Verint Systems Inc.

Thank you for standing by, and welcome to VARNT's first quarter fiscal year 2025 earnings conference call. At this time, all participants are in a listen-only mode. After the speaker presentation, there will be a question and answer session. To ask a question during the session, you will need to press star 1 1 on your telephone. To remove yourself from the queue, you may press star 1 1 again. I would now like to hand the call over to Matthew Frankel. Investor Relations and Corporate Development Director. Please go ahead.

Thank you, operator. Good afternoon and thank you for joining our conference call today. I'm here with Dan Bodnar, Varun's CEO, Grant Highlander, Varun's CFO, and Alan Rhodes, Varun's Chief Corporate Development Officer. Before getting started, I'd like to mention that accompanying our call today is a slide presentation. If you'd like to view these slides in real time during the call, please visit the IR section of our website at varun.com, click on the Investor Relations tab, and click on the webcast link and select today's conference call. I'd also like to draw your attention to the fact that certain matters discussed on this call may contain forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995 and other provisions of the federal securities laws. These forward-looking statements are based on management's current expectations and are not guarantees of future performance. Actual results could differ materially from those expressed in or implied by these forward-looking statements. The forward-looking statements are made as the date of this call and as accepted as required by law, VARIN assumes no obligation to update or revise them. Investors are cautioned not to place under reliance on these forward-looking statements. For more detailed discussion of how these and other risks and uncertainties could cause VARIN's actual results to differ materially from those indicated in these forward-looking statements, please see our Form 10-K for the fiscal year ended January 31, 2024, our Form 10-Q for the quarter ended April 30, 2024, when filed, and other filings we make with the SEC. The financial measures discussed today include non-GAAP measures, as we believe investors focus on those measures in comparing results between periods and among our peer companies. Please see today's slide presentation, our earnings release, and the investor relations section of our website at burn.com for a reconciliation of non-GAAP financial measures to GAAP measures. Non-GAAP financial information should not be considered in isolation from, as a substitute for, or superior to GAAP financial information. but is included because management beliefs provide meaningful supplemental information regarding our operating results when assessing our business and is useful to investors for informational and comparative purposes. The non-GAAP financial measures this company uses have limitations and may differ from those used by other companies. Now, I'd like to turn the call over to Dan. Dan?

