[00:00:00] [SPEAKER_00] I've had the experience of stumbling onto an A.I. voice agent. You can hardly tell at this point that it's not a human.
[00:00:08] [SPEAKER_01] Typically, a human agent can only take one call at a time. But with an A.I. voice agent on Aircall, they can take 100 concurrent ones at a time.
[00:00:15] [SPEAKER_00] I'm still getting phone trees or chatbots that have canned answers. And it's just frustrating. It shouldn't be like that. How do you see the market?
[00:00:25] [SPEAKER_01] Is an A.I. voice agent going to be as performant as your smartest agent who's been around, who kind of has all the knowledge of the things that are never documented? Probably not yet. But I do think that it is better than the average rep in the call center.
[00:00:44] [SPEAKER_00] Can you start by introducing yourself to listeners? Give a little bit of your background so far as it's relevant and how you got to Aircall and then what Aircall is. And we'll start talking about it more deeply.
[00:00:59] [SPEAKER_01] So I, Tom, I work at Aircall as the chief product officer. When I first joined Aircall about two years ago, it was a little over two years ago, almost getting two and a half. We were in a completely different world. I mean, this was about a year after I think ChatGPT had launched. There was some early promise. But I don't think anybody sitting in my shoes or most people's shoes would have guessed how quickly it might have moved.
[00:01:25] [SPEAKER_01] Of course, there were folks who are maybe more prescient or more future looking, better future predictors than some of us. But I think it probably caught most of us by surprise in terms of how well and how fast it's moved, especially in certain general AI spaces like coding and others.
[00:01:43] [SPEAKER_01] And so since my time joining Aircall to now, we've really turned from what you would describe as a software SaaS business to much more of an AI business. Because almost all customers around the world no longer look at, you know, a phone system or customer communication software as just the software itself. But more around, you know, what can you help me actually resolve?
[00:02:12] [SPEAKER_01] Whether it's tickets for conversations or, you know, can you actually autonomously handle conversations? And while deployment and, you know, uptick is not across the entire world uniformly at 100%, we're still in the single digit early innings. And you can bet that all businesses are thinking about it and trying to find, you know, a future partner who have the capabilities that they can really lean on and trust moving forward.
[00:02:38] [SPEAKER_01] And trust is an interesting thing because it runs across the gamut of not just the AI services, but also your base reliability in, you know, whether it's your chat or telephony services, your ability to navigate the different telco regulations around the world. All of those things matter.
[00:02:59] [SPEAKER_01] And I think over the course of, you know, the next few years, we are going to see some more definitive winners, especially for certain cohorts of, you know, let's say ideal target customer profiles. You might have a couple of winners in, you know, enterprise and a few down market, some verticalize. But anyhow, so that's a little bit about maybe not just about me, but what's changed in the market and what Aircall is about.
[00:03:29] [SPEAKER_01] I'll add one more thing, a bit about me. Prior to my time at Aircall, I worked at various different Silicon Valley tech growth startups or growth stage companies, always in product here. Most of my career has been in B2B. So pretty familiar, I think, with how kind of businesses think about things. We specialize at Aircall a little bit more on the smaller business side.
[00:03:56] [SPEAKER_01] So there are consumer elements in how we do business. And that's fun, right? It's it's it's you're maybe sometimes not as bogged down by the slow moving natures of some enterprise. But I'll stop there. You know, I'm sure there's a lot more things to talk about. I'll stop. Yeah. Yeah.
[00:04:15] [SPEAKER_00] Yeah. Yeah. Yeah. Well, we were speaking before we started recording. You were saying that one of the advantages you guys have is that you started overseas and are now in the U.S. market. So you have a multinational footprint, which is helpful for for multinationals.
[00:04:37] [SPEAKER_00] Does that does that include multilingual services?
[00:04:46] [SPEAKER_01] Absolutely. Absolutely. I think there is a couple of points to it. I think with AI nowadays, even, you know, you can easily get access to multilingual services, you know, especially if you look at transcriptions or even voice agents. You can look at any of the providers and you can look at any of the providers and they'll be able to offer 100 plus languages and you're good to go.
[00:05:07] [SPEAKER_01] But where Eric call really excels is that we have local go to market sales teams and support teams who are of that nationality. So a good example of this is like we have teams on the ground in outside the United States. We have it in London, Paris, Madrid, Sydney, Berlin, Mexico City.
[00:05:32] [SPEAKER_01] And I think we're one of the few who serves like are, you know, a little bit more down market who are boots on the ground. And the difference between and I think everyone who's international can can probably attest to this difference between just being able to speak the language. But also kind of knowing the local culture and way of doing business. There is a huge difference between those two things. Right.
[00:05:56] [SPEAKER_01] It's abundantly accessible to just be able to have some services that can transcribe into those languages. I think it's more rare to have, you know, a customer success team or a sales team and support agents who really know the local business culture. And that, I think, stands out to a lot of our customer base in the world of AI when there's so much just AI spam.
[00:06:23] [SPEAKER_01] You know, at the end of the day, I think what becomes a little bit more scarce in the world and humans are always gravitating towards scarcity to a large extent is just a team that can really help them. All right. And so we pride ourselves on that, especially for those companies that are more multinational, being able to really talk their talk, knowing how businesses really work.
[00:06:47] [SPEAKER_01] And then, of course, our products are also then built with this in mind across the board. Like we really care about the different cultural aspects from all the different local markets. And we think we're very thoughtful about how we do this. So that's maybe what makes us a little bit more unique. And that does come from perhaps a more European heritage where on day one, you're forced to somewhat tackle all the markets.
