We're an AI here at Cantor, and we're very happy to have Nitesh here, the CFO of SoundHound AI. I would make a bet that a good chunk of you here in the room are absolutely familiar with SoundHound. You might know a couple of things they do conversationally, but maybe I'll just give maybe a one-minute intro for you and Nitesh that would help us kind of level set before we jump into all the questions about what SoundHound AI is doing for the market. Sure. Thanks for having me, Tom. Glad to be here. SoundHound is a conversational AI and voice AI leader. We've been a pioneer in the space for over 20 years. Our founders built this company with the vision of voice enabling the world with conversational intelligence. Did the PhDs at Stanford, pre-iPhone days, in speech recognition and machine learning, and have built a proprietary stack. We're one of only a handful of companies in the world that own all the pieces, parts of the voice AI tech stack from a software perspective. We think that gives us competitive differentiation because we can innovate quickly, we can modernize, and we've been growing rapidly. We announced our earnings just 10 days ago. We're really trying to disrupt the world and bring a new horizon of how humans interact with technology. I know we'll talk a little bit further, but every 15 years, 20 years, there's a new major inflection in technology. We think we're in the middle of them. We think this is the Gen AI LLM era. Within that, we think this is going to change how humans interact with technology rather than just a keyboard input or a touch-type swipe on your phone. Humans will be able to do a lot more interacting with technology through natural conversations and just conversing how we're doing now, how humans have done it for their history, tens of thousands of years. Within that world, we think voice AI is the killer app, and that's what we've built over time. We have many applications across products, automotive, in the services space with restaurants and financial services and healthcare. We are building an ecosystem of monetization and voice commerce to connect voice-enabled product with voice-enabled services. Yeah. That is a great overview for a relatively complex company in the sense that you do cover a lot of areas. I like the analogy that you talk about with conversational search, even comparing your company sometimes to Google, which I think is interesting. You mentioned competition. We get a lot of questions from investors around how crowded is this market, who do you compete with. There is probably a number of different competitors because you do have this diverse model that we will get into, but maybe kind of help us understand who you are competing with and trying to win against. Sure. Yeah. Depending on the industry, application, and sort of pillar, we see different competitors. First, like I said, our differentiation is generally in tech. When we go head-to-head with competition, we generally win on the basis of better technology. We also have different go-to-market motions and different ways we partner. I'll kind of unpack a couple of these. First, where we got our foray, we launched, unveiled after 10 years in stealth, we launched our voice AI engine in about 2015, 2016. The platform first got a lot of attention from the automotive makers. Naturally, voice makes sense while driving. It's a safety issue. You want to keep your hands on the wheel. There was one major player. It was Nuance for many decades who was a leader in the ASR speech recognition space. They spun off a public company, Cerence. In automotive, that's who we've been stealing share from, frankly, over the last several years. They came in with edge solutions, meaning they did it in-car without internet connectivity. You can turn up the volume, turn on the AC, open the windows type of thing. We got traction with cloud capabilities. You can connect to maps and navigation and connect to what happened in the game last night or what's going on with the stock. We got entry and ultimately have been displacing them. We now have over 20 automotive brands that are customers of ours. We're continuing to scale across new players. We've gained a lot of traction with EV companies, which tend to operate at a greater speed and are more software-centric. We've been able to gain a lot of traction there. A lot of displacement with Cerence. There's also the Big Tech that play there. Our differentiation, number one, where when we go head-to-head, we have customer benchmarks that we do head-to-head better technology and better performance from sentence accuracy. How does the voice AI operate and understand? It's kind of more than Apple. Yeah. The other difference is we do it in brand centricity. We do white label. You can say, "Hey, Hyundai." You do not have to say, "Hey, Alexa." We have a broader suite of products. We, again, do edge, cloud, hybrid engines. That is where we have been playing. That is the automotive space. When you get into IoT, it is really much more nascent. There are not many players. It is a lot more greenfield. When you get to services and restaurants, also pretty greenfield. There are some legacy players, private companies you