Twilio Inc (TWLO) May 2026 Conference Transcript

We'll get started. Thanks, everyone, for coming. Derek Wood, Senior Research Analyst at TD Cowan, IIC's in Excel. Appreciate your support. And we've got VP of IR, Rodney Nelson of Twilio. Thanks for coming, Rodney. Thanks for having me. I am going to give you kind of a softball question to start with, I think. And it may just kind of lay the foundation here. But you're, I mean, the stock has had just, you know, great performance this year. You know, obviously you guys have gone through a big evolution over the last few years. But, I mean, there are a lot of things. I mean, there's been really impressive growth acceleration in the business.

Like, how would you set the table in terms of, like, what's really been working and, you know, know kind of behind the scenes on the on the organic growth acceleration it is just that i mean it's been you know call it a three-year journey to get to the point that we're at today as a business um you know we were i would argue one of the first software companies that quote unquote took our medicine after after all everything that happened in covid uh we made a lot of really difficult decisions to inject financial discipline into the business you know headcount is down roughly 40 from the peak it's been about flat for two years now we've been operating at about 5,500 employees since the start of 2024. And so you now have a team that's largely been in place kind of from top to bottom with Kozama taking over as CEO at the start of 24, bringing in a couple of really, really polished and really outstanding senior leaders to run marketing, run product, run sales. Pairing Kozama with Aiden as our CFO over the last several years has been a very dynamic duo in the business. But I think most importantly, we inject a lot of discipline, rigor, and focus in many different areas of the business. And a lot of that started on the P&L when looking at margins. So obviously margins have come up considerably over the last couple of years, going from a business that was roughly breakeven to now one that is on the doorstep of 20% operating margins and something similar on the free cash flow side. And then here recently, I think where you see the discipline and focus manifesting in the business is in the innovation velocity. We've really doubled down on the areas where we have a right to win, particularly in infrastructure we you know effectively abandoned our ambitions in the app layer that we were pursuing many years ago and the net result of that is a much more efficient and a much more productive product organization and the the captain of a lot of that work here recently came at our signal conference a couple of weeks ago but along the way we've managed to re-accelerate the messaging business which is our largest business we've seen some emerging tailwinds in the voice business which has catalyzed growth there and is now growing its fastest rate in five years but you're getting a much healthier and much balanced version of Twilio today than I think you've ever seen and we've augmented that with a pretty meaningful shift in capital allocation being much more tilted towards capital returns which has amplified the financial performance of the business over the last few years so it's been a lot of things not just any one thing but this is I would argue the strongest Twilio has ever been in the ten years we've been public.

Nice way to lay it out there so you know Voice is, I mean, Kazama talks about this renaissance in voice, and obviously that we've seen a big acceleration there. Can you just give us a sense of what's behind that? It sounds like a lot of the startups there, I mean, I think we, and I've seen other people kind of position, like you guys are like the AWS of voice for these startups. Like you're the platform that they're building on. Is it all just the AI natives? Is it, you know, what are you seeing from the ISV channel? Give us a little more bottoms-up look on what's driving voice right now.

