickly find the funding support I needed for the company.

Currently, what is the focus of the business in terms of projects that you are working on?

We are focussed on driving massive short-term value for large enterprises with A.I.-driven solutions. For example, we have worked with Bank of New York Mellon on predicting failures of certain types of transactions that go through their systems. These failed transactions amount to tens of billions of dollars a day. If you are a manufacturing company, even if you make-to-order, the issue of working capital is fundamental to your operational efficiency and financial efficiency. In companies with large numbers of physical assets, this directly impacts their bottom line and their stock price. So working capital management using A.I. is one of the areas we are working on along with others. Vianai helps clients with problem finding using design thinking, and then work with sophisticated A.I. techniques to do the math with data and drive short-term business value.

Could you give us an idea of how your A.I. platform and design thinking approach will help clients across industries?

At Vianai, we have mastered a purposeful combination of design thinking and A.I. We believe that effective problem-solving starts with effective problem-finding. Design thinking techniques help us with both problem-finding and problem-solving. This powerful combination has the potential to greatly improve the success rate of A.I.-driven projects in the enterprise. In our work with clients, we first apply a human-centered and empathetic approach to research the concepts, seek to understand, find and define the business problem that has a value to the organisation and then look to see how data and technology can help gain insight into that specific business question. We work at the intersection of desirability, feasibility, and viability.

What differentiates your startup from other well-established players in the A.I. business?

There are several thousand A.I. startups…I’m sure they’re all unique and doing fantastic things. The way I live my life and have done my work is to focus on customer needs and market opportunities. If you focus on that with discipline and dedication, the competition issue takes care of itself.

This is also my approach at Vianai. We aren’t defining ourselves in terms of whatever else is going on in the competitive landscape, but rather in terms of the un-resolved problems and opportunities that we have identified at potential customer organisations and going after those. In that sense, what we are doing is significantly different from what anybody else is doing, whether at a startup, or even at a large company. It is about dramatic improvement in development simplification and explorability of A.I.-based systems. With our technology, we can simplify the expression and the execution of these systems massively—by hundreds of times, if not more.

Is Vianai your first venture after you left Infosys in 2017?

Yes. But I did do some teaching, consulting, and advisory work in the interim.

Richard Feynman used to say, “the best way to learn is to teach,” so I taught two classes in the past few years; one in California and one in China. I did some consulting to help some organisations with their strategy and execution at the request of friends who are top executives at these companies, and also took the time to identify the most important business issues that can be solved with A.I., and created blueprints and prototypes for a next-generation platform. I am also serving on the supervisory board of the BMW Group and on the advisory board of the Stanford Institute for Human-Centered Artificial Intelligence (HAI).

Any learning from your past roles at SAP and Infosys that you feel could be useful as you build your startup?

I was fortunate to participate in the transformational journeys at both the companies. Large companies have a massive scale, and they have many benefits because of it. Every successful company does things in big ways, reaching large numbers of customers and is able to affect the work of massive numbers of people. However, they can also face significant challenges in making transformation happen. The burdens of legacy are real, but they can be surmounted by committed leadership. There are existing markets, existing businesses and existing processes that have a huge amount of inertia and entrenchment that need to be navigated.

Many of these skills and learning are not completely irrelevant to a startup and vice versa; so I believe everything I did previously is a valuable asset for what I am doing today.

The technology landscape globally has undergone a paradigm shift in the last decade. How has your journey been so far in that context?

Yes—the advent of cloud and mobile has shifted the enterprise technology landscape significantly, and now, the potential of A.I. represents a seismic shift of proportions we have not seen. David Patterson and John Hennessy, who won the 2017 Turing Award, in their Turing lecture last year talked about how it’s a fundamentally different age now of semiconductors. The traditional Moore’s Law is being replaced by domain-specific architecture for chips, especially for A.I. In enterprise landscapes, we have recently moved from systems of record to systems of engagement, building upon the democratisation and proliferation of technology. Today, we have the opportunity to create systems of intelligence that can bring A.I. techniques to transform all aspects of a business and do so in a way that is transparent, explainable, and explorable; inclusive and accessible to a massive number of developers.

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