may not have heard of, some call center players. Really, technologically, when you see one of the ways that people measure success, customers, is when I order something in a drive-thru or phone ordering, how successful am I at completing that order? Order accuracy. Humans, we know post-pandemic, actually, there's been deterioration in even human quality. You might drive into a drive-thru and say, "I want cheeseburger, whole pickles," you'll still get pickles. You might say, "I want French fries," you'll get onion rings. That happens. We say humans are about 85% accurate. Our technology, purely AI, in many cases, is exceeding human performance. We go 85% out of the gate. We work with them for several months. We're 90%-95% accurate. On an AI to AI basis, we really do not see many equivalent players. There are some people who put a human, it is kind of Wizard of Oz and have a human there, and they will say they are 95% accurate. Ours is fully AI. We will have a human backdrop if needed or a fallback, but generally, it is greenfield. Now, one thing our co-founder and CEO, Keyvan Mohajer, says, I've always liked this line. It's, "Voice AI is hard AI. It is tough to build." We, again, 10 years in stealth, have been building on this for years and years. It takes 10 years to develop. It takes you 3 years to realize it takes 10 years to develop. We have seen that over and over again. We have actually investors in the company, major tech players who tried to do it by themselves for a while and then came in and partnered with us. Probably one of the most notable examples recently is McDonald's, who tried to build it in-house. They actually acquired some companies. They ended up selling that capability because it was too difficult to do it in-house to IBM Watson. IBM had a partnership and scaled to like 100 locations as a pilot. Recently, within the last six to nine months, all public information said, "Hey, we're going to stop this relationship, or we're going to look for voice AI solutions elsewhere." You see this happen over and over again. People are like, "Well, how hard can it be? Let me build it." It truly is hard. That is why many customers come to us solutions. I know I'm going long on the competitor answer, but one last play. That's important. I'll say we're getting a lot of traction in the enterprise side, financial services, and healthcare. There's some conversational AI players. We acquired a company last year, Amelia. It gave us footprint deeper into the enterprise stack, into these new verticals for us. One of the big things when we were diligencing the company, we have seven of the top 10 money center banks. The biggest thing they wanted to see was how do you move conversational text-based to voice. It was just a hard horizon where they were using third-party agents from the likes of Microsoft and Google. We came in, and we've been able to displace those third parties with our own solutions. For us, obviously, it's moving into our own stack. It's cost efficiency. It's speed benefit. Frankly, performance-wise, we're able to do a lot more and innovate. A lot of different players in the different verticals we play in. It's in early days in emerging space. We know more and more players will come in, but we think we've got a nice running start. I would implore the audience to go to the SoundHound YouTube videos where I, a few years ago, when I met this company, was impressed. It is truly better technology, at least from a usability perspective. Just double-clicking on the competition before we leave it is we're reading very recently about Alexa. Even I think Apple made an announcement this week about maybe double-clicking and doing some whole software uplifts in terms of conversational technologies. Do you think this could expand and kind of naturally acknowledge the market type of thing? Or do you think that this could change the competitive landscape from these big guys? Let me make a more broader point, and then I'll hit the specific question. Every, again, generation, there's some new major inflection in technologies. I mentioned at the beginning, we think we're in the new conversational, natural conversation era. Led the capabilities that LLMs are providing in terms of flexibility and capacity to hold conversations, very complicated conversations, just like how humans converse. This is a new era. This is where technology is shifting. Anytime you end these sort of brave new eras, there's going to be all sorts of new competition. Incumbent players in one space are going to try to get their footprint into it. I think that's a sign of a very healthy, attractive market. We welcome it. We compete head-to-head with many different players. I do think there's validation, absolutely. We see it in the restaurant space. We see it in the enterprise space. We see players who have traction in one part of the market saying, "Hey, this is where conversations are shifting. We want to make sure we're following track." I think that's a sign. Yes, there are going to be major players. Obviously, the companies with unlimited resources could spend unlimited amounts and could do a lot of things. I also will say, and I spent a large part of my career at