Yeah, I mean, I think what's so great about our business is our core platform, our longest-running product is actually our voice API. When Jeff started the company 18 years ago, the very first product was our programmable voice API. So we've quite literally been in this business for almost two decades. And the one thing that is true for an AI native that's also true for an enterprise, that's also true for a more traditional-looking ISP is none of them are in the communications business. And so if they want AI agents to do the bidding of what was historically served by a customer service agent in a contact center somewhere, at a very minimum, you still need the connectivity layer. And that's where our super network comes back into play. If you have customers all over the world, you need the full breadth and depth of 4,800 carriers globally. You need to be compliant in all 180 different countries that we operate in. The rules and regs change constantly. You have to be on the lookout for fraud and robocalling. and all of those capabilities are things that we've been building and compounding for the last 18 years. They're also really gnarly and frankly unsexy problems that nobody wants to rebuild and kind of recreate the wheel on. And so we've taken something that is absolutely critical and vital and incredibly hard to do at global scale with reliability. And even though it looks undifferentiated to our customers, it's mission critical to how they solve these problems. And that's just as true for the AI natives as it is for customers that have worked with us for 10, 15, almost 20 years. And I think what's interesting with the AI natives in particular, you know, the best use of their resources is to build what's differentiated in their product stack for their customers to solve, say, customer service AI. They have to have a enterprise-grade communication stack from day one. You have a shot at winning that business. And what we've seen with the AI natives is they not only rely on Twilio, come to us through our self-serve channel. So they're voting with their feet and their dollars to use Twilio as a provider of choice. They're also then leveraging our reputation for quality and reliability in those RFPs to say you're getting best of breed AI capabilities up here and you're getting best of breed communications capabilities down here and that's because it's coming from Twilio and so in just about every case we are providing the telephony infrastructure to actually power that call back and forth between an agent and a human but increasingly we're also selling through many software out on some of which we've sold for a very long time some of which are newer to handle more features up the stack if you will while staying in the infrastructure layer and so that could be orchestrating the models themselves the speech-to-text and text-to-speech chain that would be our conversation relay product that could be streaming real-time intelligence off of that call that would be our conversation intelligence product and a variety of other features in between and so a lot of the momentum is happening in the voice business because customer service is such a rich opportunity but there is an emerging opportunity and messaging as well that we can speak to if desired when you guys talk about voice being the new kind of entry point for new customers I mean is that mostly from the AI natives that's a lot of times where they will start yeah I think that's become the new front door if you will and self serve and a lot of that is AI natives but it's also for just new businesses that are building themselves in the AI era and so they maybe think a little bit less about how do I go and procure all these different package software solutions to, gee, I have all these tools, I have CloudCode, I have Codex, I have Vercel, I have all these things that allow me to build exactly what I want with relative ease, and communications is one of those things that I can now plug into natively, whether that's coming directly to Twilio's new console, which we just launched at Signal, or accessing these tools through coding platforms. It's never been easier to get up and running with Twilio's stack. And so it is absolutely AI natives that are coming through the front door, and that front door is voice, but it's just as much kind of the AI-enabled business, if you will, that's entering the call there as well. Can you give us a sense what, like, conversation relay and, like, what that ecosystem looks like and speech-to-text and text-to-speech, and when do you guys win, when do you guys partner, who are the partners that may, like, you know, be alternatives than using your Yeah, I think it's important for us to always recognize who we are, and then that dictates what we build and what we partner on and what we may leave to others and so in our case we don't want to be a model building company you can see that in the text-to-speech and speech-to-text landscape you're starting to see that in the speech-to-speech landscape you've already seen that at the LLM frontier lab level the model layer fragments pretty quickly and we've seen that at just about every single layer of the stack and that creates complexity for our customers so rather than pour a lot of capex dollars into the ground to consume a bunch GPUs to train a model, we would rather partner with a variety of different ecosystem players, give our customers as much choice as possible, but do it through a single product where you don't have to then go out and procure maybe five, six, seven different vendors to do everything from speech to text, text to speech, the LLM, the speech recognition, the turn detection, the interruption handling, and oh by the way, the connectivity. You can do all that through a single provider in Twilio, and then the added benefit is you get better input costs because you're not paying rack rates to the individual model providers. And then you're also getting the ability to pick and choose which models you want to leverage. So if you want to switch from model A to model B, because model B is maybe now just a hair faster or has a bit better speech recognition, that's a very simple configuration change on a massive re-architecture of a software platform. So it gives our customers much greater flexibility than being overly committed to any one model provider.

So yeah, I mean, you play the orchestration layer into the models, whether it's an LLM or a speech model, and drive the connectivity there. The use cases, I mean, you talked about customer service. I mean, that's, I think, one everyone's familiar with. I mean, are you seeing, like, outbound sales and marketing, voice AI? What are you seeing in actual call centers? Like, where is, like, the strongest adoption from a use case perspective?