Thank you, Matt. I'm pleased to report that our strong momentum contained in Q1, driven by the strong AI business outcomes, that our open platform delivers to our customers. The variant open platform that we introduced last year transforms the latest AI technology from any vendor into tangible AI business outcomes better than any other contact center platform. And because the platform is completely open, we're able to quickly deploy AI-powered bots into a customer's existing workflows accelerating their time to value. In Q1, revenue and non-GAAP diluted EPS came in ahead of our expectations, and we are raising our annual guidance. We believe the AI opportunity in the contact center market is very large, as brands seek AI-powered bots to help increase CX automation. The market is starting to pivot from telephony-centric to AI and data-centric platforms, and Variant is very well positioned to lead the new CX Automation category with our differentiated open platform. Contact centers have been challenged for many years to hire more people and deliver higher quality customer experiences. Today, contact centers seek a CX Automation platform that is centered on behavioral data and AI to deliver increased workforce capacity and lower labor costs, while at the same time elevating customer experience without additional headcount. More and more brands are seeking a CX automation platform that can deliver tangible AI business outcomes. At our investor day last year, we discussed several examples of how variant bots are helping our customers to reduce costs as well as driving faster growth for variants. For brands, the economic benefits from AI business outcomes results from the lowering the cost of their workforce and increasing customer loyalty. At the same time, for variants, the economic benefits come from increasing our addressable markets as brands increase their adoption of variant AI-powered bots. Our momentum continued in Q1, and later I will review Q1 large wins driven by AI-powered bots and customer case studies demonstrating the strong AI business outcomes we are delivering to our customers. Next, I would like to review our first quarter results and trends. In Q1, revenue came in at $221 million $7 million ahead of our guidance. Our strong innovation continues to drive gross profit growth faster than revenue, and non-GAAP gross margins expanded 260 bps compared to the same quarter in the prior year. Non-GAAP diluted EPS came in at 59 cents, 5 cents ahead of our guidance, and an 11 percent year-over-year increase. Our SAS metrics also came in strong, and Grant will discuss our Q1 results in more detail later. As I mentioned earlier, Variant quickly transforms the latest AI technology into tangible AI business outcomes better than any other contact center vendor. Our open platform is highly differentiated from telephony-centric platforms due to its unique design with behavioral data and variant DaVinci AI at the platform core. Variant DaVinci acts as the factory for our bots. It leverages the latest commercial, open source, and proprietary AI models to quickly deploy new bots and refresh existing bots. As variant bots emerge from the bot factory, They train continuously in the bot gym on relevant behavioral data available in the Verne platform data hub. And finally, the Verne bots are designed to leverage the same workflows our customers use every day, enabling brands to quickly deploy bots and benefit from AI business outcomes now. Our ability to deliver strong AI business outcomes is reflected in our Q1 momentum, including competitive wins for many of the leading brands in the world. During Q1, we had strong SaaS bookings driven by customer adoption of our AI-powered bots. As a reminder, our bots are only available as bundle SaaS running in the very cloud. And our new bundle SaaS ACV bookings in Q1 came in strong with 25% year-over-year growth. Some of the large wins that we recently announced include a $14 million win for one of the world's largest retailers, which I will discuss in more detail shortly. A $7 million win for Fortune 500 brand, a leading healthcare company adopting four variant bots. a $7 million win for an insurance company, and a $4 million win for a leading health care provider, both adapting variant bots. And finally, a $4 million win for a top five US bank, which is an initial order covering about 12% of their contact center operations, with a fully negotiated option to expand volume. Let's take a closer look at the eight-digit win in Q1. This large retailer is deploying the Variant Open Platform in the cloud to increase CX automation in their contact center. Variant was awarded the $14 million contract due to our differentiated ability to deliver AI business outcomes now. The contract includes deployment of four Variant AI-powered bots. The data insight bot, which enables users to engage in AI-assisted conversations with their data by leveraging multiple AI models to answer natural language questions and to automatically identify anomalies and trends in the customer's data. The transcription bot, which delivers market-leading transcription accuracy, resulting in improved analytics and higher impact for business insights. The Quality Bot, which automatically evaluates customer interactions, resulting in reduced supervisor costs and improved agent coaching. And the Data Reduction Bot, which automates data compliance and protects sensitive personal data. In addition to deploying these four bots, we're also replacing several legacy solutions from two competitors and helping the customer to consolidate dozens of data silos into a single unified data hub, which is critical to the ongoing training of the bots. The Variant Bots are designed to deliver specific AI business outcomes. As customers increase their Variant Bot adoption, they are reporting significant AI business outcomes. Let's take a look at three such case studies that we recently announced. The first case study is a financial services company deploying variant bots to increase self-service containment across 14 million interactions annually. The customer deployed the variant IVA and achieved a successful containment rate of 80% by the variant bot without human agents. This impressive market-leading containment rate drove significant agent capacity. And the extra capacity is being used to extend service hours, to elevate customer experience, and to lower labor costs. The second case study is an insurance company deploying Variant Bots to increase agents' work-life balance by providing agents unlimited schedule flexibility. The insurance company deployed the Variant TimeFlex Bot and saw a 30% reduction in agent attrition. The third case study is a bank deploying Varianbots to help agents improve their upsell skills and increase revenue. As one starts to benefit from increased agent capacity through AI, many are now looking to leverage their agents for additional tasks, such as upselling and increasing revenue. With the various coaching bots guiding the contact center agents in real time on how to effectively sell to customers, the banks saw a 48% increase in upsell close rates. This is an example of how brands are able to leverage increased agent capacity to drive higher revenue. In summary, we're pleased with our large wins in the first quarter. including some of the leading brands in the world selecting variant open platform. We're also pleased with the significant AI business outcomes reported by customers using the variant AI-powered bots. The key driver behind our momentum is our ability to deliver AI business outcomes now, and we believe this is a unique and sustainable differentiator. We expect AI technology to continue to evolve at an even faster pace, as evidenced by frequent Gen AI enhancements from leading AI vendors. But Gen AI models alone do not create AI business outcomes in the contact center. For that, a CX automation platform such as ours is needed, which can combine AI models in a bot factory train these models on fresh, relevant data 24-7, and then embed the AI into existing contact-centered workflows. Variant is benefiting from the fast pace in AI innovation and adoption in the industry. The Variant Open Platform was launched mid-last year, and it's driving a recent momentum, positioning us well to lead the new CX Automation category. Today, we are raising our revenue and non-GAAP diluted EPS guidance for the year. As discussed at our investor day, we're targeting an acceleration in our revenue growth rates to 10% in fiscal 27, consistent with our rule of 48 target. With that, I'll turn it over to Grant to discuss our financials in more detail.

