Latest / The Tech Matchmaker / AI for Contact Centers: Scala.ai's New Intelligence Layer for CX | Greg Smith
Transcript
- Gina: Good morning, everybody. Today we are talking with Greg Smith, the Global Head of Growth and Go-To-Market at Scala.ai. Greg, welcome to the Tech Matchmaker. Greg: Well, it's an honor to be here. Thank you for having me. Gina: Yeah, now Scala is turning heads in the contact center AI space right now out of the gate and we're super excited to have you with us. Why don't we start with you, tell us a little bit about yourself and then we'll get into the product. Greg: Yeah, well, I spent about 25 years in sales and marketing leadership roles, mostly on the healthcare side with healthcare technology companies. I live in Seattle. I'm married with two teenage boys that keep me up late at night when they don't come home at times or Gina: You Greg: on time. you know, I love both my work and my personal life very much. Gina: Excellent. Let's get into Scala. Give us the elevator pitch. Greg: Yeah, big picture. Gina, know, as somebody who spent many years in the contact center, you know this probably better than anyone. Every contact center leader is drowning in data, but they're starving for intelligence and big picture. That is what Scala was built to solve. We are an AI native platform that helps contact leaders get greater efficiency. in their operations, so really focused on eliminating waste and driving revenue opportunities for them. And ultimately, we believe that leaders want to be able to see what's going on in the operation, understand what's happening predictably, proactively, and then be able to act on it without having to go wrangle teams of engineers to create change. And so that's what we're focused on building. At the core of the Scala experience is what we call Scala Pulse. Think of that as the heartbeat of the platform. And Scala Pulse is one unified intelligence layer that connects all of those CX systems, conversations, knowledge bases, and then helps people turn that into understanding about how their business is performing. Again, be able to identify proactively when hotspots are appearing. and then use the automations that we make available through the AI platform to take action confidently and quickly. Gina: And I think, you know, the first time that we met, you guys said something that kind of stuck with me you're like, and I don't know if it's your tagline or what, but you were like, we turn complexity into clarity. Greg: Yes. Gina: how I interpreted that was, okay, so we're pulling all these systems and channels and human agents and AI agents and creating that one intelligence layer. So for somebody that's never seen the platform, and I know you kind of talked about, help the frontline leaders, what does that translate to for somebody that's never seen the platform? Like is it, okay, now it's all my reporting rolled up or talk a little bit about how that benefits them by having everything Greg: Yeah. Gina: in one. Greg: And it's really a flexible platform. It's comprehensive by nature, but depending on the client that we're working with, we can start small with a few data sources and use cases, or we can go very comprehensive and ingest the entire CX tech stack into the Scala platform. And then what we want to do is quickly within 30 days, go tackle high value use cases that create immediate impact and business results. We intentionally have designed the platform to be easy. If you think of many of the operators or contact center leaders, not to discount their tech knowledge, but they're not technologists by heart, they're business Gina: Yeah. Greg: people and making it easy again for them to quickly get perspective on what's happening across every single customer conversation. Where does the AI platform identify opportunities and patterns? that are predictive in nature and proactive in nature and are very difficult, frankly, for people to see. Serving up insights where there's opportunities to create greater efficiencies, serving up insights where there's opportunities to deploy AI agents that make it easy to solve problems that in the past would be buried in either complicated workflows or even IT teams that often were slow to respond to the needs of the leaders in operations. Gina: You know, when you were saying about the operational leaders not having necessarily the technical background, it made me think back to the time when, which for some people it's their nightmare now, to your point, if they want a new report or if they want to get data on something, it's, IT, here's a ticket, I need this new report or whatever the point may be, right? And it's wonderful that we're empowering them to be able to run their business, right? Like their side of the business kind of thing. I know a lot of the conventional wisdom in the contact center space is like more dashboards and more point solutions. And we have a tool for QA and another for agent assist. And I was just chatting with somebody in the industry, actually, we both know Nate Brown. And we were saying, we're kind of now going into AI the way we did software where everybody's buying different AI solutions that do different things. And so your whole premise pushes back, well, it kind of brings it all together, but it pushes back on that. Like you can bring it all in, correct? Greg: You got it, absolutely. And we've intentionally designed the platform to not be another point solution or another tool that you have to make sense of across all the other disparate tools that you might be working on. And really to bring that clarity and that simplicity from a user experience. We've spoken in the past about AI being the new UI, and we mean