[00:07:13] [SPEAKER_01] Whereas in the United States, you kind of get the, you know, one large market, great market, but you're not forced to do that on day one. You know, Aircall was forced to do that on day one. And since then, we've been scaling in that manner. And United States just happens to be one really large market. And, you know, some of our best tech talent is obviously out of the United States. But we have a large presence here as well from San Francisco, New York, Seattle, et cetera.
[00:07:39] [SPEAKER_00] Yeah. And it's funny, my family and we talk about it just now that they're living in those states, how that people don't appreciate that cultural sensitivity. And it's one son in particular is, is in a star Japanese startup.
[00:07:58] [SPEAKER_00] And he, he talks about their colleagues that, you know, he's the favored guy because he's, he's comfortable and he can read the room and he understands those nuances. Yeah. We spent a lot of time in Asia. Yeah. It's, it's an underappreciated skill or, or aptitude, I should say.
[00:08:23] [SPEAKER_00] Not, not that people that have never left the States, some may have it, but not many have it. Yeah. And you guys are really, you guys are really focused on voice as opposed to text. I mean, when General DeVeo first came out, there was this a huge shift chatbots that would then hand off to, to human agents at a certain point.
[00:08:52] [SPEAKER_00] I am continue to be frustrated. And I've mentioned this many times on this podcast, the, the pace of adoption. Uh, I'm still getting phone trees and, uh, or, or chatbots that are, have canned answers. And, you know, it's, it's just frustrating. It shouldn't be like that. How do you see the market?
[00:09:20] [SPEAKER_00] Uh, and as you said, you're, you're at the very beginning of this massive market. Uh, how do you see that adoption, uh, continuing or hopefully accelerating?
[00:09:33] [SPEAKER_01] Yeah. I think, I think it's very much accelerating. So that's the good news. What I would say is that right now, um, you get this tension between perhaps what folks actually think customers might want versus what feels safer for, you know, their jobs, let's say. Um, and like all adoption, adoption curves of kind of a frontier technology, I think you're going to be faced with that.
[00:10:01] [SPEAKER_01] But what makes this space, what makes me feel more bullish about this space in particular is that you, a lot of companies, um, now understand that you don't have to do everything in one step. That is to say, look, let's say you have a phone tree, an IVR that all your operations are like based off of that. And you don't want to muck with that, right? Like there's, you got, you got people who are, who are, uh, employed who are, you know, who, who have specific shifts.
[00:10:30] [SPEAKER_01] And this is, especially in large contact centers, uh, and some of the largest contact centers, you can get up to like 10,000 plus, uh, even a hundred thousand reps. Um, not all at the same time, but with all the different shifts that are happening across the year, right? There, there, there's numbers that are really large that you wouldn't even fathom. Um, and to even get there, you must've had a really well oiled machine. So companies don't really want to mess with these things. It's a headache. It's a, it's a, you know, potential there's downsides to the service.
[00:10:59] [SPEAKER_01] Uh, but what I think companies are discovering is that they can first start to get a taste of how well generally AI is behaving or, uh, how well it can be deployed in, um, things like after hour use cases, overflow use cases. And these are all little bit less scary than trying to deploy, you know, on from eight to five.
[00:11:22] [SPEAKER_01] Um, and then what I see is the moment customers have taken that first step for a use case in which is a little bit more upside only, meaning like they weren't even picking up these calls anyways. So even if they just answered a few questions and maybe the customer left through a structured few questions on a voice agent, um, what, what they're really looking for, it's more upside than there's almost very minimal downside.
[00:11:49] [SPEAKER_01] Um, once when they get experience of that, they start seeing so much more opportunity to then basically get higher and higher coverage. Um, and so part of what, you know, we try to do at air call is try to educate. I think you have to really educate your customers. Um, and if, if there's any customers listening, it's like, you, you want to find a partner who can help you along on that journey.
[00:12:13] [SPEAKER_01] Cause it, uh, is this, the, the it's companies are, you know, customer service or even sales. It's so personal for most of these companies. It's kind of the lifeblood, um, that it's not the same as just procuring any random piece of software. Um, and so what you often typically see now in the enterprise market is most of these voice agent or, or AI agent companies are going to be coming with a full, like a forward deploy engineer. They're going to build the solutions with you on the side.
[00:12:44] [SPEAKER_01] And I do think in the early stages, that is what we all have to go through, um, to, to kind of get through the right levels of automation for that. Ultimately is reasonably comparable to what a human agent, uh, could possibly achieve. Uh, and I think most companies that start small, they all see the value quickly. They get a taste of it. And then they start, um, they're really expanding their usage. And that's certainly what we've seen across our customer base.
[00:13:11] [SPEAKER_01] Um, and the other thing I would add is like really making sure that, you know, we're a partner to our customers, not just like a random piece of software that, that is being procured. And I, I think this one is a little bit more well-known now in the, in the industry, uh, broadly. Um, but S and B is probably not as fast on some of the AI adoption in some of these cases.
[00:13:32] [SPEAKER_01] But I, I do anticipate with the things that we're doing that there, there would be massive acceleration in the next couple of years because the, the, the, what you might say as ROI is quite frankly, just too high to ignore.
[00:13:46] [SPEAKER_00] Uh, the other thing is, uh, companies can scale customer conversations without scaling headcount. I mean, so your, your funnel can, uh, can widen, uh, without having to take on more, more people.
