Voice AI and the Future of Customer Engagement with 3CLogic

In this milestone 50th episode of Syncing with ServiceNow, host Andy Whiteside and co-host Fred Reynolds are joined by Guillaume Seynhaeve (G) from 3CLogic to explore how Voice AI is transforming customer service and the contact center experience. They discuss 3CLogic’s Voice AI Hub, its deep integration with ServiceNow, and how enterprises can streamline operations, improve service quality, and balance automation with human support.

Why Listen:

• Discover how Voice AI can automate up to 40% of repetitive service desk calls
• Learn how AI-driven voice agents improve speed, accuracy, and customer satisfaction
• Understand how ServiceNow and 3CLogic combine to enhance agent efficiency and lower operational costs
• Hear real-world use cases of intelligent escalation, post-call automation, and sentiment detection
• Get insights into the future of multimodal, single-channel engagement strategies

Whether you're managing a service desk or shaping your organization's AI strategy, this episode offers a compelling look at how voice is making a powerful comeback—with AI at the helm.

Transcript

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Andy Whiteside: Hello, everyone, and welcome to episode 50 of syncing with Servicenow. I'm your host, Andy Whiteside, Fred. We made it to 50.

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Fred Reynolds: Yes, I was just thinking that when you said 50 I was like, there's a milestone.

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Andy Whiteside: And we should have a little little party ready. Yeah. Okay.

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Fred Reynolds: Yeah, okay.

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Andy Whiteside: That's good. It is a milestone, I bet. I bet, of Servicenow partners there are only one in the country, one in the world that's done 50 service. Now podcasts, what do you think.

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Fred Reynolds: I don't know. That may be the case. There's some there's there's individual individual ones that may do that. They love to get on there and do a lot of podcasts. But yeah, maybe as partners, you're probably right.

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Andy Whiteside: As a partner, we're probably the only one that's done 50. So let's get this one going, Fred. We have a special guest with us. You brought G. From 3 C. Logic. G. How's it going.

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Fred Reynolds: Good, good, Andy, Fred, good to see you guys.

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Andy Whiteside: 1st partner, Podcast.

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Guillaume Seynhaeve: Yes, no, I've done one, but the 1st is here. How about that?

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Andy Whiteside: Where a partner brought you on to talk about your solution as part of a podcast.

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Guillaume Seynhaeve: Yeah. But I have to admit there aren't that many service. Now podcasts, if if you know, certainly not many that come to mind, so 50 big milestone congratulations!

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Andy Whiteside: Servicenow does their podcast, but not very many partners. And so let me explain why we do it. So the goal here is to add what I call content with context around what's going on in the service now world. And we don't talk about us. The partner we talk about what service now is going on in this case. What you guys are doing with service now. So G, can you go ahead and pronounce your full name for us. Just so. It's on the record here.

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Guillaume Seynhaeve: Oh, come on, Andy, that's just that's just rude. But yeah, all right for those who really want to get into it. It's Guillaume Sana, for obvious reasons, G. For short, just the letter trying, keeping it easy for the rest of the world right.

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Andy Whiteside: What's the heritage of that name?

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Guillaume Seynhaeve: French. So family of origin, born and raised in France, came to States when I was young, so I'm pretty sure they would have chosen a different name had they known we'd end up here. But yeah, there's the. There's the shortened version.

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Andy Whiteside: Well,

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Andy Whiteside: I've got 6 years of French classes, basically the same 3 years over and over again. So 3, and then do the same 3 over again. I, my French teacher, would not be happy with how I would have said that.

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Guillaume Seynhaeve: Yeah. And I was the guy that kept being kicked out of French class because I was correcting the French teacher. So.

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Andy Whiteside: Yeah, did you take? And we won't go too too far down. Did you take French in high school and college.

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Guillaume Seynhaeve: No, I didn't go that far. I did take it back in in middle school and so forth. And I thought it was gonna be an easy a. But again, I myself a disfavor correcting the teacher. So I actually end up getting worse grade in French.

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Andy Whiteside: That's funny.

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Guillaume Seynhaeve: Then you would think so funny how those things work out.

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Andy Whiteside: Well, between you and Fred, you guys brought a blog for us to review today. Let me grab this here. The title of the blog is.

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Andy Whiteside: Get my mouse to work here. 3 C. Logic announces new voice. AI hub to streamline deployment of virtual agents. This is from April of this year. Gee! We had a brief conversation before we got started here that this is relevant, but also a lot has happened since then, Fred, from your perspective. Why did you want to cover this blog today?

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Fred Reynolds: Yeah. So 1st of all, I've been wanting to have G on this podcast for a while, I really think that 3 C logic has a special solution, special solution. We can't talk today. That actually helps with like service desk and and contact centers and joining that. And it. And it integrates so well to service. Now it's just a perfect fit for us, Andy. This is what I really hope. Our ces. Listen to this. I know one. I'll give Evan a shout out. He always text me after he gets our podcast. You know, he listens to them. But like.

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Fred Reynolds: I want them to really understand the concept here, and I know that G. Does a great job articulating that I've known G for the last couple of years. I think every conference I've been to him or his teams there. It demonstrates. Well, it really fits a good use case. So again, Andy, it kinda is, is making that seamless customer experience for your your contact centers and your

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Fred Reynolds: customer relation system.

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Andy Whiteside: Yeah, yeah, Fred, let the cat out of the bag a little bit. Our number one target audience for our own, our podcasts, our own employees that they don't have time to learn everything going on in the industry. So we try to influence them with some of the topics we cover here. Gee! What's the what's the origin for this blog? Why is it relevant.

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Guillaume Seynhaeve: Yeah, look so voice AI, we call voice AI hub, is our answer to sort of where? You know, voice is headed. Interestingly enough, you know. Look 3 C logic. Taking a step back, we are a cloud contact center solution. That would be the You put us in that C cast contact center as a service category for lack of a better one. Right?