I think what's interesting is you're seeing emergent use cases in just about every industry. We've talked a lot about how in health care it's now much more efficient and a much better experience for the patient to have an AI handling billings questions. They're often, the bills are often very confusing. There's a lot of words on there that the average person is not going to understand, myself included. And so it might require a patient to ask a question three, four, five different times just to really fully understand the answer. if the person or if the thing on the other side of that call is a human, a certain degree of frustration is going to build. They have a cycle time they have to be managed against. With AI, none of that exists. It can be endlessly empathetic. It can be endlessly sympathetic. It will answer the same question multiple times if need be. That call actually winds up taking a little bit longer, but it still costs our customer a fraction of what it used to cost them to solve that patient's problem much more effectively, even if the call now runs seven minutes instead of three. But you're also seeing, I mean, there's been a lot of service-level businesses, home services companies, many of whom consume our capabilities through an ISV, where they are getting inbound appointment requests in the off hours, where nobody is around to actually take that call. They're effectively finding revenue by having AI agents serve those shoulder periods where maybe a call comes into a plumber at 8 p.m., they're not monitoring their systems, they're not answering their phone, but the AI agent can take the call. that's found revenue. That's an appointment they otherwise would not have gotten. And then you are also starting to see a bit more outbound as well. I'd say it's predominantly sales, a little bit less marketing. But anywhere that you can have a conversation and leverage AI and memory and intelligence to drive a more intelligent conversation, whether it's inbound or outbound, we're beginning to see experimentation in all those different dimensions.

So, I mean, I know you guys don't guide to this, But I mean, you know, in terms of like what pretext for a question, in terms of like what could be elements underneath the model that can keep growth accelerating or just like see new catalysts in the model around AI. I mean, whether it's expanding use cases, moving more into the enterprise, like just what you talked about on what sounds like increased minute usage, or more new customers in the front door, or what you announced at Signal under the persistent memory, and there's upsell, cross-sell there. I mean, that's a lot to throw out there.

Well, I think maybe as a starting point, at least through the lens of AI, it is still exceptionally early. I've called three different hotels in the last 72 hours. Two are part of a major chain. One is a boutique. I was met with zero AI. And these were very basic customer service questions. I was literally like scraping around trying to find a bill to submit my expenses. That is tailor-made for AI. Like that, all you need to do is plug into the billing system, have some understanding that my phone number is probably associated with that bill somewhere, and you can trigger that instantaneously in the context of that conversation. And yet, I was put on hold for five-plus minutes in every single instance. So even there, where it's a fairly rudimentary use case, we're not yet seeing the proliferation of this technology yet. And so I think that does create some secular tailwind that I think can benefit not just the voice business, but frankly, all of the channels. Because one thing that we firmly believe is, if you're going to roll out AI and have more intelligent conversations with your customers, you have to recognize that those conversations happen everywhere. Personally, I would much rather text that hotel and get my bill that way than have to spend time on the phone, whether it's a human or otherwise. And so we do see more customers, whether it's AI natives or our direct customers, increasingly looking at how they can leverage all of these channels in sync with one another, and that's where elements like conversation memory, conversation intelligence, and orchestration come into play. So in the old world, if you were building with Twilio, you'd have to write glue code to staple all of these channels together. that's effectively what Orchestrator now does out of the box. You'd have to have some agent or some platform that's giving you that real-time insight into what's happening in that call. That's been conversation intelligence for Twilio for the last couple of years, but that product has continuously evolved to include more channels and become real-time. But then you need some layer that's going to reinform the next communication of who I am to that business. So if I have a phone number on file with United, every time I call they should have some idea of why I'm calling, what flight it's related to, what issue could be a part of that call, and effectively head off the reason for calling before they even pick up the phone. That is all possible with memory, because we can extract those insights off of that call in real time, reconcile it back to a profile, deduplicate observations that we see, and maybe eliminate previous observations that had been filed in that profile. So you always have the most current, most informed view of who that consumer is to then deliver a relevant and contextual response to whatever the next use case may be, sales, service, marketing identity, et cetera.

I mean, that sounds like a big deal. So what was new that really came out this year on memory capabilities? I mean, so you kind of just said it. You had to stitch a lot together, and now you've got much easier access to that memory to orchestrate that? Or what's been the big advancement?