it. When you use ChatGPT or Claude Gina: Cool. Greg: It's very, very simple and it's very, very intuitive. You shouldn't have to go do a bunch of data wrangling to make sense of what's happening in the operation. You really shouldn't have to put in a ticket for your analysts or even your IT team to go build a report that comes two weeks later that doesn't empower operations leaders to get in front of the business and to really manage from leading not lagging indicators. And that's important for what we're building here. Just as an aside, I watched a demo of a really compelling company. They're a competitor of ours, so I'll be careful not to disparage them. But they were going through a product demo of their conversational AI. And I'll tell you two minutes in, five minutes in, Gina, you would have to be a technologist to launch and deploy an AI agent, whether that's an internal agent focused on you know, eliminating manual and low value workflows or a conversational agent that's going to engage your customers. That shouldn't be that hard. And so we built it to be very much low code. You don't have to be a prompt engineer, high efficacy and easy to deploy when Pulse identifies opportunity where an AI agent, for example, and that's one narrow example, might create more value for the business and what they're trying to do. Gina: Walk us through a use case where, you know, customers come to you and kind of like talk about how, what, what an engagement with you looks like, you know, so what's the consulting side of it? What's the onboarding and then how soon can customers start to realize the ROI? Greg: Yeah, I say three use cases in 30 days. So being able to get use cases that are deployed quickly and creating value immediately for the business is very important. Often what we see in conversations and discovery with the clients that we're working with, and this is universal across some of the biggest organizations that we're working with for even some smaller businesses that have contact centers that are a little bit smaller in scale. Often their eyes are bigger than their stomach. so we again have built a comprehensive platform that can grow, evolve and scale with the businesses that we're supporting, but really narrowing that conversation and working with them to look for opportunities that are high volume, have significant ROI opportunity attached to them, have problem points that are showing up for either the leaders or the customers and zeroing in on those. Start with three and then over time, we've got forward deployed engineers that are both technical and operations experts that are really consultants to work with the people that are buying our solution to get the value that they want. And again, when you think back to many of the solutions that you've probably used in the past, whether it's with a contact center or even outside, often the technology and the tools themselves have so much breadth. that it intimidates people. People don't use them. People don't engage with them. We really want to make it easy for, again, the business leaders that are tasked with running the business. Use cases, Gina, really vary. Depends on the needs of the companies that we're working with. We're often starting with our performance intelligence configuration. This is our QA and QM tool that evaluates 100 % of conversations. And that one resonates not at the expense of the intelligence platform and the insights that we're serving up or even the conversational AI agents that we can deploy, but it resonates because it's such a concrete problem that so many contact centers have today. They're doing Gina: Mm-hmm. Greg: manual QA, they're not taking advantage of all of that gold that exists in those customer conversations. And we're really helping them transform how they think about their product, their service and those customer journeys. Gina: So you've mentioned QMQA, we know you can create agents, we know you've got the overall dashboard. Is there any other parts to your solution that, you know, and it is all AI native, right? I think that's another big one. You guys didn't start and then transfer to AI that you are created and born in AI. is there any other, Greg: Correct, AI native tech track. Gina: yeah, is there any other product or any other functionalities or features that you'd like to highlight? Greg: Well, again, it comes back to the intelligence. If I can serve up insights about how your business is performing that historically have been very difficult for people to surface up, to be able to use the agentic reasoning engine and our proprietary LLM models to go and really look and uncover patterns and trends and serve up opportunities that typically would have been really, really buried or would have existed anecdotally in a smart leader's brain or a hypothesis, we can go and make those really tangible really quickly. so giving people intelligence to understand, to see, and then to be able to take those insights and determine how they wanna deploy fixes that make the businesses more efficient, more effective, and ideally turning contact centers into revenue centers. Gina: I love it. What's next for Scala? Greg: What's not next? You know, you've met our CEO and co-founder, Ardie Sameti, and Gina: Yes. Greg: he's fantastic. We have all joined this company to follow his vision that he's outlined for the growth of this organization. But, know, Ardie is really setting a perspective for Scala that's focused on technology that solves real business problems. and making sure that we are taking our operations, our domain expertise and regulated industries and helping teams, again, create immediate value and solve those business problems. Three use