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Guillaume Seynhaeve: So our focus has from the get go always been how to optimize customer engagements, interaction and so forth. And let's be honest. A lot of that has been digitized. Digital transformation has largely been set up as a way to sort of

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Guillaume Seynhaeve: try and perhaps kill off the contact center in the traditional sense. Right? We all have a love hate relationship with contact centers right as consumers when we call in, it's usually because we feel we've exhausted all other options. And usually what happens is you. You know, you enter that menu option and you're yelling representative in 0. Because you're trying to skip that experience that has traditionally always been associate as a poor one. And so hence. Why, you know, we call usually as a last resort.

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Guillaume Seynhaeve: That being said, I would argue that you know voice, despite the proliferation of digital channels. Chat and knowledge base and so forth, has always remained sort of that dominant fallback. Right? So it is still a very important part of the overall customer experience, and the reason voice AI hub for us is an interesting sort of of milestone. Is that what's changed in the last call it the last year? Is, of course, AI. It's affected. Everything and voice is is certainly

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Guillaume Seynhaeve: you know, within scope. And what's happened is you now have the ability to create conversational experiences with voice that match the experiences we've always hoped voice could do

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Guillaume Seynhaeve: so in the past. We all know about Ivrs right? Those very static, structural deterministic flows. Press one for this, plus, 2 for that press, 3 for that. And

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Guillaume Seynhaeve: if if you happen to have an option that wasn't presented, well, then you're out of luck right now. You move on to these conversational experiences that are probabilistic, but have the ability to consume and understand a person's intent.

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Guillaume Seynhaeve: So what are we doing here? Well, ultimately we're allowing voice to live up to the reputation it should have had all these years. But again, voice and those experiences are only as good as the systems of record and data that they have access to. That's where you can then create really meaningful personalized interactions where I know that it's Fred. I know what Fred might be calling about, or I can manage the conversation, perhaps even

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Guillaume Seynhaeve: self service it or optimize. What do. I need to then transfer it to a live agent? If a human actually has to be a participant in that experience, so it can affect call deflection.

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Guillaume Seynhaeve: It can affect self-service. And in this, you know, age of optimization, it's extremely relevant.

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Andy Whiteside: I think you would. You're talking about like the panacea of customer service.

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Andy Whiteside: I mean, certainly for someone my age

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Andy Whiteside: but even for generations to come. When a human being wants to get something done, they want to talk to someone.

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Andy Whiteside: But that's not scalable.

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Andy Whiteside: What if that someone could be AI,

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Andy Whiteside: and potentially more valuable than a real human being could be.

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Guillaume Seynhaeve: I think ultimately, you know, we'll see what the future holds. But we are at a point right now where I think the adoption of AI. It needs to be taken in balance with the you know the role that humans still have yet to play. I think ultimately, you know, there's a certain degree of acceptance if it's a simple request. Yeah, of course I want to automate it. I don't have to wait for a live individual.

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Guillaume Seynhaeve: And you know, if you can do that over voice, maybe you're in your car. You're not in front of a desktop. Maybe you don't, wanna you know. Go through a long, you know. You know, type, chat exchange whatever. If we can optimize those experiences then now, AI makes that possible right? But it's a balance of the 2. Candidly.

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Guillaume Seynhaeve: So it's a balance between Voice AI and your more traditional contact center capabilities which I would say, that's your human experience right? And there's plenty that we can tackle because we've had a few blogs with service. Now in terms of what we do when it comes to optimization of the agent experience. You know. How can we leverage AI to make sure that if something does get escalated to a live agent.

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Guillaume Seynhaeve: how do we make sure that that experience is as optimized for the caller as it is for the agent, and of course their supervisors, overseeing those operations and so forth. So it's a little bit of all the above

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Guillaume Seynhaeve: the funny thing, Andy, and you heard it here first, st and we'll see if it comes to fruition.

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Guillaume Seynhaeve: You know the way things are headed, as it pertains to voice specifically as a channel. There's already studies suggesting that, you know, if if it continues to evolve in the way it's evolving. There may be a point where it becomes the only form of of engagement. There are organizations before the end of this decade about a 3rd of the fortune, 500 that could see a future where everything is now serviced through a single channel.

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Guillaume Seynhaeve: where, maybe, voice is that dominant form of service, because it's now capable of handling everything from simple to complex. And again to your point, can automate and self service. You know the everyday, you know, mundane requests, and then be smart enough to know when the human has to be brought into the equation, which I find really really interesting, because if you look at sort of the evolution of customer experience specifically, is, it

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Guillaume Seynhaeve: pertains to contact centers. You know there was a time when everything was obsessed with being multichannel right? You had to offer every channel that anybody might choose to use to to connect with your organization. But that creates, you know silo channels, silo data. You know, different agent groups, one for chat, one for calls. So it created with it its own set of problems.

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Guillaume Seynhaeve: Then you move to this concept of omni-channel.

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Guillaume Seynhaeve: And now we might be moving to this concept of a single channel, because now the technology has reached a point where that's feasible, that history is interesting.

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Andy Whiteside: Jumping down into the blog. There's a section here of key capabilities driving enterprise value. I'll just go through them one at a time you can give your take on this on these and expand on them. If you want, build on brand compliant AI agents. What does this mean?

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Guillaume Seynhaeve: Look. The idea is that you can build your own agents right in in the simplest of terms. We want to provide the keys to to the everyday user. Without having to have, you know, a coding background or any technical proficiency required to do so. Right? So can you create intelligent voice experiences, avatars, if you will, that will represent your organization and perform very specific tasks and do so in a way that is, you know, mirrors. How we use chat gpt. Today, for example.

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Andy Whiteside: Fred. Anything to add to that one.

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Andy Whiteside: Greg, you're on mute.

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Fred Reynolds: Sorry about that, hey? GI was gonna ask you, is that one of those avatars or one of those that you guys created for knowledge when you did that demo for me.

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Guillaume Seynhaeve: Yeah, I mean, you can. Basically, the idea is it's it's again, you've you've shifted from being from creating deterministic workflows right to prompt engineering where you basically create a persona. Okay, here's who you are. Here's who you represent. Here are the things I need you to be able to perform. Whether it's to gather information right or to provide answers back. Maybe you're pulling off of a knowledge base, whatever the case may be.

