Artificial IntelligenceInterviews

“Enterprises derive full value of conversational AI only through end-to-end chatbot platforms”— Sairam Vedam, CMO,

9 Mins read
Sairam Vedam, CMO,

“With time, AI-powered virtual assistants or chatbots are expected to evolve into tools for enterprise business transformation beyond just being conversational interfaces. Enterprises using virtual agents for automating and addressing customer queries, will extend them to take action after customer requests. Enterprises can achieve the real value when conversational AI is used for business transformation by connecting conversations to business systems.” – Interesting points made by Mr. Sairam Vedam, Chief Marketing Officer, in an interview with Wire19. is the industry’s first and only enterprise-grade, end-to-end conversational AI-powered bots’ platform to design, create, train, test, and host AI and NLP-powered chatbots for use in the most popular consumer and business communication channels.

Continue reading to know more about AI, IVA and their trends in his exclusive interview.

1. What’s your take on AI adoption in 2019 and conversational AI?

“By 2020, 50% of analytical queries will be generated via search, NLP or voice, or will be automatically generated.” – Gartner

2018 marked the arrival of artificial intelligence (AI). Not just in terms of hype it generated, be it the number of papers published or attendance to various industry events, or mentions on corporate earnings calls or even parliamentary hearings, but in case of its actual application in real world as well there was much progress.

2019 will be the real turning point in my view, which will radically advance the adoption of conversational AI. The impending 18 months will be crucial for its rapid expansion and implementation. But for me, personally, it’s gratifying to see the success of an idea close to my heart.

There are reasons to be optimistic. A recent McKinsey survey, which tracked the percentage of executives whose companies are using variants of AI in at least one business function or unit, has found an interesting uptake on use of applications such as image detection, voice enablement, natural language understanding, voice search, translation and data mining. That’s interesting.

Source: McKinsey AI Adoption Survey, 2018

2. Tell us what’s unique about Conversational AI?

Conversational AI comprises a group of technologies, closely allied, such as NLU, NLP, NLG, and machine learning etc., which when combined and used in specific contexts, help build powerful conversational systems.

  • Conversational intelligence goes beyond natural language understanding. Today, you have the ability to glean understanding from conversations. There are solutions and tools that help gain intelligence from conversations whether in spoken or written form. This understanding is not simply natural language understanding, but a higher level of knowledge that comes by analyzing content at an organizational level. Intelligence does not imply common sense reasoning, but rather application to specific already modeled domains. This way, you derive insights from huge piles of data captured in conversations.
  • Platforms with simplified bot development processes. A plethora of platforms are now available in the market that facilitate the design, development, management, and operation of conversational solutions leveraging natural language enabling technologies and third-party APIs.
  • Proliferation of human-machine interactions in natural language. Chatbots have come of age with enhanced abilities to simulate intelligent conversations with humans in natural language. Most times, these interfaces that are non-industry specific, and apply across a range of domains and functions.
  • Regular messaging turning intelligent. Our ubiquitous messaging platforms such as email, text messages, and other human-to-human communication – can now be programmed to be smarter with a range of possibilities to ease communication.
  • Voice assistants with a range of capabilities. Spoken, conversational interfaces, that come embedded in hardware devices, and enable spoken interaction and connect with cloud-based ML capabilities.

Each of these, again, have a specific growth trajectory with deep implications for the industry. Take, for instance, the improvements in NLP technology. It has given a huge fillip to proliferation of virtual customer assistants (VCAs) in customer service.

3. What are the reasons behind growth of Intelligent Virtual Assistants (IVAs)?

Gartner predicts that by 2020, 25% of customer service and support operations will integrate virtual customer assistant technology across engagement channels, up from less than 2% in 2015.

In near future, virtual assistants will be the first line of interaction with customers in the coming decade, just like the way the 1990s were dominated by the telephone call center and the 2000s saw the shift to websites and email.

Virtual assistants will form a synergy with other digital solutions such as IoT, analytics and image recognition, and will become an interface that compiles the information from these devices to offer meaningful insights to users. When clubbed with advanced analytics capabilities, VCAs can process information much faster than human agents and will predict consumer needs and behavior.