mega-cap companies, that innovators' dilemmas are a real thing. It is hard to reinvent yourself. When you have a big profit pool, to be able to risk it and try to enter new areas is a very challenging dynamic. That's why we see new breakthrough customers or new breakthrough companies all the time. We hope to be that in this new era. We believe, again, our right to win is our proprietary voice AI stack. I think the difference also is in this world, as said many, many times, data's gold. Companies, our whole model is brand-centric. I mentioned this in the auto space, but generally speaking, we are very flexible and agile with how data is managed. We work with customers. We know it's their customer relationships. We work in partnership for how to manage the data. We want to use it to refine and improve our models and to scale. We understand, like I said, in the automotive space, that Hyundai, it's their customer, and we want to work with them. We also think of that with privacy. We think of that with security domains. We think of that with all the capabilities we're bringing. Our go-to-market motion's different. I raised that in the point of some of the names you just threw out. I spent many years prior to coming to SoundHound at Nike. And one of the biggest challenges that Nike had was it's their customer footprint. When they would start to partner with the Big Tech, how is the data and the customer conversation holding? Because there's always risk of disintermediation. Our model is we're brand-centric. We have our own unique way of winning in this market. That's a whole other vector of wanting to control the brand, some of these large OEMs. I think that's a loose segue to the diversity of your business in terms of different types of products, but also different types of rev rec, right? The percentage of revenue from recurring sources has increased through the Amelia acquisition. Maybe talk about where you expect that model to go to in the future. If there's anything you want to maybe say about the product loyalty business as well. I think we model about 20% of your revenue. Yeah. Three pillars, and I'll unpack each of them. The pillar one is voice-enabling products, cars, TVs, IoT, and that's a royalty licensing business. Up until 2023, it was the vast majority of our business. Almost 85% of our business came from that. If you think of the application in vehicles, as a car is shipped, we get a royalty. The royalty rate depends on the capability we provide. With edge solutions, you can think of roughly kind of single digits per vehicle. When you get cloud capabilities, it could be higher price points. We are the first company who went live in partnership with Stellantis, went live with integration with OpenAI. That was early 2024 with their premium line DS premium brand. They have scaled into many other brands. That GenAI capability is a price point above it. If you think of like there's 90 million global light vehicles produced per year, take whatever average price you want it, but just for simple math, say $10 per vehicle, that's $900 million or nearly a billion dollars of opportunity annually. Call it reoccurring revenue. Because as new vehicles are shipped, that's when we get the collections. It's a lot more complicated because you do upfront work. You might have to build custom environment, product feature sets, new languages, etc. For if it's a five-year contract, for example, revenue recognition for that workload will spread over five years, even if you've collected the cash. That's kind of pillar one. To your point, it has definitely shifted as we've grown pillar two aggressively this year, which is pillar two. Before you get to pillar two, on pillar one, because there's a lot more IoT devices, there's a lot more televisions. Yeah. There's a lot more thermostats. Absolutely. Besides the 90 million cars from New Jersey. It's a huge opportunity. How would the royalty business work in terms of because you can't take $10 from. No, the price point will change depending on the application. But there's a royalty rate. You could also put consumption economics on it. I'll talk about the third pillar in a second. But you're absolutely right on the there's projected to be 75 billion IoT devices in the next several years. And you're right. It's smart appliances, but it's all sorts of infrastructure. One of the real differentiators with voice AI as compared to traditional technology architectures is that for many of these IoT devices, to have a keyboard or a big GUI interface or have a mouse connection is really difficult. They don't have the economics. They don't have the space. To unlock the power of voice AI, all you need is a very inexpensive microphone. A $5 microphone, and you can unlock the power of voice. For us, we see that as a huge horizon. You're right that depending on what it is, I mean, a larger refrigerator or a TV can actually afford decent royalty. If you get into smaller footprint devices, maybe not. I'll come back to that point because it's a really important point that even a light bulb can unlock the power of voice AI and to have a capability to be able to say, "Time to replace my light bulb," or those things can