Mr. Tanmaya Jain in conversation with the Kalzoom Team – inFeedo is revolutionalising the HR space with its AI assistant Amber. Read the story of setting up the company and learn how it is utilizing AI to interpret employee emotions.
Uma Nidmarty: So how would you define what a chatbot is?
Ayush Jain: My most layman definition of would be, chatbots are chat and bots. So now bots are anything robotic, anything automation. And then on the chat, I see it as more of an umbrella – it could be just a chat or it could be even a voice assistant or it could be any kind of program that you put in information and get out information.
Animesh Samuel: Its automated conversations. However, just a machine to give an automated conversation or an automated response is not going to suffice. In this era, data is of prime importance and especially unstructured data is very key. So if a machine is able to read and understand text like a human then what happens is that you don’t have to actually look out for a keyword but you can understand semantically what a person is talking. The machine can use both the rules that are set there and when it is trained on a neural network is able to respond proactively, intuitively to the user and the user’s needs.
The best advantage that chatbot has over a human is that machines don’t forget. So any conversation can be taken and can be dealt with that.
Uma Nidmarty: How far along do you believe we have come as relates to the AI component of chatbots and how much further do we have to go? From all our conversations so far we seem to feel that chatbots still come across as a very transactional element. So what is your opinion on that?
Ayush Jain: So what I think is that it’s just the beginning, though in fact the beginning has been in place since the 1960’s. That’s when, in fact historically chatbots came into existence. The pace of that growth has definitely become exponential now in the last two to three years.
However, we are just looking at the tip of the iceberg. Being in technology since the last ten years, we can see how technology has been changing and making our lives better exponentially. We can definitely say that chatbots are here to stay. The AI component that is the primary requirement for the chatbot industry to grow and to survive is going to become better and better.
Animesh Samuel: So when you talk about AI, ever since the 1950’s there have always been these waves about AI. When first it was proposed by Turing that a machine could think and make a decision, it was considered preposterous. To make it possible there were two factors that were not existing earlier but which exist today. One is the kind of computing power, the GPU’s that you need, the teraflux of computing power that you need to process all this data, and to learn to put it on a learning model or a deep learning network. And the second aspect of it is also the collaborative nature of the environment today.
So today people are happy to open API’s, people are happy to collaborate. Like our platform is consumed by the likes of Persistent Systems and Capita etc. where they are using our platform to build solutions for their end clients.
Uma Nidmarty: So given that chatbots today predominantly seem to pervade our mind space as relates to consumer activities. How do you think this translates across industries like manufacturing? Where do you feel the real gold mine is?
Ayush Jain: I have been a big advocate on the power chatbots can bring in areas such as governance. For example, the government today has applications, the government today has websites. But what happens is that all these things require a learning curve for the user. The information could be there, but the user cannot access it. The real beauty of the chatbot is that you can make it you so simple for anyone to understand. So now no one has to tell you to learn the website and understand where this information could be or which tab to put into. So with chatbots, all and all we see a future where these things become more seamless i.e. there is no learning curve, there is no installation etc.
Animesh Samuel: In the manufacturing part or the industry part of it, we are doing use cases like for example for Tatacom where a CXO level person, if he wants to approach a prospect – Typically an analyst would have to go through tons of data online. You know who you are meeting? What’s their background? Their hobbies, where they went to school? What’s their company’s strategic focus? Strengths, weakness etc. So typically on a platform like ours, you are able to get that information real time and the beauty is how it gets dispersed by a chatbot.
In an industry or an enterprise, there is a lot of unstructured data. There is a lot of soft communication on the platform like Skype and also chat about the enterprise outside. Any enterprise will have a social footprint today. People, employees, suppliers etc will be talking about the organises. So there is a lot of data in an unstructured format that’s out there which can be made accessible to the right person via chat and at the right time. So in that sense, the industry has a lot to benefit from making sense out of all this data that is there.
The growth of unstructured data is about ten times more than that of structured data. Also, the unstructured data is in silos.
Uma Nidmarty: So you both have talked about chatbots. What they are? And the tremendous opportunities it presents across multiple areas and applications. What do you think are the top three challenges in actually building and investing in this infrastructure as an IT services company?
Ayush Jain: I think you know as an IT services company the challenges are: one- because chatbots they have no UI. They have no other differentiator. The biggest differentiator is your NLP engine, is your AI. So you know as an IT services company you either have to invest in building your own AI/NLP which is totally very difficult. Or you have to find the right partners. In fact, one of the things like Animesh mentioned like companies like his who are the NLP experts and a company like Persistent or a company you know the other IT services company could partner together. Because as an IT services company to be able to cater to the demand and you got to be able to solve your customer’s problem. That can only happen when you have the right NLP and AI in place for the chatbot to really function. Chatbots do backfire. If the right engine is not in place.