Thanks, Dan. Good afternoon, everyone. Our discussion today will include non-GAAP financial measures. A reconciliation between our GAAP and non-GAAP financial measures is available, as Matt mentioned, in our earnings release and in the IR section of our website. Differences between our GAAP and non-GAAP financial measures include adjustments related to acquisitions and divestitures, including fair value revenue adjustments, amortization of acquisition related intangibles, certain other acquisition and divestiture-related expenses, stock-based compensation expenses, accelerated lease costs, IT facilities and infrastructure realignment, as well as certain other items that can vary significantly in amount and frequency from period to period. Let me start with an overview of our strong Q1 results. Adjusted revenue increased 5% year over year to $221 million, $7 million ahead of our guidance. As a reminder, our 5% adjusted revenue growth reflects the quality managed services divestiture we completed at the end of last fiscal year. When looking at the $7 million overachievement, about half was due to contract values coming in higher than anticipated And the other half was due to contracts closing earlier than planned. Non-GAAP gross margins came in strong at 72.4%, up 260 basis points year over year. We are pleased with our gross margin and believe our ability to increase gross margins reflects the strength of our AI innovation and the AI business outcomes we deliver to our customers. The combination of our revenue overachievement and strong gross margin drove non-GAAP diluted EPS of $0.59, $0.05 ahead of guidance, and up 11% year over year. Our strong first quarter results were driven by our continued SAS momentum. In Q1, SAS revenue increased 20% year over year. Bundled SAS new ACV bookings which is a leading indicator for AI momentum, increased 25% year-over-year, as 80% of our bundled SaaS bookings were contracts that included AI-powered bots. It's important to note that many of our customers initially purchased bots for a portion of their potential AI volume, and our flexible consumption pricing model provides Verint a natural path for revenue growth as brands increase their consumption of our bots. Another SAS metric that relates to AI adoption is term length. In Q1, I am pleased to report that we saw our average SAS contract term length about 30% longer than a year ago. We believe these longer term lengths reflect growing customer confidence in the direction of our open platform and commitment to Variant's CX automation strategy. A third SAS metric related to AI momentum is bundled SAS pipeline. As of the end of Q1, our advanced stage pipeline for the remainder of the year was up more than 20% year over year, with over 80% of the pipeline including bots, reflecting the fact that our AI innovation is only available in the VARIC cloud. Our other SAS metrics were also strong across the board and can be found on our IR dashboard. I would like to talk more about our AI business outcome strategy with our large customer base. Today, Verint delivers workflows to about 4 million contact center agents. As discussed at our investor day, we are enhancing these workflows with AI powered bots, which expand the Verint revenue opportunities significantly. To monetize this opportunity, we offer our customer base a hybrid cloud architecture enabling them to quickly deploy Barron's latest AI innovation in our cloud without the need for large, disruptive, and risky rip and replace programs for their existing systems. Also, our flexible AI consumption pricing model enables our customer base to deploy bots at low volumes initially, and then easily expand as they prove the value from the AI business outcomes we deliver. We also provide our customers future-proof pricing strategies that allow them to redirect investments from agent-based applications toward investments in AI-powered bots. We see customers in our base increasing their agent capacity with AI-powered bots and using the extra capacity in multiple ways to elevate customer experience, to eliminate hiring, to empower agents with upsell offers, and to reduce labor costs. We believe our ability to deploy bots with a flexible consumption model will enable us to accelerate our revenue growth as strong AI business outcomes drive more adoption of our bots and a greater volume consumption by our customers. Turning to our guidance for fiscal 25, Given our strong start to the year, we are bumping up our revenue and EPS guidance for the full year. On a non-GAAP basis, our revenue outlook for fiscal 25 is now $933 million, reflecting a bit more than 5% growth compared to fiscal 24 adjusted revenue. We expect gross margin to increase again this year, and we are raising our gross margin expansion guidance from 100 basis points to approximately 150 basis points year over year. The combination of revenue growth and continued margin expansion is expected to drive operating income up high single digits for the year faster than our revenue growth. And for diluted EPS, we now expect $2.90 at the midpoint of our revenue guidance. Regarding below-the-line assumptions, we expect interest and other expense net to average around $500,000 per quarter, net income from a non-controlling interest of around $250,000 per quarter, and for the full year, we expect a cash tax rate of around 12% and around 72.5 million fully diluted shares. Let me also discuss how we see the year progressing. We expect bundled and unbundled SAS dynamics to be similar to last year. For bundled SAS, we expect revenue to increase sequentially throughout the year. In fact, we expect our bundled SAS revenue growth rates to accelerate each quarter on a year-over-year basis. For unbundled SAS, we expect the quarterly cadence of revenue to be similar to last year, driven by the timing of unbundled renewals. For Q2 total revenue, we expect a range of $210 million to $214 million, reflecting a sequential increase in bundled revenue to more than $70 million driven by AI adoption, a lower amount of unbundled SAS revenue compared to Q1 driven by the Q2 volume of renewable contracts, and a sequential decrease in non-recurring revenue and support as expected. For EPS at the midpoint of the Q2 revenue range, we expect non-GAAP diluted EPS to be 52 cents. Looking at the second half of the year, we expect revenue in Q3 to be similar to Q2 and to finish the year with a strong Q4 driven by both strong bundled SAS growth and a large volume of unbundled renewals similar to last year. Turning to our balance sheet, we continue to be in a very good financial position. Our net debt remains well under one times last 12-month EBITDA and is further supported by our strong cash flow. With regard to cash flow, we are targeting a greater than 40% increase in pre-cash flow to approximately $180 million for the full year. As we previously discussed, our largest use of cash generation is expected to be stock buybacks. In Q1, we purchased approximately $37 million of shares of common stock. And in Q2, we will continue buying back shares as part of our previously announced $200 million stock buyback program. In summary, We are pleased to have exceeded both our revenue and non-GAAP diluted EPS guidance in Q1. We are pleased with our strong bundled SaaS bookings growth, large wins with some of the world's leading brands, and significant AI business outcomes reported by our customers. As we discussed today, VARENT's AI-powered bots deliver economic benefits to our customers and also to VARENT. We are focused on accelerating the deployment of AI-powered bots to our large customer base. And finally, we are pleased to raise both revenue and EPS guidance for the current year as we work towards becoming a Rule of 40 company in fiscal 27 with revenue acceleration and margin expansion along the way. With that, operator, please open the line for questions.