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Guillaume Seynhaeve: and being able to assign it, a voice, a personality that you can adjust, and then put it to market. 100%.

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Fred Reynolds: Yeah, we'll keep going through these. I think we'll hit on some of that.

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Andy Whiteside: Next one. Here G is automate, real world task.

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Guillaume Seynhaeve: Yeah. So the goal here is that you know the

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Guillaume Seynhaeve: you, you're not gonna create a voice AI agent that is good at everything.

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Guillaume Seynhaeve: The the broader the set of tasks you give it. And this is probably stuff that you guys know. Even the context of Servicenow and their agentic AI agents right is that if you give it too much to do, you introduce the opportunity for hallucinations, right and so forth. Right? Everything's probabilistic. So if you give it too much to do. The probability of it always being great is is significantly reduced. So the idea here is, can you create as many.

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Guillaume Seynhaeve: you know agents voice AI agents as is required for very specific on task. You know. You know functions, and then can you align it or attach it to you know, the information that it requires to perform that task. So think service now, right? If I want to put in for Pto, do I have access to that person's, you know, Pto schedule you know how much time they have available.

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Guillaume Seynhaeve: If I want to. You know process and open up a case, you know, being able to do so in service. Now, if I want to know what Fred's background is, or answer his questions. You know, based on an information that's in a knowledge base. So that's why, you know, we perform real world tasks. We facilitate that, but in conjunction with a system of record like that of service. Now to bring it all together.

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Andy Whiteside: Fred comments.

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Fred Reynolds: No, I'm good on that one.

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Andy Whiteside: Next one g. Enrich AI with enterprise, knowledge.

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Guillaume Seynhaeve: At the end of the day. AI is only as smart as the information you feed it. Right? So this is just a simple way of saying that you know it will know as much as you give it access to. So to my other comment, whether it's an existing knowledge base when you want to create and feed to it. You know all those things are what are going to allow it to have you know the context, and also the brand alignment to to what it is you're trying, you know, to build.

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Andy Whiteside: Right.

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Fred Reynolds: Yeah, nothing new. I just. I know that, you know just the play with service. Now, service now is invested so much into all of its AI capabilities. Right? I think the combination to be able to be in that platform. Gee, I gotta imagine that allows you guys to go way beyond what you're even doing to go down to the, to the the work that service now could do for automation through AI as well.

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Guillaume Seynhaeve: A 100%. So imagine bringing together the power of voice. AI, as sort of that experience layer

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Guillaume Seynhaeve: as sort of you know, that entry point into being able to then collect or be the intake to launch service. Now's agentic, AI and AI agent. Orchestration capabilities. Right?

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Guillaume Seynhaeve: So the the beautiful thing about voice. So why we we all tend to default to it is you can share so much more information in such a shorter time. Period, right? The transfer of information between 2 individuals. It's the most efficient form of of information transfer relative to digital channels and any others. Why, you know, we are conversational beings at heart. Right?

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Guillaume Seynhaeve: So how can you take that information and be able to, regardless of how it's being given.

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Guillaume Seynhaeve: being able to parse it out and use that to then construct or feed. You know, service. Now's platform to drive action right, which is ultimately when you do. When you have a conversation. There is an ultimately, there's an intent specifically in customer experience, whether it's it, whether it's employee services or customer support. So it allows us to basically right, create those conversational experiences really as an intake point

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Guillaume Seynhaeve: and perhaps even have the option to provide the answer without having to escalate to a live individual, but, if need be, collect all the information that the agentic AI, or live individual, would need to execute a decision.

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Fred Reynolds: I think

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Fred Reynolds: the biggest change, too, and that, we'll see, is like we were saying like going back to voice. And the reason is because when AI is involved, if you you know you do chat Gbt, and you give it one thing, it'd be complicated. It takes a couple of minutes. It comes back with your answer. I know. When she was giving me a demo of this he was speaking a question to it, looking into a case looking into something that could be complex. It's so quick to come back. So your patience.

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Fred Reynolds: your patients don't get stressed out by like you said when you call the news, and you're trying to talk to a representative hitting 0. It's because they take you through this path. You're repeating yourself. You're repeating yourself. You're explaining something, and you know somebody's in the background looking into a

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Fred Reynolds: a catalog to find the answer for you. You know, when you, when you have AI and when you have this, it's just instant to you, right, no matter how complex it is.

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Fred Reynolds: Think that's what's gonna have the uptick in it.

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Guillaume Seynhaeve: Yeah, I mean, look, there's there's a couple of ways that this affects value for a couple of different individuals for the customer. It's it's the. It's the ability to prop to potentially get meaningful help

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Guillaume Seynhaeve: without having to wait for it. Right?

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Guillaume Seynhaeve: For the organization that might deploy these. It's the ability to potentially remove from the equation all of those repetitive calls that come in, hey? I want an update on my case, or I want to report an outage, you know, one that might already be known, and you know, etc. So that you can allow for only the remaining calls that require human intervention to actually reach an agent

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Guillaume Seynhaeve: for an agent. It's the. It's the ability to actually focus on those complex inquiries and not get distracted from those everyday repetitive tasks which I'm sure you know, become aggravating after a while. Candidly, Fred, right? I mean, I didn't. I'm sure people didn't go to college or whatnot to to just do password resets for their entire life. Right? That's usually not a career choice.

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Guillaume Seynhaeve: And then, you know, then, that trickles down to operational expenses. Right? What does it take to be able to field all these types of requests from simple to complex and scale in such a way that perhaps your operational costs go down right, because contact centers have always jokingly be called cost centers.

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Guillaume Seynhaeve: But what you want to balance that with to my earlier point, is making sure that you don't, you know, pull the lever so you know hard that all of a sudden you've made yourself completely unapproachable, and you can't reach a human agent at all.

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Guillaume Seynhaeve: And so, you know, this can drive a lot of value, but only if executed in a way that actually doesn't provide that sense that you're trying to avoid any type of real engagement with your audience and your customer base? Right? So how do you balance the 2 right, which is, how do you remove all those things that really should have never gone to a person in the 1st place? But there is no real.

