Future of Enterprise AI with Umesh Sachdev | Uniphore

Christina: Live from Nasdaq’s Market Site. I’m your host Christina Ayanion, and joining me today is CEO and co founder of Uniphore, Umesh Sachdev. Umesh, thank you so much for joining us. Christina, it’s great to be with you.

Umesh: Thank you for having me

Christina: Uniphore has really been making waves in the industry, and you’ve become a trusted partner in providing businesses with seamless client experiences. How so talk a little bit about Uniphore and what you do?  

Umesh: Christina, we’ve been around fifteen years. We’re a company whose vision from the beginning has been to use AI to be the defining AI and data platform for the entire enterprise anywhere that they have a conversation, whether it’s on a phone call, like the call center, or video meetings, like over Zoom, etcetera, which people within the company do AI now has the power to be a co pilot to every employee in the enterprise and deliver efficiency and other business benefits.

We’ve been at the forefront of this. Today, we serve with thousand five hundred enterprises around the world. We’re a global company. We do this in over twenty countries and support over a hundred global languages.

Christina: So we’ve really seen the spectrum of how the the latest state of the art AI, including generative AI, is able to work within large enterprise environments and really deliver value. AI is really embedded in your genes. You’ve been an early mover from the start in the world of AI, which is really a significant advantage now with the AI boom. How does Uniphore specifically use generative AI?

Umesh: So we’ve been a native AI company from the very beginning. All our products have been built on a common platform, which have tremendous amount of power of AI. Several building blocks we think of them as lego blocks of technology. One of them is generative AI.

We’ve been using large language models, which is the underlying technology to these generative AI models. Since twenty nineteen in our products. We use them in areas like our AI can detect sentiment of when people are talking to each other depending on the words and their tones. So we use large language models and generated where I could detect somebody’s sentiment.

When a customer’s calling a telecom company’s contact center, the customer may not be a native English speaker. So our AI models detect. First up, what language are they speaking? And so language detection is an area where we use generative, models.

But more importantly, what we’ve learned of, you know, having deployed these for the last three or four years is that One of the biggest downsides of today’s, generative AI models is they require a lot of compute and lot of infrastructure and you don’t need to spin up every time you have a certain application of AI in the organization. You don’t need to spin up the biggest model all the time. So we’ve found the best tailor made approaches of what works best for which type of use cases. And like I said, we today have over seven hundred and twenty five thousand end users who speak over a hundred languages who use and get benefit of these generated AI models every day from Uniphore products.

Christina: That’s incredible. I think it’s really interesting. You mentioned the emotional intelligence piece. It really helps drive businesses and drive smarter business decisions in that sense.

Umesh: Absolutely. Let me give you an example. Think about, you know, in the new world where we all went hybrid or remote work and you’re trying to now be a salesperson and sell to new customers and they assemble a team over a Zoom caller or Webex caller teams They assemble a team of eight to ten people.

Your presentation is on the screen as a salesperson. How do you read the room? How do you know what you’re saying is making sense to the audience? How are they reacting?

Do they have a question? Should I clarify something? When everybody was in person, doing this by watching each other’s facial emotions, etcetera, was very easy. Now in the virtual or a hybrid world, it’s really hard.

This is where AI becomes a true co pilot with emotion AI being one of the fields that we are at the forefront of, where it’s not just watching every participant who’s a small window is watching facial reactions, facial emotions. It’s paying attention to what’s being said by the salesperson.

And giving instant cues to the presenter that you know what? You’re probably losing your audience. You probably want to slow down and clarify this one point. Those are real life examples that we are seeing work within the enterprise.

Christina: Absolutely. And the time spent I saw on your website that the time spent for post call work has reduced fifty percent due to Uniphore?

Umesh: Well, one of the biggest applications we see for employees, seventy five percent of the time spent by salespeople inside of a company is a non sales activity, which means they’re filling up a form, they’re entering data into a into a software, Same thing with call center workers. There are fifteen million call center workers around the world.