As a reminder, to ask a question, you will need to press star one one on your telephone. To remove yourself from the question queue, you may press star one one again. Please stand by while we compile the Q&A roster. Our first question comes from the line of Shaul Eyal of TD Cohen. Please go ahead.

Thank you. Good afternoon, gentlemen. Congrats on the beaten race. Dan, I want to ask the recent string of sizable contract announcements. Look, I've been covering this name for decades now, and I cannot recall the pace or even the amount, the number of sizable transactions that have been announced just over the course of the past few weeks. What's driving that? Is that pure demand? Is that Gen AI resonating with customers? And maybe if I can also squeeze in just a macro level question. We've been getting, maybe I should say, mixed views about the macro within the software arena. How do you see the current macro environment? Thank you.

Thank you, Sho. I'll answer the first question first. So yes, we do have momentum, and I believe these large deals represent confidence and commitment to our strategy that we see from customers. First, it's important to note that we've announced large contracts from world-leading brands. So they are leaders in their segments, and they are basically endorsing our open platforms. It is not just the size of the contract, but these are leading customers choosing Variant as the core platform in the contact center. And being the core platform, in addition to buying bots, which is obviously a focus, they're also consolidating solutions from other vendors into the variant platform. So part of this announcement is displacement, and part of it is bot expansion. The second important thing about this announcement is that these customers are, again, they're large, they're complex, and they want to adopt bots, but they're also not so interested in the AI technology. They are interested in AI business outcomes that are delivered in the Connect Center. So you can see from the announcement they deployed different bots. Each one is choosing the bots that are right for them at this point in time, and the platform is open and modular, so they can choose the bots that make sense based on their business priorities. But also I think we mentioned that they're using a relatively low consumption at the beginning and what they want to do is they basically want to prove the AI business outcomes and then they increase the consumption over time. So they don't have to come up with all the budgets up front. We are an open platform so we are flexible. They don't have to commit to a very large reap and replace project. They can do it on a more, you know, the pace they like. And as they deliver the outcomes, they will pay for themselves. So what we hear from these customers is, you know, they'll be able to get more budgets and continue to increase consumption if they're able to save cost for labor and for extra agent capacity. So second question was around the macroeconomics in Q1. So for us, Q1 was a strong quarter, basically across all key metrics, including leading indicators. So booking for SaaS, bundle SaaS was 25% up. Very important that we saw an increase of term length by 30%, which means customers are committing for longer term as they buy into the Verden strategy, not just buying product. And we also had the bundle SaaS pipeline for the remainder of the year is also up more than 20%. And that's where our AI innovation is in the bundle size. And of course, that's where we generate the AI business outcomes that customers are looking for. So if I have to kind of assess the customer sentiment in Q1, I would say customers are focused on AI business outcomes. And these outcomes generate significant ROI. So they're willing to invest when they see the benefit and they see greater economic benefits than the investment. And while customers are being more cautious about investing in software, they clearly want to invest in tangible business outcomes now. So Ferentz is well-positioned to do both. First, we're well-positioned to deliver strong AI business outcomes, but I believe also we can deliver them now with quick time to value based on the design of the open platform.