4. How is driving IVA innovation and adoption?

Some major trends in the IVA market, in the last 12-14 months, have been a shift from rule-based solutions to AI-driven IVA solutions. These AI-powered IVAs come with enhanced capabilities for solving much more complex interactions such as sales and marketing, payment collections, employee support, and customer acquisition and retention.

IVAs can enhance the overall customer experience, and significantly change the face of front-office operations for enterprises, with increased collaboration with human agents enhancing their efficiency. is primarily offering a comprehensive, end-to-end platform (hosted as well as a service) that allows enterprises to build and deploy out-of-the-box or completely customized chatbots for their customers and workforce.’s offers different intent matching models to understand customer concerns more accurately and offer more relevant results, pre-built IVAs for specific industry and function use cases, and support for reuse of components for faster IVA development.’s customized solutions and expanding capabilities in areas such as sentiment analysis, training, language, and support, have been path-breaking.

This implies that, in the immediate future, many first-level support requests will be handled by VCAs, freeing call center and customer engagement employees from routine tasks and enabling them to handle escalated customer issues that require more time or personal interaction.

5. That’s great! Give us some examples from the real world.

There are many. But to give you a sample:

  • Today online travel booking providers deploy VCAs to provide tailored suggestions based on customers’ recent searches and booking history. Customers can talk to these bots at any hour and get help on a variety of issues, such as booking or changing a flight, booking a hotel room, making restaurant reservations, or getting suggestions of local tourist attractions based on user preference and seasonality.
  • Restaurants use them to manage reservations, respond to customer inquiries and customize customer orders, freeing up employees to spend time with the customers.

6. We have heard there are different kinds of virtual assistants. Please shed some light.

Yes, there are many virtual assistants that are rising in prominence:

  • Virtual support agents (VSAs) are assistants that provide IT support and assistance in collaboration with the IT service desk. They pull information from knowledge management sources and an ITSM tool to provide answers to common questions. They extend chatbot capabilities by also taking action on behalf of the business user to do things like reset passwords, deploy software, escalate support requests and carry out changes to restore IT services.
  • Virtual enterprise assistants (VEAs) are conversational interfaces for employees to simplify their access and engagement with the enterprise and its systems.
  • Virtual personal assistants (VPAs) are generalist assistants for users that broker first- second- or third-party services and knowledge, commonly deployed on consumer or dedicated devices.

These examples show that with time, AI-powered virtual assistants or chatbots will evolve into tools for enterprise business transformation beyond just being conversational interfaces. We will see enterprises, which have been using virtual agents for automating and addressing customer queries, extend them to take action after customer requests.

Enterprises will derive the real value when conversational AI is leveraged for business transformation by connecting conversations to business systems.

7. What role will the voice play for future conversational platforms? What do you think?

Voice will be the most essential capability for future conversational platforms, because the potential savings from automating voice communication are greater than automating text-based chat.

Today, more than 43 million Americans own a digital assistant or a smart speaker such as Amazon Alexa or Google Home (Source). There have been significant product releases from Amazon, Apple, Microsoft, Google, Samsung, Baidu and others, with vendors flooding the market.

Consumers use these digital assistants to get news and weather updates, play music, control devices, order food or other items, listen to audiobooks and podcasts, and get flight information, to name a few.

Voice conversations tend to be more nuanced, and specific capabilities need to be built into the interfaces to understand interruptions, cues and tone-of-voice signaling, which is currently beyond the scope of most implementations.

While the focus has mostly been on consumer audience, it may shift gear in 2019 with businesses moving to leverage voice-based assistants for enterprise functions. These include workplace tasks, such as scheduling, basic information searching and assisted conference calls, as well as more complex operations including handling email, processing expense reports, and providing augmented intelligence capabilities and other deep conversational features.

Suggested reading: “The role that chatbots and AI has played in marrying a marketer’s objectives with the customers’ needs has been huge”— Manish Dureja, Managing Director, JetPrivilege

8. People prefer speaking over typing their search queries now. Should we expect a boom in conversational AI-powered search?

More users for AI-powered assistants, and in new ways, implies that sooner than later demand for advanced conversational AI-powered search will crop up significantly.

Voice search will revolutionize the way consumers search online.

