A couple of weeks ago I shared with you what my first few days revealed to me about Infosys Nia™. I was fortunate to get time with two of my engineering colleagues, Sudipto Shankar Dasgupta and Ganapathy Subramanian, who have worked extensively on Infosys Nia. Sudipto is Vice President and Head of Engineering for Platforms at Infosys responsible for the development of Infosys Nia. Ganapathy is Vice President and Solutions Head for Platforms at Infosys responsible for solutions and customer implementations built on top of Infosys Nia. What materialized was a fascinating and informative conversation about the platform, the underlying technology, and the impact on clients. Here’s how the conversation unfolded:

Sudipto Shankar Dasgupta’s thoughts on Infosys Nia’s engineering scope

Me: What does it take to bring an artificial intelligence (AI)-based automation platform like Infosys Nia to life?
Sudipto: Well, Infosys Nia comprises of several critical components. At the core is knowledge and underlying it is a data-based platform powered by purposeful AI. To bring Infosys Nia to life, we seamlessly integrated automation, data and knowledge platforms. This was the first step – the amalgamation. The second step was to gain a strong understanding of our customers’ business problems that Infosys Nia had to handle. This is dynamic and will keep evolving, from one phase to another.

Me: What is unique about how AI technology has been integrated in Infosys Nia?
Sudipto: When we at Infosys talk about AI, it is always purposeful. We try to understand how AI innovations can be instantiated for business processes and be a differentiator for customers. We also consider the massive amounts of data customers generate together with the knowledge derived from it along with machine learning techniques. In short, AI is not considered in isolation, it is looked at comprehensively, as a way to handle knowledge in order to offer customers differentiated value.

Me: How do you work with data scientists for Infosys Nia?
Sudipto: For any organization, data scientists are critical resources because there are very few of them. Our opportunity was to understand data scientists’ roles and responsibilities and automate the tasks they would traditionally perform. This way, even if there are complex issues that data scientists would typically handle, Infosys Nia will be able to manage it. This will reduce the organization’s dependence on data scientists.

Me: How do you see Infosys Nia advancing in the future?
Sudipto: We are constantly asking questions that will help us keep a finger on the pulse of AI and focus on innovation – “How can software and hardware overlap?” “How can impact analysis or root-cause analysis be carried out better?” “How can traditional dashboards be improved with Augmented Reality (AR) and Virtual Reality (VR)?” We are also thinking about video and image processing advancements to uncover customer landscapes and understand their work. This is the future we are looking at.

Me: What does it take to maintain the momentum and keep your customers ahead in a continuously evolving AI technology landscape?
Sudipto: Yes, AI is a dynamic space with innovations taking place constantly. It’s driven by different ecosystem players like academia and open AI community, where developers and industry leaders contribute and share. Infosys ensures that we stay ahead of these innovations, keep customers hidden from the burden of the changes and help them reap the benefits rapidly. To achieve this, the AI platform should be able to seamlessly integrate primary components like automation and analytics with new technologies.

Ganapathy Subramanian’s views on customer Proofs of Concept (PoCs) as a way of fostering confidence in Infosys Nia

Me: What in your opinion is the benefit of an Infosys Nia PoC to a customer?
Ganapathy: With Infosys Nia we ensure that our clients get to experience, in their own context, the art of the possible with AI. This approach has been developed such that customers can solve business problems and see the value their data provides within short time periods. PoCs help us review what is, and is not, working for clients which is addressed by rapid engineering capabilities as needed. In essence, the ability to gauge outcomes quickly has been our inspiration for developing PoCs to test real-world situations.

Me: How do you help clients take the AI route with Infosys Nia-based PoCs?
Ganapathy: In the past three quarters, we have conducted over 20 proofs of value with respect to Infosys Nia which are now going into production. Across the board, Infosys Nia has offered good results. Take for instance, a PoC deployment we did for a European apparel and retail manufacturing company that wanted the capability to forecast design cost, a critical factor impacting a time-dependent final product – that season’s collection. In order to drive value, Infosys Nia based its recommendation on historic data across a wide category of apparels. Similarly, we have done transformative implementations for various industries and sectors like railroad and banking. It is important to note that most were done in just 6 to 8 weeks.

Me: What is the importance of doing PoCs, for both Infosys and clients?
Ganapathy: From an engineering point of view, Infosys Nia is more than a platform. We can leverage it to engage meaningfully and iterate fast with clients – which PoCs allow us to do. It helps engineers rapidly change the way they create a roadmap for the client. Next, from the client’s point of view – they just want to see value, fast. A PoC lets us offer this iteratively with real data. It also gives clients the opportunity to collaborate with engineers to define the roadmap the way they want it.

Me: How ready were customers to adopt Infosys Nia?
Ganapathy: For a while now, our customers have been hearing about AI and cognitive technologies like machine learning. Our customers are eager to capitalize on the potential that it brings. What’s more, our customers are now getting good at collecting, storing and leveraging data because they understand that is where true value lies. Combine this with their drive to be more efficient, improve business processes and stand out from the competition, and they are all geared to leverage AI.

Me: Can you share any key learnings arising from your PoC work with Infosys Nia?
Ganapathy: I’ll touch on three things. First, the space of machine learning is dependent on data. Though the platform is positioned to learn and amplify, a lot depends on incoming data. This helps the platform re-calibrate. Secondly, as I mentioned earlier, different clients are in different spaces related to AI. Understanding where the client is and what they have (in terms of data) are key to creating a plan that will align best with their needs. Thirdly, doing PoCs has helped us look at necessary and critical elements to be integrated into the platform in order to offer the best possible value to our clients.

It was clear as I walked away from my conversations with Sudipto and Ganapathy that Infosys Nia isn’t just cool technology. It is grounded in the foundational principle of being deliberate to provide businesses the differentiating value they seek in an ever-changing dynamic business landscape. It was abundantly clear that making available the option of PoCs is a strong way to reach out to clients so they can recognize value quickly and iterate fast to realize it completely.

As final questions to both Sudipto and Ganapathy, I did ask them why working on Infosys Nia was exciting to them. Here is what they had to say:

Sudipto: Knowing that the world is becoming more accepting of AI is truly exciting. In the coming years, we will witness automation taking on several roles that humans do. This will free up humans to try out other tasks. The world is moving more to AI, the cutting-edge, disruptive technology of the future. And since we are working on this with Infosys Nia, it is thrilling and exciting.

Ganapathy: Today, we are at an inflection point – technology-wise and research-wise. The underlying factors enabling the development of AI – like compute power – are not new but they have evolved by leaps and bounds recently. We can now do everything in this realm cheaper, faster and better. Add to this the fact that software is evolving thanks to the focus that academia, the open source community and top IT companies are placing on it. On top of this, improved data collection and analysis tools have matured significantly to allow companies to maximize data. All this makes for a very exciting time to be an AI engineer.

Our engineers are clearly excited. Businesses need to step forward to embrace this technology, and this approach of bringing Purposeful AI™ to the enterprise. I happen to know we will be discussing business use cases and Infosys Nia at Confluence 2017. If you are not going to be there join the conversation here or at: @PurposefulAI.

@puneetsuppal


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