ITechnology Interview with Umesh Sachdev, Co-founder and CEO at Uniphore

“AI & Analytics has evolved tremendously over the past few years and adoption is accelerating across businesses.”

Hi, Umesh. Please tell us about your journey into the AI and Dataops industry?

My cofounder, Ravi Saraogi, and I founded Uniphore in 2008. Our mission from the beginning was to enable better and more effective conversations for people. I am from India, where half the population is functionally illiterate, making most text-based applications essentially useless and then even further complicated when hundreds of languages and dialects are put in the mix.  With that in mind, we developed voice-based technology that allowed people to use their voice as a primary interface, regardless of the language spoken or if the user could type anything on a screen or keyboard. From there, we were an early leader in combining our voice expertise with Natural Language Technology with AI, automation and machine learning capabilities to build out an extensive platform that supports all types of conversations. Today, the Uniphore platform supports all conversations, no matter where they take place or whether it’s with an intelligent virtual assistant, chatbot or traditional phone call, and can address customer service challenges from the beginning of the interaction through any follow up and follow through, including post-engagement summaries and reports.

How did you cope with the disruptions brought by the pandemic? How did you leverage technology to stay on top of your product development roadmap during the peak of the pandemic months?

Interestingly enough, the global pandemic brought us a new opportunity. Stay-at-home orders and remote work changed the way the world communicates. Businesses scrambled as their entire workforces had to move onto a digital  infrastrucure to continue serving their remote customers. The rapid digital transformation happening across the enterprise highlighted the need for automated and intelligent solutions to help drive new business models. With more than 15 million agents employed globally and an increased focus on agent support and digital customer service, the market opportunity was stronger than before the pandemic. Quickly, our product and engineering teams recognized there were several products that we could build to better serve our customer base who had to transition to work remotely. These new solutions focused on improving and optimizing contact center interactions from start to finish,  strengthening the connection between frontend customer experience and backend fulfillment through Robotic Process Automation (RPA).

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What is the most contemporary definition of Conversational Service Automation? How do you promote this idea across your customer base?

A simplified definition of Conversational Service Automation is this:  More conversations are happening between people (contact centers, sales calls, employee meetings, public hearings, tech support, product support, etc.), between people and machines (chat bots) and between machines (independent of regular human engagement).  When you group all these applications and use cases together, we refer to these as conversational services. All have a purpose and desired outcome. The challenge is that we humans cannot keep up with the sheer volume of conversations, the various channels they are happening on and the complexity of many of the requests for help and support.  That’s where automation comes in. Intelligent automation and AI can and does help us listen better, learn more and manage these conversations much faster, with more accuracy than if we tried doing it alone. Because of this efficiency, people are freed from the tasks that they don’t enjoy doing like taking notes, writing wrap up reports, searching endless systems for the latest information, and so on.  We are now able to show empathy, deliver solutions in near real time, and show people the way forward. Uniphore’s comprehensive conversational automation platform has automation built into all of the processes empowering customer service agents, making conversations more real, impactful, and efficient. Our customers love this, they know that a human touch improves the overall experience which is what our technology is helping to make even better. 

What kind of IT infrastructure does a company require to better leverage your CSA platform? How do you help your customers achieve this?

Our solutions can be deployed on cloud (AWS, GCP etc.) or on premise on customer’s IT infrastructure. We have been innovating to create the most cost-effective IT investments and lowering TCO for our customers. Our AI models leverage GPU architecture to provide a low footprint and high throughput performance. We also integrate with all popular on premise and cloud contact center infrastructure that our customers choose to use.  

Tell us more about your objective of acquiring Jacada. How do you plan to extend the benefits of this merger to your customers?

Jacada has more than 30 years of customer service automation experience and is the low code/no code pioneer in the industry. Combined with Uniphore’s leading conversational AI solution, we can empower businesses to easily automate key interactions across self-service and agent-assisted customer engagements. Our customers will benefit from this comprehensive platform to realize state-of-the-art digital transformation, resulting in significant ROI.

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AI and Analytics

Could you tell us more about Embedded Analytics and how AI analytics technology investments play a role in adoption of these applications across industries?

AI & Analytics has evolved tremendously over the past few years and adoption is accelerating across businesses. Analytics was traditionally limited to structured data. Today, however, AI is increasingly able to analyze unstructured data, using mature AI tools and innovations in natural language processing (NLP), speech recognition and computer vision for image and video analytics. Advances in NLP, Speech and Computer Vision are leading the efforts in bringing AI and Analytics to the “front-office” or in situations involving human to human or human to machine communication. Uniphore is leveraging all three areas in its Conversational Service Automation (CSA) Platform and building best of breed solutions to drive improved human engagement and performance in different scenarios from Customer Service to Sales.

What are the “Hits” and “Misses” with AI in DataOps? How do you use AI and ML in Uniphore?

AI is best appreciated when it is put in “action” vs just focused on providing insights or predictions. Actionable AI is in the fabric of all things we do at Uniphore. At its core, our platform is all about using AI to improve agent performance, improving customer experience, automate customer service/front office automation and derive deep insights from these conversations. We use AI and ML NLP, and Computer Vision to deliver a platform capable of things like real-time Speech Recognition, Emotion Recognition, Language Id, Speaker ID, Intent, context-aware, Sentiment, Information extraction, Call Summarization/Notes, Next Best Action, Facial Emotion Recognition, Gaze/Attention Analysis and Engagement Analysis and several other features.  It’s this flexible combination that makes our platform unique and it’s what fuels our growth.

Tell us more about hiring trends in the AI ML and Voice market influenced by AI and data science.

Market for AI/ML and Voice talent has been hot in the past few years and timely talent acquisition has been a challenge. This has been significant challenge both in the US and India where we have most of our R&D teams. On the positive side, we are leading in many areas of AI research and product direction makes us very attractive to talent that is looking to work on cutting edge AI and automation.  We are finding that many engineers who want to come onboard and build something great, which I believe is unique to a startup company (rather than the other side of the coin at large company). Ultimately, our company culture helps us bring on some of the best talent including PhDs and people with deep industry experience. DataOps and MLOps are other ancillary areas which are trending as well when it comes to AI Operations. We also work very closely and partner with academic and AI research organizations across the globe to keep in touch with ongoing research and have access to the best  AI talent from universities.

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 Industry Trends / Insights

Which industries have you been keenly following to understand current technology trends?

We are seeing tremendous success in Telecommunications, financial services, insurance, BPO and healthcare.

Where is the AI-based customer service industry heading? Which technologies are you keenly following in this industry?

With capabilities in our products across AI, Automation, Machine Learning, RPA, Video AI, I believe the future is about who can simplify the integration of the latest technology innovations  to provide the fastest and easiest way to derive the maximum value from these efforts. This leads to the low code/no code revolution that is happening in other industries and now is coming to the contact center market. With the strength of Jacada’s portfolio of offerings, especially in the low code/no code area, combined with our comprehensive platform, you will see innovation expand rapidly and businesses who get on board will thrive.

Your favorite podcast / webinar that you have listened to in recent times:

Chambers Talks” produced by JC2 Ventures.  Specifically, I enjoyed the back and forth John had with Eric Yuan

Tag a person in the industry whose answers you would like to see here:-  

Vinod Muthukrishnan from Cisco

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Thank you, Umesh! That was fun and we hope to see you back on itechnologyseries.com soon.