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Guillaume Seynhaeve: you know, intelligent way, you know, up until now to really parse those out.

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Guillaume Seynhaeve: and then at the same time optimize those experiences. When you get to a live agent, because the other thing that 3 C. Logic contributes. It's not in this blog, of course, but is everything we do when a call does have to get to someone right. Everything from real time. Transcription to feeding. Now, service now is now assist to provide a summary of the conversation. So the agent knows what the call is gonna be about as as it reaches them

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Guillaume Seynhaeve: to being able to do basic things like, you know, pulling that information intelligently. So I know exactly who I'm talking to, what the issues about. And then automating all those post call activities. Right? Summary notes, resolution notes. All the way through to being able to provide the C-suite visibility into the quality of those customer engagements. Right? So what is the sentiment of the conversations, or our customers happy with the service? What are they typically calling about?

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Guillaume Seynhaeve: And all of that becomes a feedback loop in of itself right? But voice.

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Fred Reynolds: That was a lot is a lot you just said. I just want to recap one thing just for the listeners here that, too, because you're doing this with service now, like service now has that you know it. It has that place for to capture all this information so like you said you were just referring to that like case summary and things like that. All the historical type stuff, too. That's what makes it so good. Because while you're in that call while you're serving that customer. All this stuff can be captured in the background, pulling from those knowledge articles, capturing that documented that summarizing that, and it's all done very quickly

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Fred Reynolds: for them, making their making the agents life a lot easier, too. But I just want to bring that back to the fact that this is in a platform that's already got a ton of data. And it's their customers data. And it's making a record of that. So they can go back and see it as well. That's important.

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Guillaume Seynhaeve: SIM simplifying the tech stack. Right? Is key

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Guillaume Seynhaeve: the the issue that we have. I don't think there's a shortage of platforms and technology. Right, I would argue that maybe part of the problem is that now every technology you know presents itself as a platform. They'll manage your contacts. They'll manage your workflows, and so on, so forth. And you've got this duplication of capabilities across systems from different marketplaces like there are Crm tools that arguably do things that contact centers traditionally have done.

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Guillaume Seynhaeve: You have contact center platforms that are arguably starting to do what Crm or or service management platforms have traditionally done.

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Guillaume Seynhaeve: And what happens is as a consumer, as an as an enterprise organization. Procuring these systems, I end up having, I end up sourcing different capabilities from different places. And the problem in doing that is now I'm civil sharing between different systems when I need something from them as well, and all of that ultimately complicates what you're ultimately trying to give, which is a pro, a good customer experience. But if that customer experience is fragmented

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Guillaume Seynhaeve: architecturally in the background from the get, go.

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Guillaume Seynhaeve: then the results will be 2.

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Guillaume Seynhaeve: So the way in which 3 c. Logic has architected itself is to complement the system of record in this case. Service now

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Guillaume Seynhaeve: really to solve for what it doesn't have and support and complement everything it already does right.

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Fred Reynolds: It's perfect.

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Andy Whiteside: So lots of thoughts as you guys were talking about that, it's starting to make sense to me. So one of the things about what G. Said it only is gonna know what it knows about. Well, the service now, platform is growing and growing and growing and growing every day. So it's gonna know more and more and more every day.

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Andy Whiteside: and and probably well outpaced the human being's ability to catch up. That's part of the reason why this is important right.

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Guillaume Seynhaeve: Correct look service now as position itself as the platform of platforms. Right? So why why integrate to 10 when there's 1 that's already started to do the consolidation, or has done the consolidation of data from the back to the middle. And now, obviously, they're moving to the front office with with Crm and so forth.

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Guillaume Seynhaeve: So then the goal is really just complementing that with a voice, and we do SMS as well. But we'll just loosely call it voice and contact center layer that allows them to make sure that the contact center is now an extension of the service. Now workflow and methodology, and not just another silo that you have to contend with. Right

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Guillaume Seynhaeve: customers don't really care how you've organized your operations in the background. Right? What they do care about is was this a good experience or not? It's a relatively simple question. What they don't always appreciate is the complexity that goes behind delivering a good customer experience, but we can appreciate that. There's a lot of moving pieces.

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Guillaume Seynhaeve: and until you can consolidate those moving pieces, it's going to be really hard to meet customers and the the expectations that they have at the level that they have it.

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Guillaume Seynhaeve: that I'll leave you with this interesting fact.

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Guillaume Seynhaeve: customer experience as measured over the last half decade, despite the prolition of AI digital transformation and so forth, has actually gotten measurably worse. People are actually unhappier with the service that they're getting today than they did 5, 10 years ago.

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Guillaume Seynhaeve: So think about that.

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Andy Whiteside: Yeah.

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Fred Reynolds: Hey? And I want to bring this to your attention to. If you remember knowledge, you know you spend a good bit of time looking at Crm of service. Now, customer success, you know. Remember talking about all that. Now you kind of see how this is. Really this is a good timing for this service now is really pushing harder. Crm, right? And it has to be with a combination. I think we like something like C, 3

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Fred Reynolds: 3 C. Logic. Because you want that customer experience. You have to have that and service. Now, such a delivery engine behind the scenes. Now you can really make that a lot more seamless, because they're always have been fragmented from my old positions where you had sales on one side, service delivery on the other, and you need that view that's together. And this is what can really do that.

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Guillaume Seynhaeve: Yep.

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Andy Whiteside: so this is interesting. We have a hard time getting. This is great. We're getting through these bullets these topics.