Consider, for instance, you are looking for interesting places to visit in a new city you have just relocated to. Instead of typing in a search query like “Bollywood movies + New York,” consumers will be able to speak their search queries using a more conversational phrase, like, “What are newly released Hindi films playing in New York?”.

AI-powered search engines will do more than just providing users with a number of cinemas; they’ll also receive more conversational answers. Search engines could follow up with questions to provide more detailed solutions by asking, say:

  • Do you have a favorite actor or film maker in mind?
  • How many tickets do you want to book?
  • What location would you prefer to watch?
  • Would you prefer a cinema closer to your work place?

According to research by (now acquired by Headspace), about 1 billion voice searches are being performed monthly in 2018. By 2020, 50% of all searches will be voice searches.

With voice search, marketers will be able to understand the context of the conversation, analyze customer interactions, user location, preferences, demographic, and transactional data; and use it all to enhance the organization’s marketing activities.

9. Are pre-trained bots and third-party data sets the future?

As data powers AI, huge amounts of high-quality training data is needed to train machine learning algorithms to get predictive and yield good analytical results.

We will see enterprises able to choose from a variety of free and paid algorithms and models that cover a variety of categories, including computer vision; natural language processing; speech recognition; text, data, voice, image and video analysis; and predictive analysis. 2019 will be the year that pre-trained machine learning models, third-party data sets and models, and open source training data will pick up.

10. How can AI integrated image recognition help enterprises?

Improved image-recognition has worked wonders in various fields. Recently, Google demonstrated an advanced imaging system for grading prostate cancer that does it more accurately than trained pathologists, and a Stanford team has achieved similar success with skin cancer.

Image recognition when clubbed with conversational interfaces expands the scope of their work manifold. With image recognition, virtual assistants can sift through information much faster than humans and are less error-prone.

Meanwhile, building facial recognition into virtual assistants helps industries such as banking, fintech and insurance implement better security mechanisms.

As AI adoption continues to increase and companies implement cognitive technologies across a wide range of uses, the excitement and expectations will only increase.

11. What changes do you expect to see in this market?

As more enterprises plan to add voice recognition and text-to-speech capabilities into both their products and customer services channels, we are also witnessing a gradual consolidation in the market with a gradual rise in the number of Conversational AI deals in 2019, says a recent 451 Research study.

Apple just reportedly bought a startup called Pullstring, that specializes in helping companies build voice apps and this adds to the growing list of purposeful acquisitions in this space.

In 2018, the number of acquisitions driven by conversational AI or chatbot technology rose by four times. For example, Qlik acquired Crunch Data to enable conversational queries in its business intelligence software; while Yodlee Inc bought Abe AI to enable banks to interface with Amazon’s Alexa and other conversational ecosystems. These are to name a few.

12. How is keeping up with increased market demand for AI-powered chatbots? What’s in your roadmap 2019? sets the tone for greater adoption of AI-powered chatbots across various enterprise functions by foreseeing the demands of the market and has brought in major enhancements in its Bots Platform. These include:

  • implementing open, extensible APIs for efficient integration with global enterprise systems and analytics engines
  • bolstering omnichannel capabilities by growing to over 30 out-of-the box pre-integrated channels
  • enhancing the unique hybrid NLP and intelligent dialog turn management capabilities
  • employing an IVR integration framework on the platform with advanced contact center AI capabilities with integration to leading IVR, speech recognition and text-to-speech platforms
  • expanding global reach with support for languages including English, French, German, Spanish, Chinese, Portuguese, Italian, Japanese, Korean, Arabic, Dutch and Bahasa
  • innovating the Universal Bot – one master assistant that routes requests to several backend chatbots across different functions and domains as needed
  • creating an advanced AI based knowledge extraction and ingestion feature set to take structured and unstructured content to produce bot knowledge
  • creating a new state-of-the-art proprietary AI framework to discover intents, sub intents, entities and discourse patterns from historical chat and call transcripts to enable rapid conversational AI bot creation and ongoing optimization

We have most recently released an all new integrated website that showcases our prowess and how we add significant value to the global enterprises leveraging the power of Conversational AI.

Leave a Reply

Your email address will not be published. Required fields are marked *

× 7 = 35