So as I'm sure folks in the room remember, we bought a business called Segment in 2020. and the vision of what the communications plus segment capabilities were supposed to look like is effectively what memory is now today. The challenge was, see above, if you wanted to use segment in concert with maybe a custom source system over here and all the disparate channels that Twilio would provide, there was custom pipelining that would probably have to be done to that custom system. There was stitching of the channels together. Those channels did not live in a single pane of glass. There was a separate system for SendGrid, a separate system for messaging and voice. Segment was a separate platform altogether. So there was a lot of maintenance code, effectively, that had to be written to even get to the point where you could begin streaming real-time insights and reconciling them to a profile. So we took a lot of the DNA from Segment, and that's what belies what's going on in the customer memory product today. But instead of going through an onerous multi-week, multi-month sales cycle to buy Segment, implement it, and then do all that work, customer memory is simply an API, and it's natively integrated into all the channels in our new console so that the second you turn it on, which is literally just effectively a click of a button to turn it on, you can begin streaming insights into memory, capturing them in a profile, and going even if you're from a cold start. That's a far cry from a multi-month sales cycle, probably a multi-month implementation, and some additional custom work to get to that point. So effectively what we did was take the best components of Segment, make it accessible as an API that is natively integrated into all the channels.

And the API APIs into customer data sources, like into your own data sources.

So if you want to take that memory, so we have APIs to ingest enterprise knowledge, but then if you also want to take the data that lives in customer memory and pipe it back out to source systems, that is available to you as well. And that's frankly a feature of our platform. We wanted to build these things in such a way that you don't have to rip or replace a single system if you don't want to to have these tools available to you. You can begin deploying them and gaining insights from them from day one. And that's, again, that's part of the value prop is we are a neutral platform that can be interoperable and play well with any model provider, any source system, any data lake, any data warehouse. That whole idea is to make the platform accessible, and that's also where Artilio Agent Connect SDK comes into play. You can deploy that in any ecosystem. It's self-hosted. It's a very simple SDK, and you can pipe agents into the platform from there.

So where does LLM sit in your stack? I mean, where are you actually leveraging AI internally for users to, like, be able to maybe execute multi-channel orchestration better or, you know, build campaigns or something like that? I mean, like, yeah.

Yeah, I mean, we're of the kind of bring-your-own-LLM mind. Like, again, see above. We want to play well with everyone. So we don't try to funnel a customer in the direction of a single model. There's actually only a small number of products where the P&L of the product, if you will, would be burdened by an LLM. Conversation intelligence comes to mind. That product is effectively monetized on ingestion and then custom operators you would have running over the top of that call. So if you're a dealer and you have an AI agent taking inbound calls for test drives, 95% of the words on that call probably don't mean a whole heck of a lot in the context of that business. But if I say make model trim in a year, I want those insights extracted and reconciled back to my profile. If I say that I have four kids and I'm talking about a mid-sized model, that should be a trigger to the salesperson. Like, hey, maybe test drive the full size with the third row that can seat seven because you may need it someday. All of those things should be able to be captured in real time to inform that next engagement, whether it's the follow-up text that I'm going to get or the in-person communication I'm going to have on site with the dealership. and so that is a product where you would have some burden of an LLM that gets embedded in the cost though and the real value to us is those generative custom operators and then the piping back to memory and the orchestration by the way between those different communications channels but we don't actually have a lot of product where we're just creating a wrapper around an LLM by design that's not the value that we want to provide we are consumers of tokens in our engineering organization of course but there's not a lot of that embedded in the business today.

Are you monetizing API calls in that memory layer?

Yeah, that's effectively the pricing mechanism for memory. It's effectively API calls. Intelligence, again, is kind of ingestion, and then operators running over the top of it. Orchestration is, again, on more of an API call basis, somewhat nominally priced, and again, the whole intention there is we don't want to preclude people from driving more volume in the platform. So if you want to send that follow-up communication via text and then engage that consumer in more of a two-way communication, but that's orchestrated based on what was said in a service call, we don't want to preclude that from happening. So the economics are probably richest in memory and intelligence, but then if that also comes with the added benefit of more volume, then you really hit a home run with the customer.

The new products that were announced, do you see them as being any kind of material catalysts the next 12 months? on? Are they more enablers as opposed to like direct monitoring?