be connected through our monetization framework in pillar three. Just before I go there, I'll go to pillar two, which has become the it's the biggest growth engine. It is now comprised of two-thirds of our business in 2024 that we just reported earnings on a short while ago. Pillar two is subscription typically. Think of the restaurant application. In a drive-thru setting or in phone ordering for pizza, per location or per lane, we generally get a monthly subscription fee. That range depends on the customer, depends on the number of locations. Generally, it's a fixed rate, but there also can be per order or per query. Oftentimes, these contracts are generally based on up to a certain number of queries, there's a fixed rate. To go above, there's an incremental rate. We have the same applications with healthcare and financial institutions, which could be based on interaction. If you call in, you need to reset your password, or you need to do some banking service like transferring money, or you need to book an appointment for a follow-up dental exam. These things are per interaction. Again, they're subscription SaaS-like typically. The vision was always, and what we built and what we unveiled earlier this year at CES was our voice commerce engine, what we call pillar three. To give you an example, this is connecting basically voice-enabled services with voice-enabled products. Just one simple, many people who drove to this conference, or maybe you're driving into work, and you want to access coffee in the morning, you could just now, instead of fumbling around with your phone and looking for that app, you could just talk to your car and say, "I'd like coffee." The car knows where you're going, and it could say, "Great. There's a next exit, five-minute detour. Here's one coffee shop," or, "There's one closer to your work. Would you like me to order your cappuccino for pickup?" That simple transaction created value to the user because, again, you're not stumbling around. You're focused, eyes on the road, and you got access to the coffee you needed to pick you up in the morning. That restaurant would happily pay for the lead generation of that transaction. A new lead is a new business. If you consummate the transaction, the transactional economic, or kind of think of the commission rate of it, they'd be happy to pay. Our model is that we share part of that commission with the product creator, or in this case, the car manufacturer. Now, if you're a car manufacturer, even you're incented because you're like, "Wow, not only did I sell the car and I got users engaged, but I actually can get monetization through this." You can think of that with TV applications and watching football on a Sunday, and you order the pizza at halftime. You could think of so many applications of booking for flight reservations or your next vacation or, again, medical services and so forth. We are just building this ecosystem. Early days are a tremendous traction against. We just launched it at CES in January. The number of OEMs who are engaged, the number of restaurant partners engaged beyond restaurants that are starting to get engaged. It's early days. This is ultimately, like we think in terms of meaningful revenue contribution, is still a little ways out. Really early traction and very excited. Yeah. I think you mentioned that in your 2025 guidance, you're not factoring in, if any, voice commerce. We'll call this pillar three. There was a couple of mentions about proof of concepts, a big uptick in the number of proof of concepts. And it seemed like there was a flywheel effect to those wins. Talk to us about how that's going to impact the model from a flywheel perspective, like voice commerce maybe impacting royalties or the way around subscription impacting voice commerce. It seems like there's an interplay to the division. Yeah, exactly. Going back to the example of the person driving into work and picking up their coffee, again, the user is excited because they're getting exactly what they want when they want a very seamless transaction. The restaurant gets new leads, and the car manufacturer is getting new revenue streams. That is actually the ecosystem that we're building, that flywheel effect. To your point, we've gotten POCs, not only with, by the way, our existing automotive partners, but we're getting new automotive partners who are saying, "How do I get into this?" Even if it might, maybe the royalty business will come down the road, I just want to get into this ecosystem because, again, from a pillar one perspective, they're seeing new revenue economics, connectivity for new services for their drivers or passengers. Restaurants are super enticed, and they're leaning in because they're like, "Wow, now I got people just driving, and I want to make sure when it shows up on the map that my restaurant is on there. If you're going to pick pizza, make sure I'm on that list." They see a new way of getting leads. Again, from other ecosystem partners, it's like people, I don't know the latest data, but I think it's like people on average spend 60 minutes a day in the car through commute and so forth. It is a captive audience. Again, safety issues, or it's also