Thank you so much.

Thank you. Our next question comes from the line of Joshua Riley of Needham.

All right. Thanks for taking my questions and nice job on execution here in the quarter. Maybe just starting off, can you help us understand, you know, as AI is increasingly maybe accelerating is the right word in terms of adoption in the contact center, What are you hearing from customers in terms of their plans to slow contact center seat growth or ultimately reduce seats? And are you finding that the comment about time to value is actually accelerating here? Is that actually leading customers to come back and buy more sooner than you would have expected previously?

Yes. So first on the agent count, So when we look, we looked obviously at the end of the quarter at our customer base, and we didn't see a decline in the number of agents. But we also do see customers are increasing the consumption of bots, so they create agent capacity. And this extra capacity at this point is mainly used to avoid hiring. Many of our customers have been on the outlook to hire, which is not easy, and they didn't have the budget necessarily, so they now use the capacity to avoid hiring. They also are giving agents, in some cases, more time, so they can increase the customer sentiment, improve customer experience. And we're starting to see also a fairly new thing, which is giving agents new tasks that they didn't have before, such as increasing revenue, so upselling, offers to customers after they deliver the positive experience. And one of the business outcomes that I highlighted that I thought was very interesting, I had that before, was a bank that actually did have extra capacity, you know, tasked their agents to sell, but they found that the agents are not really very good at selling. So they actually used a very coaching bot to improve the sales performance and they achieved 48% increase in sales by those agents. And this was done by the AI basically telling the agent what is the best time during the call to offer something, matching the offer to the customer, so it's more specific about the customer history and preferences. And also very interesting is that the coaching bot was suggesting to the agents what language they can use to overcome objections for sales. And of course, you know, there's a lot of different ways to approach customers and get them to be interested when they actually originally called not for buying anything but for resolving an issue. So I think that... you know, as an industry, we'll see a lot of different usage for the extra capacity. But I think that, as you mentioned, there is growing interest in creating AI business outcomes. And customers don't really want to consume AI and pay for tokens. But they are very happy when we sell them based on a unit of measure that they can, you know, connect the return on investment directly with the bot consumption. and this creates a significant saving. The Timeflex bots reducing agent attrition 30%, that's millions of dollars for a large contact center. It's very expensive to hire and train agents and of course it's not just reducing the attrition but also improving the engagement by employees and morale. So there's a lot of different benefits and we think the industry is just starting to realize how they're going to use that benefit. And not every customer is just running to reduce the number of agents. They're mostly looking at how they can use their human agents more effectively and augment those used agents with more and more bots.

Got it. That's super helpful. And then just on the unbundled SaaS growth, clearly above what we expected for the quarter. Can you just help us understand what is driving the greater than expected activity with partners? Is it a few big deals that came in? And maybe help us understand the magnitude of the deals that were pulled forward here for the unbundled revenue. Thank you.