Well, I think for starters, we don't have, we don't really have outsized expectations for them this year. I mean, they went GA in early May. You know, we're halfway through the year effectively. Like, they're not really a material contributor to the guidance that we have out there for the balance of the year. But these are products that we've been talking to our customers about for the better part of two years. And I do think that made this product development lifecycle particularly effective is we were constantly gathering feedback from our customers along the way of number one where do you want us to innovate number two what do you want to look like and there were some there were some additions that we made along the way I mean when we think about like Twilio Agent Connect or some of the innovations that we launched in partnership with the coding platforms at Signal like those were maybe not on v1 of the roadmap but we had to not pivot but but make adjustments on the fly as the AI ecosystem continues to evolve around us and those were very well received by our customers. And then on top of that, we were very intentional about bringing partners into the beta for a lot of these new products so that they would be fully enabled out of the shoot to kind of talk about how you could use these products, what the prevailing use cases are, which has been a point of emphasis for Thomas and his team over the last couple of years is to really lean back into that partner ecosystem.

Who were those? Did they come on stage on the?

We had a number of them at Signal. Day two? They were there at day two. They actually had some incredible sessions that could basically show you in the space of a single prompt in Claude go from a cold start with Twilio, no account, no API key, and after 30 minutes of Claude doing its thing you had working Twilio product and working Twilio use cases, which is pretty incredible. I mean, we've never necessarily had the GSIs as a big part of the story, simply because APIs don't require a lot of heavy lifting, but there are some incredible boutique partners that we've been working with for a long time who participate in that beta and are kind of enabled to deliver these new innovations too.

So they were service partners? Well, I think we've got to talk about the messaging business. Of course. That also has accelerated. Has that been because of the synergy with voice or what else is behind that? I mean, a little bit.

Again, we try to position the platform as conversational and omni-channel by default, and that's exactly the experience you have in the new console. So there's no longer this fragmented, disparate, you know, one channel lives over here, one channel lives behind this login over there. You now can build in a much more conversational fashion in the new console because all the channels are right there available to you. That's more on the come because the console, it was just launched a handful of weeks ago. But look, like we've seen kind of remarkable resilience in the messaging business, And it's not coming from any one place. Our top five or six industries, which make up the bulk of the business, are all seeing really healthy rates of growth, tech, financial services, health care, professional services, retail and e-commerce, advertising and marketing. I mean, they're all performing very well. Geographically, the U.S. continues to hum along. International, even though the messaging business is going through some tough comps internationally right now, continues to perform pretty well. And then, yeah, I think we've seen pretty good resilience and durability by use case. and Verify, if you want to use that as a proxy for the authentication business, that continues to be one of our faster-growing add-ons. It's also one of the larger add-ons that we sell that continues to see really healthy adoption in a variety of different industries, not just regulated verticals like FinServe and healthcare. The marketing use cases continue to hum along. Notifications are pretty steady, Eddie. The one new thing or maybe two things that we saw in Q1 that stood out, But we did see a much stronger seasonal recovery. Q1 is typically a seasonally slower period for us, especially coming off that holiday shopping season. The bounce back that we saw in Q1 was a bit stronger and a bit faster than we typically see, which was great to see. And again, not necessarily isolated into any one area. But we have also begun to see the AI natives leaning into the messaging channel as well. Now, that's mostly for traditional Twilio use cases, notifications, 2FA. Way out at the margin, there is some experimentation beginning with 2A use cases. That's not really a growth driver today, but that is, again, if you're going to have conversational experiences with your consumers, a good number of folks want to communicate via the messaging channel. And so that's something that we think is a possibility over time, especially with these newer features that we just launched.

Is RCS and WhatsApp, does that move the needle, or are they pretty small?

They're still pretty small. Both are growing very quickly. They both pale in comparison to the size of SMS still today. you're still making some trade-off every time you move from SMS to those channels they're not as ubiquitous WhatsApp in particular you have to find markets where you have good agreement between businesses and consumers that yes we should all be here in most markets everybody wants to use WhatsApp or peer to peer in a lot of markets businesses would love to use WhatsApp as a business messaging tool in very few markets do both of them want each other there Brazil is probably one of those exceptions where there's there's there's an incredible ecosystem around WhatsApp for business messaging and business calling. So that business has done well. RCS, it's a similar story, but it is carrier enabled. And it comes with a lot of added benefits that have been native to WhatsApp for some time, branded capabilities, richer media. I do think some of those things, if you're going to scale two-way use cases, are table stakes. I'm much more likely to text back and forth with a business that I recognize with a logo and a name than a random shortcode or a random toll-free number. But it's still very early days. I mean, the carrier support continues to come online. Handset support, if you're on a very old iPhone, you still can't receive RCS messages. So there's a hardware cycle element to it. But we are beginning to see those volumes grow pretty materially, albeit off of a very small pace.