cases in 30 days. How can we go in and very quickly not turn this into a science project, not put the technology on the backs of the users, but to make it invisible and seamless so they can get the results that really will transform. what they know best, which is their businesses. Gina: And three in 30 days is not something we see a lot of in the industry. So it's impressive that you guys are able to accomplish that. Greg: Yes, and I think coaching the customers that we're working with, and don't get me wrong, this is much more expansive than three and 30 days. Gina: Yes. Greg: But sometimes the hardest place is to just help them organize, prioritize, and categorize where are those opportunities? What are the high volume opportunities that have high friction points and have immediate opportunity to create value for the customers? And it varies from each organization we're working with to the next. Gina: Is there anything you'd like the audience to know that I haven't asked you? Greg: That's a good question. You know, the thing I think about often, and I think we've had conversation on this in the past, maybe there's this buy versus build mentality. We talked to a lot of organizations whose primary value proposition of their company is not being an AI technology innovator or creator. And I appreciate it and I respect it. I've worked in the past with really fantastic Chief Technology Officers, Chief Strategy Officers, and Chief Innovation Officers. But to build something that's secure, hallucination free, that can scale and grow and adapt, unless you're doing that 24 hours a day, that is very hard to replicate. And so that's one area that I like to constructively challenge the audiences that we're engaging with. I appreciate there might be some interest in building this yourself. But what's your product roadmap? What's your innovation strategy for six months, nine months, 12 months? How will you evolve and scale? And that's something that Scala brings to the table that I think our customers appreciate and recognize. Gina: And one thing that I haven't asked you yet is who is your ideal customer? So for our listeners that are out there, know, it, well, I do have five different systems that I kind of would love to be able to see all rolled up in one. Talk a little bit about who gets the best, or who is your best use case? Like, yes, I see. Greg: our best customer. Yeah. Yeah. When we think of the ICP, it's a great question. I mean, we're in the early stages of growing this company. We are a hyper Gina: Mm-hmm. Greg: growth company. And so we are agnostic to the industries that we're focused on. However, our domain expertise is really in regulated industries. So healthcare is one that we have decades of experience in. Both on the benefit administration challenges that healthcare companies are facing, or whether it's the clinical challenges that delivery systems or digital point solutions are struggling with. We understand that extremely well. We also understand in banking and in travel, just the rigor around security and the regulated environments, requirements and high bar for being secure, being compliant, protecting data. And so we've done extremely well in those verticals because we talk the talk and walk the walk and can really quickly help those teams think through what an AI strategy looks like. Having said all that, I would say our lion's share of customers that we're bringing on board and focusing are in those segments. We are seeing customers that fall outside of that. And I think it's important as we grow this business to... work with customers that are engaging, collaborative, and want to be innovative partners with us. Gina: Absolutely. To wrap things up, Greg, I've always been a fan of James Lipton, so to end the podcast, we do a little bit of rapid fire. What noise or sound do you love? Greg: Fantastic question. I love rock and roll. I'm, you know, I spent my formative years in Seattle, was part of the grunge scene and have been very close to the spirit of the grunge and punk rock movement. So give me some noise that gets me up in the morning and I'll take it. Gina: I love it. What noise or sound do you hate? Greg: I don't hate, I try not to hate anything. no hating. What would I prefer not to hear? I read on Nextdoor, somebody in my neighborhood complaining in Seattle about the birds getting up, they're up at four in the morning and how do they turn the birds off? And I was like, you know what, like, isn't that great? I want to hear the birds. So wake me up. I'm good. Yeah. Gina: my hand hurts. And what profession other than your own would you like to attempt? Greg: I love sailing outside of work. I've gotten into sailing with my two teenage boys and would love to go deeper there. when, you know, Scala is, you know, the next publicly traded company and we're doing extremely well, maybe I'll sail off into the sunset. Gina: Love that. If somebody wants to learn more about Scala or get a demo of Scala, who should they reach out to, Greg? Greg: I always think you're a great resource. You have a pulse on what is innovative and valuable in creating results for the clients that you're working with. So happy to have them come through you. They can also visit our website, Scala, which is Scala.ai I encourage people to request a demo. We love showing off the platform, the technology and what we've built. And that always brings the experience to life. So those are the two ways I would probably recommend. Gina: Wonderful. Greg, I so appreciate you making the time to join us today and teach us all a little bit more about Scala and pique our interest. So thank you so much for taking the time. Greg: Thank you, appreciate the questions.