[00:14:04] [SPEAKER_00] So, uh, can you talk about, uh, embedding AI directly into daily workflows and, and knowing when to involve humans and, uh, and your, uh, customers, are they contact centers or do you partner with contact centers? Because the AI cannot handle everything.
[00:14:27] [SPEAKER_01] Excuse me. Most of our customers are not contact centers. They might use, they might have an offshore contact center or onshore contact center that, that they, you know, then procure to who might procure air call. But most of our customers just due to the size, um, it's more of a direct relationship with air call as opposed to, Hey, I'm going to a contact center. And then, you know, the air call just happens to be inside that contact center. Oh, excuse me. Um, uh, and so maybe, you know, that, that helps maybe set the stage.
[00:14:57] [SPEAKER_01] A bit to, to answer the first question, which is, you know, how do we know, uh, if, if I were to repeat it back, like how do we really help customers figure out when to insert humans in these AI workflows? And I think there's, um, maybe two main ways. The first is like, uh, as, as, as it pertains to the business that we do and what customers do on our platform, we have one suite of products that we call assistance technology. That is simply in the background assisting humans anyways.
[00:15:27] [SPEAKER_01] So in those cases is pretty much all human led, except now AI is much more in the background. We have a lot of live assistance technology that can really hear, you know, tone and pick up on words that are key topics. Uh, reps who can follow a playbook. It really helps speed up the training and onboarding of new reps.
[00:15:47] [SPEAKER_01] And inevitably there's a lot of business out in the world where, uh, even if the AI can perform like exactly the same as human, their customers just feel better about talking to a human. Uh, right. Uh, and in those, because it's a relationship business. Um, and, and now I don't know if that's definitively true down the line, but certainly the businesses think so. And I think there's reason to believe that their customers might think so.
[00:16:13] [SPEAKER_01] So in those cases, um, I get it. Like some customers might be pretty hesitant to have voice agents talk to a, uh, to, to humans. Cause it's not part of their brand. And they're, they're trying to, um, convince, you know, a customer that's going to be a longstanding relationship. And the first, the last thing you want to do on day one of that relationship is to throw an AI agent at you, right?
[00:16:37] [SPEAKER_01] That, that does not, um, come off like a long lasting valuable relationship business or at least how one of those would, would operate. Um, and so the way to really have AI help there is to be more in the background, to be able to, you know, train reps faster, to identify key, you know, things that they can object to or help out. Um, because humans, we could all use some help. We can't store everything in our brain. We certainly can't do everything just the right way at the right time.
[00:17:05] [SPEAKER_01] And so that's where the technology really, really does help. Um, now there's different types of businesses that like to deploy, um, AI, uh, whether it's chat agents or voice agents, they're higher in transaction volume. They, they have a different way of doing business. Uh, and generally what we do with these types of companies when they deploy these agents is that there are very easy ways for us to instruct the AI agent and build the workflow with the AI agent in which X,
[00:17:34] [SPEAKER_01] uh, escalation points are triggered. And then the call would route to humans, um, and to your team. Um, and that tends to be part of, you know, the design process we go through.
[00:17:47] [SPEAKER_01] Um, there are certainly tasks in which you can take like refunds, for example, most companies don't want, unless it's like crazy volumes in enterprise world, but most companies in our world don't want like a refund workflow to necessarily have no humans in the, in the approval. Right. Um, there could be fraudulent things happening, all that kind of stuff. Um, so a customer would decide, okay, here's a bunch of topics that, you know, I want to escalate to a human.
[00:18:15] [SPEAKER_01] They can actually design the AI agent workflow with us to say when there's detection on topic A, let's route to this team when there's detection B. Um, and they can even, you know, tweak the knobs a bit on how much an AI agent should attempt to answer the question or solve the problem before escalating. And it's really interesting when you work with these customers, how some customers are a lot more sensitive to the companies who are like, Hey, do the moment there's frustration? Just escalate.
[00:18:44] [SPEAKER_01] Cause that's just how I want to run my business. And then there are others who are more in the deflection kind of mindset. It's like, Hey, try to deflect this, you know, as long as we can. And these are just prompts that go into the AI agent, uh, try to deflect this as long as we can. And then only after, you know, three or four occurrences of frustration, then you, and, you know, I do think businesses have a right to choose how they want to weigh this trade off between deflection and customer service, maybe satisfaction.
[00:19:14] [SPEAKER_01] Um, and we allow them to configure that. We, we obviously, depending on industry would have some best practices, uh, but otherwise, you know, it is up to the business to decide how they want to tweak this workflow and decide when to, uh, move it over to, to, to, for human intervention. Hope that helps.
[00:19:35] [SPEAKER_00] I'm not wanting to talk to an AI. I, I've had the experience of stumbling onto an AI voice agent and it's kind of a relief because first of all, you can, you can hardly tell at this point that it's not a human, but the conversation tends to be much cleaner and much. I don't mean cleaner. Like people are swearing. I mean, just simpler, just more direct.
[00:20:03] [SPEAKER_01] It's, it's funny that you say that we have a lot of customers who over time have shifted towards this point of view. I do feel the more folks use it, the more they can see the benefits. Now is an AI voice agent going to be as performant as your smartest agent who's been around, who kind of has all the knowledge of the things that are never documented? Probably not yet.
[00:20:27] [SPEAKER_01] But I, I do think that it is better than the average rep in, in, in call center. And there's a few reasons for that. But one is at least from the business point of view, I'll put it that way. But even from the consumer point of view, from the business point of view, they're actually more adherent to what you want them to do. They don't, you know, so, so they, they, they don't really go off script or do things that, that they don't, you know, they're not instructed to do.