So that’s one thing. The second thing is as an IT services company the other thing that relates equally is that the differentiators are really difficult in this space. Because again apart from your interface or your NLP and stuff you don’t have anything else that you can show. Therefore, what we have found a sweet spot is that more and more IT services company are focusing on certain industry segments through which they can build case studies. Or through which they can build their experience or work with multiple partners and figure out what works best. And third is of course educating the customers. A lot of companies are still in the thinking mode and still not open because they don’t realise the value of the chatbot. And last of course is finding good people. So these are the challenges that I see as an It services company for chatboats.
Uma Nidmarty: How about you Animesh?
Animesh Samuel: As a deep tech company, we do not have any domain knowledge apart from the core tech that we are building. It becomes very imperative for us to find the right partner, the right services company who is able to use our technology and deploy it to their clients.
Uma Nidmarty: So I think we have run out of time. And I really want to thank you both for your time and the excitement that you both show around this new technology.
Mr. Aakrit Vaish in conversation with the Kalzoom Team – Haptik provides solutions in the conversation AI space. Here is an inside look into the CUI space through the lenses of Haptik.
Mr. Sandip Kumar Panda in conversation with the Kalzoom Team – Achieving a growth rate of 101% over the past three years and being recognized as the fastest growing technology company in the Deloitte Technology Fast 50 India 2018, InstaSafe is all set to diversify and go global to solve critical needs of the customers in the cyber security space.
Predicting the Indian IT outlook for 2018, I had written that the tightening of the visa regime and the surge in Artificial Intelligence (AI) and automation would pose challenges…
64% of early-stage companies fail in the first 18 months. How to prevent your early-stage company from being a statistic…
Industry 4.0 is no longer a future trend. Manufacturing companies are capitalizing on the innovations brought by young technology companies like Infinite Uptime. Having recently raised $5 Million in Series A funding, Infinite Uptime is poised for the next phase of growth.
Raunak Bhinge walks us through the company’s journey and future growth plans
1. What has been the journey of Infinite Uptime? And what are the key drivers for your success?
Infinite uptime was started in the U.S. towards the end of 2015. That was when the product development started. We started with a few angel investors where we got the first initial funds to develop the product.
We came to India in January 2017 and that’s when we raised our seed round. We started going to market in about July 2017. The response from the market has been really good. We have been lucky that we have hit the market at a time when the industrial IoT space has just started to take off and is now is reaching a hockey-stick curve in the product development cycle.
Apart from India, we have a team in China and in the U.S. The team in the U.S. is mostly focused in research and development. And, we have sales channel partners in the U.S., Australia, and other countries.
2.You have mentioned in news articles that 80% of your customers are in India. What has been your experience with the Indian manufacturing sector? Is adoption of Industry 4.0 pervasive or only focused among the large players? What is the opportunity?
The market is quite fragmented in the manufacturing industry. There are a lot of small & medium players and a few large players – few as in few hundreds. Currently the adoption starts with the large companies. Large players are trying out different forms of industry 4.0.
The adoption among the small & medium companies is low because they are more driven by a P&L kind of a system.
How pervasive it gets, we will see with time. However, at least everyone’s trying it out. You never hear a “no” in the industry today. This was probably not the case about five years’ back or even three years back.
There are a large number of small & medium sized companies who are exploring solutions such as ours. But they are looking for the RoI proof with the large players before they jump into it.
3. From a sales point of view, what is your approach in reaching out to a small & medium players and large players?
The market has a very large number of small & medium players, so to go to them directly is not feasible for most IoT companies. We mostly use a channel and system integration partner distribution network for sales. We do pilots with both the SMEs and large players. It is such a new concept that until and unless they see the benefits they won’t spend on it. Our strategy is the same for both, and that’s how it will be. Whether you are one machine, one manufacturing line, or 100 you want to see results before you invest.
4. You recently raised $5 million in Series A funding. What are your growth plans?
We plan to channelize most of it in team building. We are building a pretty substantial team here in India. We have some USPs in our product. We want to focus and ensure that we always stay on the top of that. Our focus is to get a good R&D and a good innovations teams and build on top of that. Also, customer acquisition is going to be very critical for us.
5. What are the challenges that young companies like you face that might hamper or hold you back from scaling the business?
We have been lucky to hit the market at this point of time in IoT. The timing matters a lot. If we had started five years back, we would be struggling to get this kind of market traction.
For us the barriers are not on the market side or the adoption side. Our challenge lies more on the ability to execute well and better than the other players. It is mostly on an execution and on innovation fronts where we need to build up and thereafter build the business on those USPs.
6. You are mostly concentrated in manufacturing. Can your solution be used in other verticals like retail, healthcare etc?
No, we are very focused in manufacturing and we will continue to do that for at least the next five years. We are not a horizontal solution that can be used by anyone and everyone. Our USPs are specific to certain types of equipment’s and we would like to keep it that way.