And when you and I are done talking to them, whether the call was good or bad, they are still working on our case. So they spent another few minutes after the call is hung up in summarizing the call, writing up notes into the system, except those are perfect examples where today AI can automate tasks and put the time back into the employees’ hands and they can do more effective work. And they can focus on the selling piece. Absolutely.

Christina: You take the heavy lifting off. Aside from generative AI, how else is AI incorporated in Uniphore?

Umesh: Well, what we realized, in working with these enterprises, the fuel to this rocketship called AI is data. And while generator AI has shown the way that you can train these models on large amounts of publicly available data and show up to deliver value in a b to b situation, in the enterprise situation, you also need to take into account the company’s own data.

But the biggest hurdle we found is that these companies don’t have data in all one place, whether it’s a telecom company or a bank, their data is in silos, their data is unstructured. So knowledge AI is an equally important field of AI that focuses on taking siloed data into one place, converting unstructured data to data, structured data, and then making it readily available for a generative AI model to take shape. We just spoke of emotion AI in addition to generative AI, which is focusing on sentiment, tonal changes, facial emotions. So think about knowledge AI, generative AI, emotion, and working in tandem on a phone call, on a video meeting, and truly being a co pilot to every employee in the enterprise.

Christina: Wow. That’s incredible. You’re staying ahead of the curve in that sense and hitting all all the points?

Umesh: Well, our goal is to get our customers the thousand five hundred enterprise and end clients that we work with every day. To get them prepared for this huge revolution, that’s generated AI. We at Uniphore believe that this is a technology transition that is likely to be bigger than the cloud, the mobile, and even the internet. And we wanna make sure all our customers, current and prospect, are prepared for for what’s about to come and change the way we work, live and play. You’re definitely doing that essentially acting as an extension of their team. Absolutely.

Christina: What sets Uniphore apart from your competitors?

Umesh: Well, first, the fact that we’ve been doing this as a native AI company for the last fifteen years. We have deployed our products in thirteen different industry types across these thousand five hundred customers. And that has given us a a data repository, a data lake of learnings that we’ve had that the AI model has had through all of these experiences.

And while the algorithms, the research work that our data scientists and PhDs have been doing, has given us an edge, what’s given us a bigger edge is all this data lake that has been accumulated over time through these customers. And we truly believe that the differentiation in the future the way to build better value for customers in the future is by having more access to more relevant and exclusive datasets. And so that is one of the value propositions. So today when we show up to a new telecom customer or a new banking customer, we are able to say that, listen, We don’t need six months to take your data and model on it and learn from it.

We are coming with rich history and learning from customers like yourselves. Of course, we need some of your data, but in a matter of thirty to sixty days, you can start to gain benefit from generative AI which is truly a differentiator that some of the other companies today are not able to offer. You’re enabling and empowering your customers to really own those conversations. Absolutely.

Christina: That’s incredible. As CEO of an AI driven company, what are you most excited about with the new AI boom and where can we see this industry going in five to ten years?

Umesh: Well, first, the I correlate this in the early two thousands with the internet revolution.  And then in the two thousand ten, mobile happened in cloud happened. Those were big technology shifts that changed the course of economy. What we are going through now with the forefront of generative AI, etcetera, is a technology transition that is likely to be much bigger than the waves we’ve seen in the past, including the internet. So it’s gonna impact B2C application like search engines, and we’re beginning to see that.

It’s gonna massively impact B2B environments. As an example, I’m a CEO of a software company at Uniphore, and we believe that in two to three years, vast majority of the new code, that today, our engineers, right, will not be written by engineers. Our engineers will speak to the code in English, and it’ll be AI writing the code. So think about the efficiency that a software company like Uniphore can have. 
If you’re a bank, if you’re a telecom company, if you’re a health care company, many different functions today that are manual and repetitive are gonna get automated and more intelligent with AI. And what this will lead to is higher value new types of jobs while the current ones will be taken on by automation. It’s opening up doors to new opportunities.

Christina: So it’s truly, truly an exciting time, and the opportunity in front of us is very profound. We’re very excited to work excited to continue following your journey as you continue to grow. Thank you so much for joining us.