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Andy Whiteside: these key capabilities. But I do. I want to tell you how just being part of this conversation has changed my view of this. You know, we start off thinking about. Okay. Now, I got to do a chat bot thing which I don't want to do. Now I gotta pick up the phone and call somebody. My, you know, Nirvana world that I would have seen as a as a you know, fantasy back when I was a 13 year old. Kid, was the idea that I could sit in front of my computer, see a person that in this case isn't real

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Andy Whiteside: person. But it's some type of AI agent. Talk to that person. And at the same time they're able to use graphics and images and stuff

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Andy Whiteside: to have a conversation around what I'm doing where I'm like. Look, I'm trying to replace this headlight on my car. It's a 2,001 Bmw. And I'm having a challenge, and it's explaining to me. Oh, you mean, and it's literally showing me images. And I'm like no, no, not that. Not that brake light the other brake light. And and I'm able to actually not only have a conversation with them and actually feed them data, but they're actually giving me feedback through a what looks like a human being

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Andy Whiteside: that's sharing like real visual images of what it thinks. I'm talking about like pictures worth a thousand world words, and I'm able to go back. No, no, not that one. The other one.

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Guillaume Seynhaeve: So what you're talking about is multimodal, right? Is in that sort of goes back to what I was talking about is having a single channel that actually can operate simultaneous differently, simultaneously operate different channels

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Guillaume Seynhaeve: over the, you know, over a single engagement, right? So I might be on my phone, Andy to your point, but at the same time, you know, I might receive a text, because it's easier to fill out a form depending on the conversation I'm having digitally than is to just verbally provide you all the answers and so forth. So not that dissimilar from what you're alluding to, which is

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Guillaume Seynhaeve: really, instead of having to pick a specific channel for the specific task or request, I have just be able to call in and have a conversation, and if other channels

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Guillaume Seynhaeve: are necessary, have them simultaneously operate and support that engagement, whether it's video and things of that nature. And that's where it's all headed. Candidly, which is why I think organizations are starting to rethink is multi-channel or omni-channel really the solution? Or is it really now that AI makes it possible.

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Guillaume Seynhaeve: having the ability to just.

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Guillaume Seynhaeve: You know, you'd be able to talk and have that conversation and have everything else, you know occur around that, you know conversational exchange. And I think that's where it's headed. Candidly. So I would agree. I.

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Andy Whiteside: I'll give you a shout out to Evan again. It's probably listening. When it 1st started talking about technology. He had a idea that he was. Gonna have this for less heavy equipment. He's gonna have this app and you you were a heavy equipment person, and you would pick up your phone, and you would start chatting with some human being, and use not only the voice conversation and the the graphical image of looking at this person, but you'd also be able to show them what you're working on. And they could show you an example. I mean, that's exactly what this is, but could be but an AI

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Andy Whiteside: chat bot an AI, an AI person versus you know what he originally envisioned as a you know, a certified mechanic, and whatever technology it was.

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Guillaume Seynhaeve: Look. I I agree with you. I think that's where it's all going. At the end of the day we're conversational beings, you know, we're talking to our phone. We're talking to our cars. It's it's it is our default form of communication. I mean, Heck, we're having a conversation right now. So I think the technology has finally made it, as you know, realistic for a voice to actually live up to its potential in in a business context, right? When it comes to servicing. You know, an audience.

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Andy Whiteside: Alright next one on the list is deploy with confidence. Gee! What's what's the point in this one.

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Guillaume Seynhaeve: Well, look at the end of day. You want to test what you're putting out before you put it out. So it comes with the ability to do what we call playground. So the ability for you to actually interact with the voice AI agent that you've created again. You know the the risk factor with with any Lm based agent is that is now probabilistic. It's statistics at the end of day.

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Guillaume Seynhaeve: So you can. You can test it 3 different, you know, 3 times asked it 3, you know, 3 times the same question, and it's going to give you a variation of the answer. But you know answers will always be slightly different one from the other.

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Guillaume Seynhaeve: So you need a playground to make sure that you can hone in and tweak whatever are the nuances as well as you know, the ability to put on what we call guard rails, what are the things that it has to do? And more importantly, what are the things that it should never do?

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Guillaume Seynhaeve: So you can sort of limit. You know what it's field of of you is. If it's, you know, if you want to ask it, the weather and that's not within its purview, or you don't want customers to start treating it as the you know, their everyday concierge, you can put those in place, and then make sure that you can test it accordingly before it goes. Live.

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Andy Whiteside: So you could literally tell this agent this virtual agent, not to talk about religion and politics, and trust that it would never do it.

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Guillaume Seynhaeve: That is, that is the goal. Yes.

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Andy Whiteside: Yeah, you can never do that with a person.

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Guillaume Seynhaeve: I I would I I would. I mean, imagine how slippery or slope that could become right. But again, that's also why we we're not assuming that this is gonna be one agent to meet all your requirements. You're gonna build ideally very same same concept as service. Now with Agentic AI very targeted specific function, oriented agents. So you'll have a whole bunch of them. They may all sound the same right, and you may not know that you're being transferred

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Guillaume Seynhaeve: from one task specific agent to another. But you'll be able and have the option to test each one before they go to market for yourself.

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Fred Reynolds: And it keeps

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Fred Reynolds: level of door rails on there keeps it safer, keeps it easier, and makes customers want to be able to deploy that right? You're not deploying something just wide open.

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Andy Whiteside: Yeah, I could tell a an agent from that that if they're on a phone call with someone from New York not to bring up the Boston Red Sox winning a game last night

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Andy Whiteside: literally had to deal with that one time where a human being

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Andy Whiteside: like brought that up like don't, don't do that. It's not appropriate. All right. Deploy with confidence. Hit that one, maintain context with memory and delegation. What is this about.

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Guillaume Seynhaeve: So again. So what we can do is the

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Guillaume Seynhaeve: We? As the conversation progresses right? It actually keeps sort of like chat gpt, you know, a running tally on things that have been discussed so that context that can come back and revert back to it. That has a lot to do with the difference between a structural flow right that has that really is taking you through a sequential series of questions. But doesn't you know know what is that you answered in the last one.

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Guillaume Seynhaeve: or can't take it into account as part of the broader conversation. Right? It's just, you know, going from one step to the next, and the prior step has no impact on the next one.

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Guillaume Seynhaeve: That's very different in this environment, where everything that you're contributing to that conversation. Perhaps previous conversations can lend themselves to maintaining that conversational you know experience and being able to sort of

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Guillaume Seynhaeve: present a more personalized, you know. Relationship, hey, Fred, the last time we spoke, you know, depending on how much context you wanted to to maintain right.