[00:20:57] [SPEAKER_01] So earlier models were worse at this, but newer models are much better at it, right? So that, that's one thing. And then on the consumer side, I think one very easy to see quality is their patience level is, is infinite. They never get upset, never, you know, they, they, they, their, their, their tone of voice never changes. They're always patient with you. And I think sometimes businesses don't, don't quite like grok those two things like immediately, right?
[00:21:23] [SPEAKER_01] Because they, they, they are comparing against your absolute best human agents oftentimes. And I think for the more experienced, you know, customer service leader, even sales leaders, they start realizing really they should be comparing against maybe the median. And then they might have a different perspective. So I'll give you a couple of other interesting examples.
[00:21:42] [SPEAKER_01] We had a customer who I believe it's out of Australia, actually, but I've heard it from a couple of us customers as well, where they actually, instead of just forcing every customer to a, a voice agent right off the bat, they first asked the customer if they would like to talk to a human or get faster service through an automated AI agent.
[00:22:05] [SPEAKER_01] And surprisingly, they found that people who selected the latter was much, much higher than what they thought initially. And I think it's because they gave the customer a choice of, you know, and a relatively accurate trade-off of choices, which is faster service, but understand as an AI agent versus, hey, do you really want to talk to human? And I think a customer then weighs in their head, okay, do I have a simple thing that should get resolved?
[00:22:34] [SPEAKER_01] Or do I have some super complex one that I just want a human to handle? And by doing that, you really increase the operational efficiency with kind of how you run your customer service center. But more importantly, the satisfaction, like the CSATs of these operations are actually higher. Because you're giving more kind of optionality and control over to the end customer, and they appreciate that.
[00:23:02] [SPEAKER_01] They can call back if things are not working well, right? So I think if it's well designed, more and more consumers are going to move, you know, to the channel that they deem probably have a higher probability of solving these things. So that's one interesting kind of example that is starting to be more frequent. The percentage is just getting higher and higher where people in many ways prefer to be, you know, talking to an AI voice agent because they think it's going to resolve faster.
[00:23:32] [SPEAKER_01] And there's quite a few of those types of examples. But I could probably go on more on some other ones, but, you know, I'll leave it at that for the time being.
[00:23:39] [SPEAKER_00] Yeah, I mean, the other thing about voice agents is, well, maybe it happens with live agents too. I don't know. But you collect a lot of data on the back end that you can analyze and use to improve the service. Does that happen with a live agent? Are those calls recorded and then analyzed as well?
[00:24:06] [SPEAKER_01] Well, it's funny because I in generally, if you are a modern, you know, if you're using a modern phone or contact center system, the answer is going to be yes. There are countries and regulations in which recordings are not allowed. They're not they're banned unless you have prior consent.
[00:24:27] [SPEAKER_01] So that's probably why when you dial into something, the very first thing that this IVR tree or this tree might say is like, hey, your phone, you know, this call is being recorded for training, whatever purposes. That's a very specific law in the United States, in different states. Not all states even have the same, just like you would expect the U.S. to behave. But most countries have something like that. Right.
[00:24:50] [SPEAKER_01] So when you're calling into a company's phone line to get service, I think the reasonable expectation is that, yeah, you're being recorded. It's honestly a little bit odd if they don't have that recording that kind of says that that that happens for live agents as well as, you know, AI voice agents. If any time you're being recorded, it needs to be somewhat exposed to the customer. And that's just law across. So, yeah.
[00:25:19] [SPEAKER_01] Now, what I would say is that more than 40% of the world are not on a modern contact center phone system. I don't know the last time you saw a perhaps a desk phone or an old landline. There's still a lot of the world who's operating on perhaps a more modern version of that. But at the end of the day, it's not a digital service. So without it being digital, it's not something in which you can, you know, get transcripts.
[00:25:47] [SPEAKER_01] And I do think there's an argument to be made that right now why there's so much waves in maybe customers looking at just modernizing, not even talking about AI, just modernizing from an old phone system or contact center to a modern one that's digital is because of the AI wave. You know, people are seeing so much potential with what AI can bring them that, hey, maybe in previous eras,
[00:26:14] [SPEAKER_01] just purely the sake of digitization was not enough to move the needle. Now, suddenly, it's enough to spur a lot of movement. So I do think in the market that there is that element that's kind of also happening. So we'll see. But, you know, that's kind of the observation that I've had. I don't have any hard data to prove it, though.
[00:26:36] [SPEAKER_00] Yeah. What do you learn from the back-end data from Aircall's system? I mean, what kinds of insights do you gather?
[00:26:46] [SPEAKER_01] So we as a platform, we do not actually train on our customers' data or do things of that nature because ultimately it's our customers who have, you know, some way of ownership towards that data. So what we do is we get consent from our customers if they ever opt into a service in which Aircall needs to have, you know,
[00:27:12] [SPEAKER_01] probably do any form of analysis on their data or otherwise for Aircall purposes. But if it's simply just, hey, us parsing the data to show it to our customers, that is part of the general AI service that we have. And I'm not sure folks get the nuance. Like if we wanted to use it for our purposes, that's generally not something that, you know, a company like us do. Right.
[00:27:38] [SPEAKER_01] And I think most contact centers and things like that probably have a similar stance towards this unless we have some kind of opt-in program and et cetera. And that's a sacred thing. You know, I wouldn't recommend customers potentially sign up for service that don't have that outline very clearly. But if you're asking like, hey, what do our customers do with this data? This is where all the magic happens.