And you mentioned seasonality before.

I mean, just can you remind us, like, other seasonal factors that tend to happen throughout the year and q2 q3 q4 i mean q1 and q4 have the most pronounced ones q1 tends to be seasonally slower you know but but it's because of what happens in q4 uh around the holiday shopping season there's a lot of activity for obvious reasons we tend to see you know pretty sharp acceleration in volumes around cyber week so black friday cyber monday you usually sustain some degree of elevation through the holiday through the christmas holiday and then towards the end of the year you see volumes fall off a little bit as kind of businesses and consumers go their separate ways and then a recovery as you move through Q1 and so that's like the most consistent seasonal pattern that we see. We get asked a lot about cyclical events like political comes up very frequently. That's been a smaller part of the business over the last several cycles. The bar that we set for customers to be on our platform is very high. We have an acceptable use policy. You have to get opt-ins. And so if you are in the business of sending political messages and you follow all the rules, you can be a Twilio customer. There just seems to be a lot of traffic that doesn't want to follow those rules. And so we made a decision years ago that we would, number one, force customers to register all their messaging traffic, and then number two, hold them to that. And so I wouldn't expect political to be a material factor in this particular cycle, also in part because the rest of the business continues to grow and and as a percentage of the mix it'll just get smaller over time yeah but we do have midterms we do have midterms for better for worse um okay i on a to p i mean the new carrier fees you guys historically haven't seen any kind of loss of demand with with um prices that go up that you guys pass through um is that the you know kind of think that the same thing's happening with this cycle clearly yeah I mean we I think we've heard more from customers in this particular cycle than maybe in previous ones I mean look nobody likes price increase which effectively is what this is now all of our customers recognize it comes from the carriers we've heard more noise about it we haven't actually seen any behaviors change yet though you know we're but we're also not naive to the fact that this is a supply demand equation at some point if prices go high enough businesses in particular small businesses may have to think about how to deploy what our pretty rigid budgets as effectively as they possibly can. That's where having the breadth of challenge that we have is so critical. So if you want to maybe deploy some of those dollars to WhatsApp or to email, or if it's a use case that may have some benefits in moving to voice, we can obviously help you get there. And that's been a consistent line of communication between our sales teams and our customers. So we know that potential is always out there. But again, see above. That's why the breadth of the platform that we have is so critical, so that customers can find high ROI avenues to deploy this spend. And I'd say it's maybe a bit more focused on marketing, which has more discretionary elements to it, although customers use us for performance marketing with existing customers typically. It's maybe a bit less relevant for account notifications in 2FA, where if that six-digit passcode is what's staying between me and transacting, it's a trivial price to pay to get me authenticated safely. Or similarly, if United is sending me that text message saying, hey, you were at gate C100, now you're at gate C1, you better get moving, otherwise you're going to miss your flight. They can't run the risk of that not getting delivered, and messaging is still the most effective place to get there. But that is something that we hear, and we're pretty adamant about educating customers about the other channels that we can provide. And the new console should help, right? I think the new console will help in a variety of ways. I mean, number one, the ability to experiment in all of the channels is so much simpler. If you're a brand new to Twilio customer and you've never experienced the console before, you now have an overhauled trial credit system where you can deploy trial credits across all the channels if you so choose. You can get comfortable with how you might orchestrate conversations and workflows between various different channels. The add-ons are all right there for you. We've simplified the error code, so if you run into a problem, an AI assistant is right there on the dashboard to tell you what that error code means and what the resolution steps are. so there's no more, you know, you're eight clicks away from resolving your problem because you have to go to the help center, engage an assistant, maybe submit a ticket. That's all being done right there in the new console. And you also now have much better visibility into your usage telemetry and your billings, which was a frequent pain point. So the ability to get up and running in multiple channels and consume our add-ons has never been easier in self-serve. And having visibility into what you're doing has also been leveled up dramatically. All right, great, amazing. Great conversation.

Thanks. We're out of time. Thanks, everybody.