Yekaliva.ai: Supercharging Customer Engagement with Self-Learning Chatbot

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Damodharan Padmanaban, Founder

In the near future, there will be a time when companies would assign personalized digital assistants to their customers. The self-learning digital assistants can use their perfect knowledge of the customers’ preferences and human-like understanding of nuances of natural languages to guide them through any problems that they might need assistance with. Sounds a lot like real life J.A.R.V.I.S, the personal AI assistant of Iron Man, put into action for personalized customer engagement?

Since the inception of ELIZA, the first chatbot to mimic human conversation, chatbot technology has experienced considerable growth in past decades. However, the artificial intelligence used to power chatbots as a tool of customer support system in businesses, has its own limitations of self-learning. Conversational bots rely on the information that the businesses feed the AI to interact with customers and lack the human emotional depth. As a result, they can’t gauge the context of questions with a great degree of accuracy. A common example of that would be a failure to provide a satisfactory reply to customers in instances of inability to relate or differentiate words of different queries. This would often leave the customers with unanswered queries that add to their frustration. Identifying the shortcomings of existing conversational bots, Yekaliva.ai, one of the leading no-code conversational bot providers, introduced their eponymous self-learning AI chatbot Yekaliva to help businesses make more human conversations with their customers.

In an interview with CIO Applications, Damodharan Padmanaban, founder of Yekaliva.ai, offers an insight into how his company brings in self-learning AI to innovate traditional conversational bots.

How is Yekaliva.ai redefining the traditional chatbots?

In today’s fast-paced lifestyle, customers do not prefer to wait for a long time. Unlike their human counterparts, chatbots can cater to hundreds and thousands of customers all at the same instance. Highlighting the prowess of chatbots, a recent study by Oracle says that 80 percent of brands have planned to make the shift to chatbots by 2020. In another study, it was stated that 35 percent of consumers want their preferable brands to incorporate chatbots. On the flip side, bots fail to read between the lines and pick up nuances of human conversations. Their failure to grasp any change of context or emotional cues has been a persistent shortcoming in the domain. It was precisely for this reason that we introduced the first self-learning AI chatbot Yekaliva, named after the character Yekaliva from Indian epic Mahabharata, meaning self-learned person.

Yekaliva, our flagship product, is an AI-driven solution that provides an intuitive, scalable, and stable method for businesses to create and deploy their customized chatbots within few minutes, instead of months of complex developmental process.

Yekaliva, our flagship product, is an AI-driven solution that provides an intuitive, scalable, and stable method for businesses to create and deploy their customized chatbots

Once deployed, the bot helps businesses in customer engagement and communication, tracking potential leads, and HR related queries. Through real-time communication and in-built analytics system, Yekaliva can analyze and give businesses comprehensive reports on customers’ preferred requirements that organizations can leverage to drive personalized customer engagement.

What differentiates Yekaliva from other chatbots?

At Yekaliva.ai, we believe that without a differentiator, solutions do not hold much value to its users. Yekaliva offers additional values to businesses through the innovation that it offers to the traditional chatbot space. The problem that current chatbots pose is the limitation in processing natural languages. For example, conventional chatbots fail to respond to queries that carry the synonyms of the targeted keywords. But Yekaliva can leverage knowledge graph and context level graph that combine intent databases for customer queries and external data like synonyms, homonyms, and antonyms to accurately converse with the customers.

Another key feature of our chatbot is the intent database that we build through real-time customer communication and in-built analytics system. In its entirety, Yekaliva is a combination of solutions rather than a single solution. It combines the chatbot with the graphs and analytics solution for innovative customer experience.

Can you take us through successful implementation of Yekaliva.ai chatbot? What is your target audience?

One of the recent deployments of Yekaliva chatbot was for the Government of Queensland, Australia. They have implemented the chatbot across various organizational departments to help the citizens navigate through different services like visa, support, and security services. Yekaliva reshaped their entire citizen support model by handling 1.6 million queries on behalf of the government.

Apart from government organizations, our main target segment is small and medium businesses. There is huge scope for these businesses to increase their revenue by driving customer engagement through smart chatbots that can work round the clock across large demographics and geographies.

Typically, how long does it take for a business to deploy Yekaliva chatbot to support their customers?

Yekaliva.ai has a standard SLA of 4.5 hours. The chatbot does not take long to demonstrate its prowess and capability of the knowledge graph feature. Businesses do not require to wait long to realize the differentiators of the bot. Even without any prior technical knowledge, businesses can create their custom bot on Yekaliva.ai’s no-code platform. So it is easy and the deployment takes only a few seconds as the businesses only need to copy a simple code from our website and integrate with their preferred channel of customer engagement.

How does Yekaliva.ai’s past growth shape the future of your company?

Yekaliva.ai is a product of the Active Analytics Research Center (AARC) wing of our umbrella organization PositiveNaick Analytics. At PositiveNaick we wanted to introduce robotic process automation at the conversational level. Over the course, we have integrated features like social CRM, optical character recognition (OCR), IoT, and NLP into our conversational bots to offer a comprehensive solution to our customers.

Currently, Yekaliva is at the forefront of the change that we have envisioned. From the beginning, the self-learning chatbot has empowered different organizations to handle their customer engagement efficiently. We pride ourselves in being the innovator in the conversational bot space, and in a bid to continue this drive we have recently set up a research base in Chennai, India. For the next few months, we want to focus on optimizing the analytics and artificial intelligence to make Yekaliva offer a more humane experience in the customer engagement space.