[00:28:04] [SPEAKER_01] And I think this is a, you know, post-2015, I would say. This is where you have tremendous amounts of innovation happening because this data, if Digitize transcribes and customers have ownership over it, they can feed it into a number of different services first. Right. They obviously can feed it into the CRM and then use that in conjunction with other data, more structured data in CRM to get a lot more insights.
[00:28:33] [SPEAKER_01] So that's kind of a probably the number one use case all prior to a lot of the newer voice technologies. But nowadays, what our systems are all doing, and especially at Aircall, is we're providing a lot of live services. So we're transcribing this information live and showing it to the agents of our customers and then adding a lot more other value add, you know, live services on top.
[00:28:57] [SPEAKER_01] Some of them I mentioned earlier around detection of, you know, sentiment, detection of keywords in which the companies have configured other answers to detection of these things. And that just reminds these agents of, you know, what they should be saying, making their lives a little bit easier as well.
[00:29:16] [SPEAKER_01] And so that's, you know, I would say if you add all of these things up, it's almost like a lot of our customers now just have this really smart, I don't want to say omniprescent, but very aware agent that is an assistant. You know, it's more of an assistant, you know, it's more of an assistant, you know, it's more of an assistant agent that kind of accompanies you prior to your call that you can ask questions to, you know, in the middle of the call when they're surfacing things.
[00:29:43] [SPEAKER_01] And then post call, as they just automatically take this transcription, they parse it, they make sure the right structured data is going to get fed into your various CRMs, right? And so this assistant is not only helping you kind of just save time and all the diligence work and the, but it's also making your, the key moments matter in your conversations. A key moment in a support call or sales call.
[00:30:09] [SPEAKER_01] So you add all that up, you know, sometimes we like to think that this assistance technology is, is as valuable as a whole kind of sales coach, which you're probably paying upwards of, you know, 150 to 200,000 USD for. And that coach came and survey all the calls. It can't be with you live on all the calls at best. They're just taking a small sample. So a lot of our customers are really buying into that as well.
[00:30:37] [SPEAKER_01] Just they're seeing the significant enhancement in kind of how fast reps onboard, how, how much better and quality that they're keeping, you know, assured, let's say with, with, with, with every single call that's happening through their, their human agents.
[00:30:54] [SPEAKER_00] Yeah. How do people implement this? Is this, is this, I mean, is it primarily through, you know, a phone number, a publicly listed phone number? Is it through a chat bot on their website or.
[00:31:10] [SPEAKER_01] When you ask how to implement, like, you mean the end to end of air call or just the AI parts of it?
[00:31:16] [SPEAKER_00] Yeah. So if, if, if I'm, if I'm an air call customer and, and I have, I don't know, a, a network, a global network of. Sales. Right. You know, a sales force that's selling a. Complicated set of products that I manufacture.
[00:31:43] [SPEAKER_00] How, where are people touching the air call system? Is it when they, they call the company or when they look at its website or, or, you know?
[00:31:53] [SPEAKER_01] Yeah. So, so I think the first is like air call is, is business facing for, from the end consumer customer side. They don't know what, you know, phone system you might be using. So irrelevant to them. Of course, you might run into an AI agent and it's an air air call agent, but for their purposes, it's like any other, you know, voice agent. What I, what I would say is that like, I'll just walk you through conceptually.
[00:32:16] [SPEAKER_01] Conceptually what happens is when a business signs up air call, they've made the determination that they want voice as a channel or sometimes WhatsApp and messaging as a channel of communication with customers. And pretty much all companies need a form of that one way or another, but they need to decide, you know, how much of that support volume or sales volume they want on voice versus other channels and different businesses have different calculuses to that. Right. Right.
[00:32:41] [SPEAKER_01] But definitively, almost all businesses try to have a phone line at some point because it's just so synonymous. Unless you're like a small e-commerce shop that you're just doing things online. Right. But most businesses, especially local businesses need that. So what air call allows you to do is first, you can procure a lot of phone numbers through air call, which, you know, is not as trivial as it sounds. Phone number is kind of a regulated thing in all countries.
[00:33:08] [SPEAKER_01] So if you want to go get a phone number, a business phone number, you can't just willy nilly buy it. And then, you know, you need to register your business because there's a lot of spam and fraud considerations that all the governments around the world have put into this. This is not an anonymous chat online. Right. So the phone numbers mean something to governments, let's say. So air call first just helps you get across that hurdle.
[00:33:34] [SPEAKER_01] If you want a phone number, yes, you still have the register, especially if you want to do SMS in the United States. For instance, you have to have a business website. We would parse your business website. We would you had to put in, you know, all these reasons for why you need to use SMS. All of these things are done to make sure that when you do communicate, the different telco networks around the world are going to be able to pass through your message or otherwise they're not going to pass through that message. So.
[00:34:03] [SPEAKER_01] Understandably, I think governments, you know, want to have a bit of control over over communication channels as like such as phones and SMS. So that's first. Now, once when you've decided how you want your phone lines to be set up, whether it's an individual line for all your sales reps or it's one line and everybody calls from that line, how to inbound routing really works, whether you post that, you know, phone number on the website or that phone number only shows up after you maybe purchase a product.
[00:34:33] [SPEAKER_01] Whether it shows up in the footer of your sales reps, like all of those are business decisions that companies make on what they might deem to be as demand. Because the more you let this show up publicly, the more like phone calls you're probably going to get. Right. So then from that point forward, now you're probably getting into some of the questions around how do we set up AI with every single phone line?