Yeah, so when we launched the platform, we talked about it's a hybrid cloud platform. And hybrid cloud meaning that you can actually have part of the solution of the platform running in unbundled and other running in bundled. So all our AI innovation is in the cloud, so customers have to buy that in bundled. But many of these large products are now having both unbundled and bundled in the same order. And many, many customers are now having this type of hybrid platforms. And with that, you know, I actually, this has overachieved my expectations in terms of customer reaction. because typically the Connect Center vendors are approaching customers and they all have one message. You have to reap and replace everything and start over again in the cloud. Verint came with the opposite message. Keep what you have. If you like it, if it's working, just keep it and add AI right now. The problem with reap and replacement is not just that it's a long and risky project, but you also delay the innovation, the AI innovation. The idea of AI now, you have to really deploy it on a small scale basis and have it work with your existing ecosystem. And this is what Variant does. So many of these customers actually kept their telephony on-prem. They kept Variant applications and other applications from other vendors on-prem. There's no dependency. They can move to AI innovation now with putting bots in the cloud. And the way that works is that because we gave them that flexibility, they also felt more comfortable to expand on-prem. And that's why we have an increase in unbundled and that's why we were able to close deals earlier and actually get larger deals on unbundled because they're comfortable that they don't have to throw it away. They can keep it as long as they want and when they feel it's the right time, they can convert the legacy to bundle SaaS But that doesn't slow them down because they already have bundled SaaS invariants with AI, you know, generating business outcomes now.

Got it. That's helpful. Thank you.

Thank you. Our next question comes from the line of Stephen Raftick of Wedbush Securities.

Hi, this is for Dan and I. Thanks for taking the question, and congratulations on the great quarter. I just wanted to talk a little bit about the competitive landscape that you guys are seeing, because you talked a little bit about how you're replacing a bunch of legacy vendors in the quarter with the AI chatbots. But how would you describe the competitive landscape of what you're seeing right now, and what are your expectations over the next 5 to 12 months?

So we see today in the CX automation market, and this is how we refer to the market, but there are basically two sets of competitors. There are telephony-centric competitors with telephony-centric platforms, and there are AI and data-centric platforms. So what customers really look for, they focus to shift to vendors that can deliver AI business outcomes. Customers are less interested in the technology and much more in what is the business outcome that you can actually deliver now. So I think there is a growing realization that telephoning the cloud does not generate AI business outcomes. But we see, obviously, telephony vendors trying to catch up with data and AI. in their platforms. And then, of course, there's variants. From the get-go, we put data and DaVinci AI at the core of the platform. So we are now really able to innovate very, very quickly. And we also, not just because the platform is open, we're bringing any innovation from the high scalers. So they generate new Gen AI models. They are in our platform within days. And we test them, we vet them for cost performance. We train those models on the data that we have in the platform. We embed them into the existing workflows that we deliver to our customers. So we're able to very, very quickly turn the latest and greatest AI models into more powerful bots. So I think that that's really impressive to our customers. It's not so much the PowerPoints. There's lots of Almost every vendor today in the market is talking about AI, but it's really the design. Is it more telephony-centric with AI attached, or is it very data and AI-centric and a focus on quickly delivering AI outcomes without rip and replace, without the need to go through a complete overall of your infrastructure before you can actually get AI to work for you? so um you know the question is where this market is is going uh there's a very fast pace of uh ai innovation so clearly i think the market is going to open platforms uh open is resonating very well with our customers and and you know we have very large customers so open is very very important it's uh perhaps less important in the smb space today uh but i think The leadership we see from the top guys is open, allows them to future-proof their investment. They're not really just buying features and functions, they're buying a platform that can bring any innovation in AI technology quickly. Again, the data is critical. When I talked about the $14 million deal, One of their big focus was they have several dozens data silos. They can't train the bots with so many data silos. Very, very big initiative was IT started to consolidate all these data silos and it became a very long data architecture project. We came in with the platform and we have adapters. We could bring all these data silos to Unified Data Hub quickly. and then of course gets the bots to continue to train and become more and more accurate and effective. So this is where the industry is going, right? It's open, it's being able to future-proof AI investments so you don't get stuck with an AI model that can be stale in six months. It's bringing data together that is critical not just for today, but for any AI innovation to have the right data available. And, of course, it's an open platform where you can choose what you need so you're not doing big projects for the sake of changing ecosystem, but you really are being able to, on a modular basis, solve one problem at a time.

Great. Thank you.

Thank you. Again, to ask a question, please press star 11 on your telephone. Again, that's star 11 on your telephone to ask a question. Our next question comes from the line of Samad Samana of Jefferies.