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Fred Reynolds: So one thing I didn't see in here, which I think it should be memory delegation. And then customer sentiment. It's not in here, but I know you demonstrated that to me at the conference. Gee! Where it can detect frustration in the voice.

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Fred Reynolds: Yeah, it will, in response, awesome.

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Guillaume Seynhaeve: So there's a couple of different get. Yes, it will understand if you're getting frustrated. And be smart enough to to know. Hey? You know what? Maybe I should just hand itself to to Fred. Who's a real person? Because maybe Fred will be in a better position to to manage

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Guillaume Seynhaeve: the situation. It's getting a little bit emotional, or maybe I'm just frustrating whatever the failure point might be. So yes, it can detect sentiment it can assume. Hey? You know I'm calling in because I lost my bag was lost at the airport. Okay, that person is very likely not going to be in a joyful mood. So you don't want to be telling jokes at that time? Right? So there's a certain degree of of read. The room that comes inherent with the solution.

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Guillaume Seynhaeve: And then also can at the end of every engagement summarize it and provide a sentiment ranking right? Was it a positive negative, you know, neutral, you know, net engagement, and those can, can, you know, feed a dashboard which a supervisor can monitor, and that can help you sort of

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Guillaume Seynhaeve: maintain a quality assurance level within your AI agents to know if there are some that are underperforming versus others? Or are there some that need to be tweaked to make sure that they, you know, are more in keeping with the types of outcomes you want.

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Andy Whiteside: Yeah, maybe you have. Somebody calls in with a thick Southern accent and like, I gotta get this over to somebody else.

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Guillaume Seynhaeve: You know, you'd be. So we've we've been putting it to the test. So that what's cool is, I mean, you could basically say, look, I'm gonna put all my prompting in English.

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Guillaume Seynhaeve: But one of the things that I might say is, Hey, you might be receiving calls in Spanish, French, German, right? So be prepared to to to respond in the in in the preferred language. Right? And the reason I raise that is, you know, English. There's English, there's English, English, Uk, English, there's Southern English, there's Canadian English. There's a lot of different English out there. And I'll be honest. It's actually

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Guillaume Seynhaeve: impressively capable of handling just about any of them right now.

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Guillaume Seynhaeve: So we've been putting that to the test, and and more often than not it is it is completely capable.

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Andy Whiteside: I agree. I use, you know, some.

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Andy Whiteside: You say I had a decent amount these days, and I just talk to it the way I've always tried to talk to my phone and

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Andy Whiteside: it

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Andy Whiteside: it fixes what I ask it, and then answers what I was asking, even though it didn't come out right.

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Fred Reynolds: Yeah.

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Fred Reynolds: Understands me better than my phone. I will test your country English, if you want me to. G.

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Guillaume Seynhaeve: Yeah.

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Fred Reynolds: And understand me. You've got it taken care of for the South.

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Guillaume Seynhaeve: I don't think it has a problem with the South, right? So it's all good.

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Andy Whiteside: A unique use case because he talks country, but fast.

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Fred Reynolds: Fast, country.

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Andy Whiteside: Fast, country.

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Fred Reynolds: He's like listening to the country music at 1.5 normal speed.

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Andy Whiteside: All right. Moving on in the blog. Next section says, real world use cases. Speed efficiency, consistency are critical in today's landscape.

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Andy Whiteside: AI Hub enables enterprises to do more with less achieving faster results. It's got 3 breakouts here, 3 bullets. 1, st one says self-service enablement. Gee.

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Guillaume Seynhaeve: Yeah, I mean, I think we we cover this right. I mean, one of the biggest appeals, at least from an enterprise. Perspective is the opportunity to to be able to service more customers without having ever necessarily having every call, go to a live agent, right that has cost implications that has customer experience implications? And so, you know, the idea is, you know, for for those repetitive requests can we finally offload those right?

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Guillaume Seynhaeve: In such a way where you know it might give you the opportunity to to put your agents to better use so they can focus on things that drive real value for the organization as opposed to just, you know, having to answer every call, regardless of what that type of request might be.

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Andy Whiteside: Read any additional piece, any additional pieces there.

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Fred Reynolds: Not really. I'm just trying to look at your blog there. Why, that's different. What I'm looking at on the

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Fred Reynolds: it's like you got a lot more information in there

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Fred Reynolds: because she wouldn't jump blogs. Nope, I'm good.

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Andy Whiteside: Okay. G, next to intelligent escalation.

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Guillaume Seynhaeve: I think this is the part where this is knowing how to balance technology with with the human aspect, right?

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Guillaume Seynhaeve: So knowing when there should be a handoff to a live agent, and making sure that that's a clean handoff. Right? So they they receive the entire transcription of the conversation that occurred virtually between the virtual agent and the customer.

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Guillaume Seynhaeve: I can quickly get a summary automation of the case or incident creation within service now, so you know there's no manual effort that has to be performed on, on the, on, the, from the agent's perspective.

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Guillaume Seynhaeve: And really ideally impress the customer with with the overall outcome. Customers never call because they're in a good mood or want to give you a high 5 for doing a good job right? So you get ranked on. How well you're handling a bad situation and knowing when to hand it off, I think, is part of of that skill set right. So this has the ability to try and help you, and if it can't, for one reason or another, or you refuse to receive help knowing when to sort of toss in the towel and hand it off to someone who can actually affect that that experience.

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Andy Whiteside: This. This might the the last one. Here's 1 for you, so I get all the time I get. Would you like to take the survey at the end, or I get to the answers, would you like to take a survey? I never take the survey if we're doing things this way in the future? Are we gonna be able just to generate a survey based on how the call went without having to have somebody tell you how it went.

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Guillaume Seynhaeve: I would argue that that's already possible. Today, I mean our speech analytics, capabilities which are, you know, not related to this already, have the ability to to rank a conversation to look at tonality, keywords, phrases, script, adherence, and so forth. Right? So short answer is, yes, it can also do and this is primarily, predominantly for live agents. It can look at, you know, from a quality assurance standpoint can help with feedback coaching.