[00:35:00] [SPEAKER_01] You know, you can you can attach agents that can handle calls right at the top of the IVR tree or anywhere in your logic. It can be after 8 p.m. before 6 p.m. These calls will get routed to the agent or all times it's going to be routed. But, you know, during business hours, there's escalation to humans after business hours. There's no escalations, but we'll leave a message.
[00:35:27] [SPEAKER_01] And you can configure all of that like directly on the phone number. Then you have your human agents and users attached to to these different numbers to the different, you know, inside baseball terms like ring groups and et cetera. Conceptually, this is kind of how it all works. And we try to make it as easy to use, as simple as to set up as possible for these small teams.
[00:35:51] [SPEAKER_01] Whereas typically, if you, you know, really try to work an enterprise product in our space, you will be hard pressed to set that up on the same day. We try to pride ourselves, you know, to be able to you can finish and get your operations live within the hour. So that's one of the maybe differences for air call as well. And I do think the more you get into AI products nowadays, the more that principle needs to hold because they're just getting so complicated. And sometimes for good reason, because you want to control everything.
[00:36:21] [SPEAKER_01] But it doesn't necessarily mean like the starting point needs to be so complex.
[00:36:25] [SPEAKER_00] Yeah. And in that you're focused on voice, can you talk about what the under the hood, what tech you're using?
[00:36:36] [SPEAKER_01] Yeah. I think most companies who are doing things like voice agents, there's probably, you would say, I'll break it out into at least two major stacks, tech stacks. The first is just your voice stack. So like, take AI out of the consideration.
[00:36:57] [SPEAKER_01] Like air call, we have parts of the voice stack that's on infrastructure, you might use, you know, a communications, a service provider like Twilio, you probably have to communicate with and work with different carriers around the world to acquire numbers. Right. And of course, you have AWS and all these compute providers that you're probably hosting these things on. But nonetheless, we like to call this the general VoIP stack, like voice over IP stack.
[00:37:23] [SPEAKER_01] There is, you know, how do you turn kind of communications that's happening, maybe on some cases on the other side of the line, a landline into something that is now digital, etc., etc. So that's the voice stack. Then there is generally the, you can say, the generative AI stack. And typically in the general AI stack, for a company that is dealing with voice, you always need something that takes human speech into translations.
[00:37:54] [SPEAKER_01] Like, so text, we call that speech to text. And then you generally would then feed this text into an LLM. So you think the open AI, the Geminis and the clods of the world, then the LLM is going to spit out some response from that text. So now then you got to take that text and convert it back to speech. So in the more traditional way of doing things, there is a speech to text, an LLM and the text to speech pipeline.
[00:38:20] [SPEAKER_01] And then once you have that all hooked up, it is then placed directly in your VoIP stack. So it's communicating kind of live, right? Some using a lot of layman terms to describe it. But conceptually, that's how you can think about it. But there's a few things in which I think the technology is evolving that most of us are paying attention to quite a bit. One is what they would, you know, we call it the voice-to-voice models, which is the inputs. You don't really control that three-legged stool that I was describing.
[00:38:51] [SPEAKER_01] It's voice-in, voice-out. The LLM is part of it. Most companies, including OpenAI, Grok, and all of them have voice-to-voice models nowadays. There are trade-offs on whether or not you want to pick something like that or something which you want to control the different legs. That, you know, I oftentimes find that the more control and the more at scale you are, the more you're going to choose to stitch those things together yourself. Because you're inevitably going to run into edge cases from all the different customer use cases.
[00:39:20] [SPEAKER_01] And without having the control, there is very few ways to even, you know, troubleshoot and really control that. But it's also not easy to optimize for latency in some of these cases. And so if you had full control over the stack, you can, you know, voice is a very latency-sensitive kind of technology, right? So someone who's talking to a voice agent doesn't want to be waiting 1.5 seconds for every response. So having some control over that helps as well.
[00:39:47] [SPEAKER_01] And latency, it has a lot to do with the telephony stack, the VoIP stack, just because you're routing data packets sometimes from, you know, US to London or Paris. And so when you add all of that up, there is a lot more, I would say, complexity than what meets the eye when people think about voice agents. And so, you know, I'll leave it at that.
[00:40:13] [SPEAKER_01] But, you know, I could probably talk for hours about some of these underlying complexities. But that's kind of a quick 101 on how folks, you know, how we all generally build them. But the devil is, you know, 100% in the details.
[00:40:27] [SPEAKER_00] And you're seeing like massive growth from what I've seen.
[00:40:35] [SPEAKER_01] Yeah, I don't want to toot our own horns. We are growing quite well. And I think we're only at the tip of the iceberg, I would say. Because there are a few reasons why I think. One is I do think voice is getting more popular. I think prior to LLM's voice, you might have actually, you've probably seen articles where, you know, messaging is the future and everything's going to be asynchronous chat and communication.
[00:41:03] [SPEAKER_01] And I think what LLM somewhat did was that it made the cost of serving customers through voice more economical. Yeah. And, you know, the thing is that the world is just so competitive. I mean, if you, customer service is a competitive space, right? Because you're always, you know, there's a lot of commodity products out there and where customer service matters.
[00:41:26] [SPEAKER_01] And so in the spirit of kind of human ingenuity and competition, they're always going to search for an edge. And I think more and more customers are finding that, look, if we can offer voice as a channel of communication with customers, it's an edge that they have over companies who don't have that. Previously, it was just cost prohibitive. You know, it's hugely cost prohibitive to train humans and to do that.