Hey, guys. This is Billy Fitzsimmons on for Samad. Looking across the headlines over the past several weeks, obviously a lot of large wins as we've talked about, but maybe just to double-click on this, Dan, can you walk through some of these deals at a high level? Who did you displace? What was the mix of expansions versus net new wins? What got these deals over the finish line? Bots obviously played a big role, but any specific bots or product that you think had an outsized impact? And then I'll also throw in there, just to be crystal clear, Dan, you're pretty clear you did not see or have not seen seat declines. Maybe in a different way, has the mix of seat expansions versus ARPU uplift changed materially with some of these recent large deals compared to maybe large deals in years prior? Thank you.

Yeah, so if you look at the common threads of all these deals, it's focusing on AI business outcomes now. In some cases, when we look at some of these deals that were competitive with an RFP, you would assume that all the players, all the success players were there. And typically today, customers can get five to 10 different responses from different vendors, because a lot of vendors are trying to play in this market. So, in most cases, what caused the customer to move away from the traditional SICKUS approach to variance was a message of AI business outcomes now. So that's how we start, and that's where we get the customer's attention. Now, the big discussion following that is what business outcomes they actually want now. And you can see different customers are focusing on different pain points. Because the platform is completely open and modular, we're taking a consultative approach with customers. We're not trying to dictate that you have to do X before Y and then Z. but we're trying to understand what they're trying to solve and we have a bot, uh, to solve it. So we usually start with, you know, one, two, three, four bots. And then we go into a discussion of what is the volume that you want to consume initially. And that's a budget issue. So if they have a big budget, uh, they will buy, you know, all the consumption upfront, but in most cases they buy, you know, 50%, 25% of their potential consumption. because they have limited budget and they know that as they deliver the outcomes, they're gonna get more budgets because they're gonna see the cost deduction and it's gonna be easy for them to go and get new budgets when the product pays for itself. And remember, a bot, we sell them on a, you pay for what you eat, and it's not based on API calls or tokens, it's based on you need to measure metrics that kind of certain people can measure. So, once we kind of agree on which bots they need, what level of consumption, then, you know, the conversation will pivot to, okay, but we don't have all the data we need, so we can expand also in the platform to consolidate more data silos for them, because the more data you have in the variant platform, the more powerful the business outcomes become. The boss becomes just much more accurate. In some cases, like I mentioned before, it will be while we're doing this, here are one or two solutions from competitors we don't like. So why don't we just consolidate? We're not necessarily asking the customers to consolidate. We focus on delivering new AI business outcomes, but In these large projects, very often they also decide they just don't like a vendor and this could become part of the deal. So that's kind of typically what we see customers love. They're not forced to convert to the cloud, the legacy stuff. They all love it. And they really can focus their budget and energy on getting new stuff and not doing infrastructure overhaul projects. In terms of, you know, the second part of your question was related to what we see with the agents. I would say that, you know, most of our customers feel like they are behind in terms of hiring. And they know that, you know, they're not giving their employees the flexibility. They're not giving their customers the experiences. So I think the industry right now is in an early stage where they are trying to augment agents, but are not looking to reduce the number of agents. When we look at our base, we don't know what customers are really doing with their agents. We have agent count, but I'll give you some interesting things that are going on. because of the flexibility of the platform. So we have an airline that have employees that are at the gate, and when the flight is delayed, they are sending these employees contact center work, because they have extra workforce capacity at the gate, and why not? They may have two hours that they can just respond to some customer questions. And it doesn't have to be voice calls, right? It could be chats or social media calls. So our platform has a lot of flexibility to use the human workforce across the comic center branch and back office. And at the same time, we see our customers are scheduling bots because they're looking at the workforce as a larger workforce of people and bots. And the more they have bots, it becomes more of a natural part of the work is to decide what kind of capacity they have between people and bots and how they allocate the capacity to the call volume that they expect. So this is all new thinking. I don't think I can report right now a very clear trend of what customers are gonna do with the capacity that has been created by AI. But I can say clearly that when we talk to customers about AI business outcomes, they all focus on, okay, that's going to give me extra capacity and here's what I'm going to do because that's how they actually build their ROI models.

Awesome. Super helpful, Keller. Thank you very much.

Thank you. I would now like to turn the conference back to Matthew Franco for closing remarks. Sir?

Mr. Franco, your line is muted. I think we're done. Lateef, can you hear me?

Yes, go ahead, Mr. Franco.

Oh, all right. Sorry about that. Thank you everyone for joining. I was just saying, please feel free to reach out with any questions you have and we'll look forward to talking to you again soon. Have a good night.

Ladies and gentlemen, this concludes today's conference call. Thank you for participating. You may now disconnect.