platform providers that are engaged here because voice, again, it's how humans have interacted for our history with one another. It's the most natural way we converse. We've learned to type really fast with our thumbs over the last, whatever, 15 years, but we don't have to learn how to speak. To be able to access services and things that you need in your daily life, we're getting a lot of traction. It is building a flywheel. You mentioned the Amelia acquisition. This was a relatively large acquisition for SoundHound. Maybe just refresh us, maybe the why and why now. It seems like with this large voice commerce opportunity, again, going back to the queries that we get from investors, and we have them as well, why not just kind of take that path and not try to double down on healthcare and financial services, subscription deals, which is it's a big business as well, but it's kind of maybe more of a we talked about enterprise connect earlier. It's more of an enterprise type of business as opposed to commerce. How do those fit? Yeah. I'll go back to our foundation is a tech platform, the voice AI platform. We believe it will be ubiquitous. Voice will be the preferred way that people seek access to services. We're just trying to, again, voice enable the world with conversational intelligence. When we started down this path, we didn't necessarily say we wanted to limit ourselves to certain industries or sectors. We thought of our entry into restaurants, which is a big opportunity. On its own, it's billions of dollars of annual opportunity. Like I said, running start, more greenfield competitive landscape. We think we've got a lot of traction. For us, we believed restaurants to us was like what books was to Amazon. They were building a big e-commerce ecosystem, but they weren't stopping with books, right? They wanted to start with that. We started to get great traction with restaurants, over 10,000 locations, and great partnerships, and continue to scale. Seven of the top 20 QSRs now and many more in pilot that we hope to unveil over time. I would say at this point, last year, we were not necessarily looking and screaming to say we need to diversify industries. We do have, in a burgeoning market and something that is moving really fast, you need to keep a pulse on what is going on. Like we talked about, a lot of competitors moving in, a lot of new players showing up. We have a dedicated team that is constantly on the pulse of what is going on. Do we want to learn who is a new competitive threat, new partnerships we want to get into? Sometimes that manifests into an acquisition. With respect to the Amelia transaction, we met the team. We got to know them a little bit. We could have had a lot of runway with the automotive and restaurant sector and the IoT. It was a time and a place that made a lot of sense and attracted valuation from our perspective and ability to jump into enterprise settings like healthcare and financial services that on their own, because of the regulatory, the security, the complex integrations, probably would have taken us several years to build on our own to build a go-to-market motion to accelerate that journey and build that capability made a lot of sense for us. It attracted economics. A lot of it, there's 15 reasons why they don't happen. You need to have a lot of things click. Ultimately, it comes down to team and culture and aligned vision and sellers who are motivated and that made sense. We are very excited. The early traction with it is great. The teams are integrating really well. We have a dedicated enterprise team. We are investing in it. They went through their own journey. We are kind of reinflecting in certain areas where we see outsized return opportunity. There is real compliment. Since we are the voice AI tech stack, for example, our speech recognition engine, which we benchmark, we talked about in earnings how comparable to other major players out there. We talk about performance of our new Polaris speech recognition engine compared to Google and how it is 30%+ better in performance. We compare it to OpenAI Whisper, and it's how it's equivalently better, but also at one-tenth of model size, meaning the cost efficiency there is. We are competing against all the best out there. We are winning on that. We know we can, in these major enterprise customers, displace those engines, put our own voice stack in. We do not have to pay third parties. That has multiple benefits, not only in performance, but also our ability to capture data, improve our own models. For many reasons, it made sense for us. We are not on the path of just acquiring for no reason. We will be thoughtful about it. Like you said, it's a meaningful side. We are in digestion mode. We are integrating. Early days are very positive, but we do not take things for granted. We will be mindful about opportunities as they come. We're not out there thirsting for the next one. If something makes sense, then we'll definitely take a look. Right. Let's pause there for a second. Are there any questions from the audience by chance? Right here. Thanks for the presentation. I was wondering if I could start off with a technology question and a finance