[00:41:53] [SPEAKER_01] And nowadays, it's you can get off and running with voice agents or even enhancing your human agents if you have them already in a much more, you know, progressive way as well. Meaning like you don't have to put in upfront costs immediately. You can kind of progressively roll it out, really get an understanding for the impact and et cetera. And so that I think is a big accelerant to our space.
[00:42:19] [SPEAKER_01] And I think the other one is what I would say is there has been a culture in the last 25 years, but I call it like the deflection culture. Most companies somehow figured out that deflection is the number one metric that matters. And it's a little bit at odds with what really matters, which is customer satisfaction.
[00:42:41] [SPEAKER_01] And so voice not only plays into that, but it allows us, you know, to allows a lot of customers, quite frankly, to just provide an experience that doesn't seem so much like it. You know, their main goal is to have you not talk to them anymore. Yeah, I know. That's crazy.
[00:43:00] [SPEAKER_00] It really is. Just on that point, you were talking about having a phone number. I mean, more often than not, when I'm trying to get in touch with a company, I can't find a phone number. And they'll have a form on their website. You have no idea whether it's being monitored. And usually it's not from my experience.
[00:43:25] [SPEAKER_00] That is very, you know, that seems like a simple fix if you could.
[00:43:32] [SPEAKER_01] Certainly. And I think more and more companies are starting to realize that. It's like every communication opportunity is a business opportunity. Whether it's shoring up, you know, your connection with the customer, even if they're just complaining about something. Or it's like a real qualified opportunity that you might be missing out on. And it makes absolute business sense to be able to, you know, have something that can just take calls for customers 24-7.
[00:44:00] [SPEAKER_01] There is very little, I think, downside to a lot of these. And I think more and more businesses will just start to realize that. And at some point, it's going to be so prevalent that, you know, there's a new frontier of competitive advantage that companies have to find. And I'm certain that, again, in the spirit of human ingenuity and competition, that they will find them. But for now, I think a lot of companies are just really trying to – AI is scary to many of them, right?
[00:44:27] [SPEAKER_01] Just to get across that initial technological barrier, get across – and there's a psychological barrier of AI as well. And to just get that basics in place and start to move incrementally towards that. And, you know, we're here to really help that as well. We understand that it's not just a simple flip of a switch. Yeah.
[00:44:47] [SPEAKER_00] Yeah. And how do you price this? I mean, is it affordable?
[00:44:52] [SPEAKER_01] I think it's very affordable. What we generally – like the way we thought about it is – and I think the market has different ways of pricing. If you are working with customers that have a very clear outcome on what they use you for, you will see many ways out there that's kind of like resolution-based pricing or outcome-based pricing.
[00:45:15] [SPEAKER_01] For Aircall, however, because we're so horizontal as a platform, it's not exactly that simple or straightforward to kind of have a resolution-based strategy. Now, we can certainly say, hey, like, what exactly is your goal? How do you – what do you define as resolution? But what we find is that that gets us into too much of like an attribution battle with customers or like an attribution conversation.
[00:45:41] [SPEAKER_01] So, we've kept this simple and just made it – look, it's pay-per-use. All actions that happen after are free. So, if you can make really good use of your configuration, the value far, far outstrips kind of what you pay.
[00:45:56] [SPEAKER_01] And what I mean by that is, look, if these phone calls that you're having are resulting in like 10 other automations that otherwise your humans have to do or it's resulting in business leads, we're not even trying to capture that upside. Even though some might argue, hey, look, you should try to capture that upside. You're just paying us for what it costs us but also a little bit of margin on top like all businesses do, right, on top.
[00:46:23] [SPEAKER_01] And now there's probably various different disagreements on how much value are we capturing. But my general thought is that this space is so competitive that in the world of value-based pricing to cost-plus-based pricing, initially more and more companies might be able to get away with value-based pricing.
[00:46:46] [SPEAKER_01] But I think long-term, just due to competition, outside of the extreme enterprise worlds where there is a compliance and there is low threshold, like low number of competitive, like viable contenders where you can have true value-based pricing, my guess, and this is, you know, again, 99 out of 100 might disagree with me on this.
[00:47:09] [SPEAKER_01] My guess is that it ends up being a bit more cost-plus long-term just because of competition. And so, and then in our world, you can't really do token-based pricing, right? And there's all sorts of, by the way, I can sit here and give you a 15-minute argument against what I just said. But it's totally, totally, I could totally do that.
[00:47:35] [SPEAKER_01] So, but I think we just pick something that, you know, kind of works for our customer base. We're more horizontal, a lot of different use cases, high variability in the goals that our customers have. And it's harder to be a little bit more outcome-oriented. I think the cost and the trade-offs of having the debate potentially on what an outcome really is, is not worth the potential, you know, people might call it incentive-based alignment and things like that. So that's just what we've picked.
[00:48:04] [SPEAKER_01] And sorry, I'm being a little bit long-winded on this one. But generally, what we also say is, okay, let's take how many minutes, you know, you can have as compared to a human agent. But now let's also factor in the flexibility that this person can multiply themselves to 100, which is to say that typically a human agent can only take one call at a time. But with an AI voice agent on air call, they can take 100 concurrent ones at a time, right? They don't sleep. They don't take lunch breaks.
[00:48:33] [SPEAKER_01] So it's infinite flexibility and scalability. So once when you factor that in, you know, we feel very comfortable that if you really priced out someone that can do like, let's say, one agent's worth of work, that it's almost like a no-brainer to hire, let's say, air call agents to do this work. Because from the flexibility to the instant training, by the way, to the actual cost, you know,
[00:49:03] [SPEAKER_01] I wouldn't be surprised if, you know, it's the ROI, let's say, is you're getting something in the value that's probably one-third or one-fourth, maybe even one-tenth the cost of what it would take fully loaded for you to have an operation like this with humans. And by the way, we also don't tell our customers that, look, go replace a human. I personally don't even really believe that is the way businesses are going to operate.