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Guillaume Seynhaeve: So you. You now can use AI to gain all those insights. So yes, you might, you know, potentially remove the survey aspect. I know that surveys traditionally have a very, very low response rate. And you could argue. The only time people respond is when they've reached that point of aggravation where they've got really nothing nice to say.

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Guillaume Seynhaeve: I have my own thoughts about where you know the role surveys play because I'm with you, Andy. I never filled them out. You know, I just you know what I do is if I'm really mad, I just switch vendors. That's typically how I tend to to respond. So this can help give you some some heads up, perhaps, regardless of whether or not a survey was, was, you know, completed or not.

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Andy Whiteside: Next section here. Intelligent escalation. GI think we've got.

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Guillaume Seynhaeve: That was the one we just covered, right. So, being able to go to a live agent, knowing when.

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Andy Whiteside: Yeah. Sorry about that post call automation.

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Guillaume Seynhaeve: Yeah, so this is a mix of 3 C logic and service now together, right is, how can you remove those manual steps that agents are expected to perform rarely do, or if they do, it's never, you know, in a standardized format from one to the next right agent notes. If you leave it to an agent to write them will never be, you know, most likely never meet the quality standards right your yours. Yours might be San scripts. Fred might might spend too much time typing up notes and wasting time to get to the next caller and everything in between.

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Guillaume Seynhaeve: So this allows you to basically transcribe the entire conversation in the in the case of service. Now we take the whole transcript. We put it into service now.

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Guillaume Seynhaeve: and that allows service now to then use, now assist to do the summarization to take that and also kick off the resolution notes. And so what you inherit as an organization operationally is really reliable insights into every conversation that took place without necessarily you know, bogging the agents down with those manual tasks which you know they hate to perform right. We all do.

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Fred Reynolds: And I can imagine that when you start the call, when this caller calls back in. If you go right back into that, the previous cases. Read some of those summarizations and make sure they understand the sentiment of that customer before even start. You know, as they're working it. That's another way to use that. Because that's that's why I just really want our listeners to understand the power of like 3 C. Logic with service now is for the motions like this. You provide that better customer service because of the information you have at your hand, and it's all pertaining to better, better service for the customer.

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Guillaume Seynhaeve: I think context is key right? And so we treat service. Now as that primary system of record. That's where the context resides.

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Guillaume Seynhaeve: And then that's where the action or actions that have to happen or haven't yet happened need to occur. Right? So how do we then facilitate that engagement layer. So that context is actually being leveraged when it matters which is at the point of engagement, right.

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Fred Reynolds: Perfect.

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Andy Whiteside: Alright. Next section talks about the bottom line impact for enterprises. Studies suggest that while calls complexity has increased, more than 40% of calls remain largely transactional or repetitive. 3 bullets here. 1st 1st one says, improving the customer or employee experience.

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Guillaume Seynhaeve: Yeah, I mean, so again, consider 40% of of your daily call volume could potentially be addressed.

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Guillaume Seynhaeve: and that might vary by organization, of course, and industry, but near half of your call volume. Could you know all of a sudden get handled, you know, from

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Guillaume Seynhaeve: from using this type of of capability together with service. Now, I think that's huge, right? So inevitably, whether you're serving a customer base in a front office type, capacity, customer, support or employees, whether it's it or Hr, you know, you're gonna get improved. Average handle time. Your customer satisfaction, you know, ratings are going to go up. Your speed of resolution is going to improve

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Guillaume Seynhaeve: the traditional Contact Center metrics that everyone is obsessed with are going to get better.

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Andy Whiteside: Next one here says reduce opera. Well, let's I can't help but not address the part up here around the 40%. I mean you. You said it when you talked about this 1st bullet, but 40%, just a massive number. That's if you told any company out there they could improve their efficiency. 10%, they would jump all over 40%. It's just a phenomenal number.

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Guillaume Seynhaeve: I agree. I mean, 10% to your point is, is is a no brainer. If you can get the 40 again, I think it depends on the organization, the industry, I mean, what are we talking about? Right? So I'm not suggesting this is the silver bullet, the customer experience you still have to deal with the remaining 60. And that's kind of the point everyone's very focused on. Let's get rid of the 40%. But what you're trying to do is get rid of the 40%. So you can do a better job with the remaining 60 right? Because those are the ones that are waiting on hold that have no option but to wait on hold.

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Guillaume Seynhaeve: and those are your high value. That customer experiences right and customers this day and age. I mean, they'll gladly toss in the towel. The switching costs right are so low. That. And we all know it costs, you know, X amount times more to replace a customer that it does to keep one right. So if you can all of a sudden take the same number of agents and be able to provide that white glove treatment for the remaining 60, because you took 40% of their workload off their plate.

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Guillaume Seynhaeve: I mean, all of a sudden you've got. You're affecting really 2 sides of the equation. Not just one.

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Andy Whiteside: Yeah.

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Fred Reynolds: Next bullet here says reduce operational costs.

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Guillaume Seynhaeve: So at some point you may be able to do more or less, depending on the size of your team. That's true. I mean, let's be honest. Contact centers have historically just thrown people at the problem. If I want to lower handle times, I have to hire X amount of more people

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Guillaume Seynhaeve: right? But that's an expensive solution. And are you really dealing with the root cause? So if you can all of a sudden do more with less than your operating costs might get better. And so that's just a function of your traditional contact center model.

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Fred Reynolds: I think you said an important part right to get that. People just can't assume that you want to get the 40%. You could cut 40% of your base. It's not. It's like most people have long lead times. You're waiting. The more complex things take a lot of time. So now, you're actually improving that because the ones that actually do need to talk to someone are getting the people who can actually help them solve the problems, and they're not rushed, which means they're happier to deal with, and the customers are happier because you're helping them. So I think, to your point. Gee, I mean, you don't get down to reducing operational cost until you handle like the the underwater that the people are today.