7. What would you suggest a company that wants to get into Industry 4.0 sector now as a solution provider?
The point we would like to mention to new companies is that they should find their niche and should be focused on certain problems and be very focused on certain technologies. They should choose to specialize across a vertical rather than a horizontal where they can scale much faster. Horizontals have already been established, so being yet another horizontal won’t help.
SMEs in the BPM sector must adopt the approach of specializing in the vertical industry and they must use customer-centric thought processes for channeling sales efforts. The success of a sales and marketing strategy lies in the approach that is used to reach new prospects and improve conversion rates…
It will need a concerted effort by the government, academia, research institutions, industry associations and industry to make India a force to reckon with in AI-led growth and enable manufacturing
There are many who believe that China, with its burgeoning costs, is losing out in outsourced manufacturing to more nimble and cheaper competitors such as Vietnam and Thailand and there has been hope that with some concerted investments in the right areas, India too will finally find its place in the global manufacturing sun. However, the time for projecting India’s pool of engineering manpower and ability to do labour-intensive manufacturing at scale and quality is now over and the baton of leadership will pass to those who are truly able to design and build factories of the future, powered by cyber-physical concepts, machine learning and artificial intelligence (AI).
Manufacturing firms of the future will use predictive analytics to estimate demand for each product category based on demand and environment patterns and also develop new products through generative design principles on an ongoing basis to satisfy demand of discerning customers. Virtual agents will interface between information systems and production processes and feed fully automated factories with planning, materials and process inputs on a real-time basis. Materials handling, location of parts and warehouse management and utilisation optimisation with digital aids such as augmented and virtual reality are commonplace today. The real cutting edge will be provided by AI applied to quality defect management through image recognition, process quality prediction and large-scale prescriptive approaches, failure predictions and predictive maintenance including support of self-healing machines. The future is all about maximising throughput with consistent high quality and redefined role of engineering talent in manufacturing.
Jabil, one of the world’s leading designers of digital factories with several successful implementations in Asia and Latin America, enables real-time predictive analytics for its customers by connecting equipment, sensors and people and claims an ever-increasing accuracy level for predicting early equipment and process failure leading to energy, scrap and rework savings and decrease in manufacturing cycle time. Companies such as GE and Siemens, both pioneers in digital manufacturing, have reported success with the use of AI — GE through the deployment of digital twins, which models and tracks the state of the engine and provides continuous analytics and predictive maintenance suggestions and Siemens through a combination of AI with neural technologies in its Gas Turbine Autonomous Controller Optimizer which ensures that every gas turbine has over 500 sensors continuously monitoring temperature, pressure, stress and other variables enabling the neural model to alter the distribution of fuel in the turbine’s burners on a dynamic basis.
Recent studies by PW and BCG place AI and advanced analytics at the core of smart manufacturing
Advanced Analytics at the core of smart manufacturing with recent trends moving beyond traditional inventory optimisation, maintenance and data security usage to intelligent factory operations, the application of digital twins and human robotics collaborative ecosystems. They predict that humans in the future factory will be entrusted with the higher-level tasks of programming, maintaining and coordinating robotic operations. With AI driving advanced predictive and prescriptive analytics and replacing SMAC (Social Media, Mobility, Cloud and Analytics) as the core of digital transformation, it is predicted that AI will also be a valuable tool outside the factory, enabling continuous logistics and supply chain monitoring, providing route optimisation for inward and outward flow of materials and finished products, tracking customer expectations and emotional states through voice analysis at service call centres and providing personalised product recommendations for customers based on deep learning of their previous responses and social media footprint. The use of AI and advanced analytics is limited only by human imagination as newer customer journeys evolve and design thinking enables early anticipation of every need.
The good news is that the adoption of digital technologies in Indian manufacturing firms has been placed by recent research at 27 percent against a global digitisation level of 33 percent and is expected to cross 60 percent in the next five years. It is also heartening that thanks to an increasing awareness of Industry 4.0, leading industry associations such as the Confederation of Indian Industry are making smart manufacturing the core of their agenda, and there is a proliferation of scaling start-ups in the Internet of things and robotics space even Indian SMEs are placing digital and Industry 4.0 at the core of their agenda for the future. Small-scale solutions are being piloted and investment in automation and analytics are beginning to bear fruit.
However, a major commitment at national policy making level and also across industry sectors towards AI is needed to position India as a true leader in new manufacturing solutions. And the competition is already planning this on a gargantuan scale. China has committed to add over $150 billion to its economy through AI by 2030 and many announcements of magnitude have been made including an AI support fund of $5 billion in Tianjin and the Beijing municipal government declaring plans for a $2.2 billion AI development park. The research coming out of China rivals the US in quantity and quality and it will need a concerted effort by the government, academia, research institutions, industry associations and industry to make India a force to reckon with in AI-led growth and enable the manufacturing sector to finally stake its claim to global leadership.
Seizing the Digital Transformation Opportunity – in conversation with Mr. Devendra Deshmukh, CEO & Founder, e-Zest Solutions…