[00:49:30] [SPEAKER_01] What we see across our customer base is that, look, the extra workload that these AI agents are taking off, they're just finding other ways to get, you know, their existing agents more work, including higher level of, you know, conversations. So it is definitely true that people are, or companies are certainly recategorizing some of that work, and people are being trained to do a different form of higher intelligence work, let's say, instead of, you know, repetitive work.
[00:50:01] [SPEAKER_01] And I think ultimately that's great for companies, for society. I'm not a huge AI doomer, job replacement kind of, those thoughts don't really enter my mind as much. I generally think that, again, human ingenuity and business competition, you know, it's going to create a lot of demand for human intelligence to a reasonable degree.
[00:50:26] [SPEAKER_00] And I have to ask, this is B2B, but is it priced such that a consumer could use it? A consumer, I mean, a business person.
[00:50:37] [SPEAKER_01] Yeah, personal business. I think so. You know, it's probably a target that Aircall has not been, like, historically super focused on. There are a lot of companies that probably do this in a way where they really focus on them. I wouldn't say that you couldn't, but you might notice that we tend to target at least a small team, right?
[00:51:02] [SPEAKER_01] We tend to, you know, we want to make sure that the ideal customer profile is a little bit more on the small team side and not, like, the personal business side. But it's, I never say never to that. But it's just that, you know, we all kind of pick our lanes on what the best product experience is for a particular type of business. And, of course, you know, we've kind of picked our lane. And then we can go from a small team all the way to many teams.
[00:51:29] [SPEAKER_01] But there is a, I would say there are some differences between, like, a personal business and a small team on all sorts of, like, dimensions.
[00:51:39] [SPEAKER_00] Yeah. Yeah. And what kind of pitfalls do you see your customers either having fallen into before they get to you?
[00:51:49] [SPEAKER_01] I think this comes back to maybe, like, why knowledge work is sometimes so hard to automate. You know, some customers are very optimistic that they can get high resolution rates, let's say, by using a voice agent. And if we had perfect information, yeah, you might, you probably can't. In many ways, I think the AI technology is somewhat commoditized.
[00:52:14] [SPEAKER_01] But what is not commoditized is all the products and services that really helps go discover the missing knowledge in your company that can then help the AI technology really perform the level of automation you expect. And a good example I would draw to this is, like, in the most prominent form of AI automation that you see today is, like, code generation, right?
[00:52:40] [SPEAKER_01] But the thing with code generation is that a lot of what the context is needed by, like, say, cloud code or any of these code generation is somewhat, like, documented in your code base. What we typically find with customers, especially on a smaller end, you know, it is still tribal knowledge. Knowledge is still missing from kind of how these operations run. You have – that's why you still see, hey, look, you got a customer service agent or sales agent that just does their job better than others.
[00:53:09] [SPEAKER_01] They've been around the company for a little bit. They know the missing knowledge. They know the fact that they're not going to be able to do that, but they're not going to be able to do that. And so the question isn't, like, how well can the AI perform if given perfect information? It's how do you get that perfect information from your customers in the easiest way that doesn't require them to kind of sit around and do all of that work to get it there?
[00:53:35] [SPEAKER_01] So that's where I think, you know, the context engineering, the data services, the easy-to-use nature of your product, they all really factor into this. And so the pitfall I oftentimes see is that customers – whether you view this as a customer's job or, you know, like our AI agent's kind of responsibility is that they are overly optimistic on just how well an AI agent might perform
[00:54:01] [SPEAKER_01] and how much context is really needed and which translates to how much effort that they might have to do to get there. And half the time, it's because most smaller companies don't have this stuff documented. So if they have, you know, more documentation, these things would make things easier. So, you know, what we're really trying to figure out even as a company is how do we make that easier for our customers? Smaller companies, they don't have the same resources, right, as a large enterprise.
[00:54:30] [SPEAKER_01] Company who might be very vested in creation and maintenance of this AI agent. So they would certainly, you know, put more resources towards a project. For small companies, I think we just got to – we have a lot of work to do still. And I would venture to say that most SMB-oriented, you know, AI agent providers are all trying to solve this problem because I think what I said is fairly universal in smaller businesses.
[00:54:57] [SPEAKER_00] Yeah. Okay. Okay. Well, we're up to an hour. This is really interesting. I hope everybody adopts something like Aircall so I have an easier time when I'm calling into places. If people want more information, how do they reach you guys?
[00:55:18] [SPEAKER_01] Well, it's easy. Just Aircall.io is probably the easiest. We, you know, we are even undergoing some of the brand we design currently at the moment. But we want to be the world's best for growing businesses, for customer communication with AI agents that natively sit on top. So you don't have to do a lot of the busy work or the heavy lifting to even configure these things.
[00:55:42] [SPEAKER_01] I'm very confident that, you know, us as a category but also Aircall as a product is going to be kind of one of the defining pillars of AI adoption in the world. I think it's going to be a much better customer service, much better sales experience for the world moving forward. And so very bullish, obviously, as attested to my employment here. But I really do think that.
[00:56:09] [SPEAKER_01] And I hope, you know, next year if we ever talk, Craig, that you have a very different experience on how prevalent this technology is. But thank you for having me on the podcast as well. Really appreciate the time. We appreciate your listeners. Thank you.