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Guillaume Seynhaeve: Or or not. I mean, it's not listed here, but you could keep your operational costs the same. But maybe your revenue goes up right, because you kind of hit on it right? If all of a sudden you create a reputation where you know man, when you, when you need customer support. These guys are here for you, regardless of what it is that you sell or do internally, externally, then you might create and improve your brand image, and yet not have to scale up your operations all of a sudden. You're gonna get

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Guillaume Seynhaeve: more for your operational costs. So is it reduce operational expenses for some organizations. That may be the the motive, or it could be. Hey, I'm an Msp. Manage services, provider. I want to bring on more customers. But can I do so without necessarily increasing my bottom line or my you know my expense line. Maybe.

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Fred Reynolds: So most are.

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Andy Whiteside: Last bullet here for this section. Faster deployment of AI agents.

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Guillaume Seynhaeve: Look a AI, there's a lot of people are wondering like, How do I do this? Right? I mean, the goal is to make sure that this is not some kind of big tech overhead. You know a professional services, you know, perpetual maintenance type of of model that you now inherit right to my earlier point, the entire thing is designed so that someone like myself and I'm predominantly sales. I'm not a I don't have a

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Guillaume Seynhaeve: not a software developer. It's not my background can actually, you know, create and build these virtual agents without having to rely on external

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Guillaume Seynhaeve: or technical resources. Right? So the idea is, you know, you can on board this technology and have it create an impact fairly quickly compared to the adoption of technologies in the past.

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Andy Whiteside: Fred any comments.

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Fred Reynolds: No, I mean, I think we're starting to see that the the adoption is happening.

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Fred Reynolds: People are starting to use AI, and as these AI agents go out there. The ability to be able to create these agents do it without having to have a computer science degree. As I think. G. You alluded to right giving a way for them to create these is going to make it happen faster and faster. You can do it very specific to use cases which makes it great. You're not trying to create an agent that can handle everything. Maybe it's a specific use case. And I think that's where the adoption will really pick up. So I think it's great. I think it's also great that you had a place in the platform to to test.

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Fred Reynolds: So you have these people who are not programmers, but can pull this together. Go test it. That's going to help them adopt it, because then we have confidence in it. So a lot of that just goes into hitting a lot of these bullets. You can move faster because they have the confidence, and they feel comfortable with it.

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Andy Whiteside: So gee! We're at the end of the the blog here. It's got a section that's kind of the wrap up. How would you close us out here?

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Guillaume Seynhaeve: Well, we're very. We've already seen that there's an enormous amount of demand for for this capability. Right? You know, traditionally, the the emphasis has always been how to optimize for the human agent, the agent, experience, and so forth. And that should remain. I'm not saying that there's not opportunity there. We affect that as well

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Guillaume Seynhaeve: within our contact center offering. But a lot of organizations are very eager to adopt AI tools that can drive meaningful value quick, right! There's still an ongoing debate as to, you know. Can you show me the Roi right for AI and I think this is one of those low hanging fruit, you know, capabilities

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Guillaume Seynhaeve: that solves for what has been a longstanding point of frustration. Right? You know. Again, we have a love hate relationship with calling into organizations. Organizations have gone as far as removing phone numbers from their websites altogether.

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Guillaume Seynhaeve: And I think that's actually had a negative effect in terms of customer response as opposed to a positive one, thinking, Hey, I'll just push them to a digital Channel knowledge base, and they'll solve for that by themselves. When customers want a mix of options right? They want digital channels, but they still want to know there's that fallback option. But just because there is one.

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Guillaume Seynhaeve: doesn't mean that it's it's it's optimized for the organization that's providing that that voice channel as as a potential conduit.

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Guillaume Seynhaeve: So Voice AI can act as an intermediary that really bridges both right. It solves the customers requirements I want to be able to call in, but allows custom, you know, organizations to use it as as a way to triage. What is something that can be self service in a way that delivers experiences we've always hoped for, and it's only gonna get better by the way, and then optimize the use of my live agents only. And if and when they need to be brought to the equation. It's it's really the best of everything you can hope for.

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Andy Whiteside: Or anything else to add.

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Fred Reynolds: Well, all I want to add is the fact that, you know we're kind of to the end here, and I just want to any

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Fred Reynolds: any customers that have service. Now.

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Fred Reynolds: you know, it needs to take a look at what 3 C. Logic has to offer to to provide that from the service desk and for helping them with the customer relationships. I feel I feel bad for some of the customers out there that have, like the hodgepodge little pieces, or or just things off the shelf to handle the ticketing and do this and do that, and segregated cause you really can't get this experience, I think, for those that have service. Now, today, we should really get them in front of G, and let that team at 3 C. Logic. Show them what it's capable of doing.

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Andy Whiteside: If if you have service now, and you take inbound calls

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Andy Whiteside: and tell me if I get this wrong.

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Andy Whiteside: It's a valuable part of your business, and you shouldn't be hodgepodging it together.

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Fred Reynolds: Great. Everybody has voice. Everybody has a service desk. I mean, this is all we're talking about, right. If you already have service now today using it for the minute piece. And people just don't take advantage of the power. What service now has this could be your starting point to really start utilizing more of that platform. And what 3 C. Logic pull together for you.

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Andy Whiteside: Right.

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Guillaume Seynhaeve: And solve your front office. Correct.

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Fred Reynolds: Correct.

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Andy Whiteside: Guys, I appreciate it. G. Thanks for the time, Fred, as always, thanks for the time.

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Fred Reynolds: Awesome. Yes.

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Guillaume Seynhaeve: My pleasure.

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Andy Whiteside: And we'll get you back on. Do it again. Gee, if you have another topic like this, maybe a month from now, 3 months from. Now, let's let's get you back on.

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Guillaume Seynhaeve: Yeah, happy. To absolutely.

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Fred Reynolds: Get a webinar soon. Gee!

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Guillaume Seynhaeve: Yeah, for sure.

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Andy Whiteside: If if and I'm saying, if tongue in cheek joking, if this continues to advance voice and AI, we'll have you back on.

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Guillaume Seynhaeve: Fair enough.

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Andy Whiteside: Not if. But when? All right, thanks, guys.

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Guillaume Seynhaeve: Cheers.