question because you're in CFO. In terms of the technology stack, I used to cover a firm once before the spinoff of Cerence. What's the technology edge that SoundHound AI has against Cerence after the spinoff? Their pitch back then was because they've been in the business for decades, right, that they have the data. What is it that SoundHound does that differentiates your voice recognition versus other competitors? And then as for the finance follow-up question is, what is your financing needs now, and how do you balance your capital allocation between what you're going to invest versus your needs? Yeah. The first question, to give you the history, Nuance had the relationships, and they definitely had the partnerships. In fact, when we first unveiled our technology, and there is a nice, just a quick one-minute demo on our investor page if you want to take a look. This is from 2015, 2016, so even compare it to state of the art today. It was well differentiated then. When we unveiled that, we had OEMs come to us because they were looking for somebody who had better innovation, could move faster, was much more flexible to work with their existing relationships. That is how we got entry. We had actually many of the OEMs who invested in us and still are investors in this company. That is what got us traction to where now we have 20 brands that we work with. There are a couple of things on the technological footprint. First, again, we built native stack up from the ground up and, again, built by our engineers that have been together. By the way, this is one side differentiator I think that does not get on the headlines for SoundHound. In Silicon Valley, we are in the backyard. We are in Santa Clara. We actually have a founding team and a bunch of engineers who have been together for over 15, 20 years. That is a rarity in the valley. I think that gives us a lot of advantages that sometimes do not show up on the surface of the P&L. Anyway, back to your question. We had differentiation, for example, on speed, accuracy, and low latency. We had a technology we called Speech- to-M eaning, which means where traditional stacks and the ones for Nuance and others were like speech to text, and then you go from text to meaning, two-step process. We did those simultaneously inspired by the brain. That, again, allowed for two benefits. One, it was faster, lower latency, but it was more accurate. There was no error propagation. If you had an error in step one that would carry forward to step two, we would be able to catch that early. There were other ones with the architecture around how we did natural language understanding. We had our own domains. We brought in and got entry originally with cloud capabilities. Nuance was traditionally on the edge stack. We came in and integrated with cloud. We subsequently would go in with cloud and then displace on edge. We have generally, we in the OEM space, because relationships matter, our disadvantage was those long-term, decade-long relationships. We always won on technology. It was a constant innovation. We were also the first, like I just mentioned, to bring integration with OpenAI stack and ChatGPT with Stellantis vehicles. We have an arbitration engine and a sort of agnosticity to our framework that allows us to integrate with any LLM out there. I mentioned OpenAI. We work with Perplexity. We build models off of Llama. We have our own knowledge domain. We have this sort of what we call the yin and yang structure of we can build our own, and we can partner with the best LLMs out there, and we can arbitrate. We have, and by the way, we have full-stack solutions, edge, hybrid, cloud. All of that allowed us to bring new innovation and a speed, which, as I mentioned, one of the best ways in the auto space to look at how are EVs choosing. We have won now several EV brands around the world, again, I think on the basis of tech. Hopefully, that is one color commentary. I can answer it for other industries as well because we think on the restaurant side, it is even more distinct. Maybe to jump to your second question, our balance sheet is very strong. At the end of, I just reported the end of the year, we were $200 million of cash, no debt. We have more than enough. I also mentioned in an outlook that we expect to be adjusted EBITDA positive by the end of the year. For us, software company, adjusted EBITDA is a really good proxy for free cash flow. We are moving from losses for many years to now break even. I have conveyed, and I will say it again, the expectation the investor should have from us is that at full sort of down the road, as a software company, we should have 70% EBIT margins, 30% gross margins, 30% EBIT margins. Let me check that one back. 30% EBIT margins. We will scale to that. Frankly, for the next horizon, think a few years, we are probably going to be in the break-even zone because we want to keep investing. To your question on where do we see opportunity, there is outsized return opportunity. When you are in these major inflections of new technological era, we want to reinvest capital because there are outsized returns. There are returns well in excess of the risk-adjusted cost of capital. We will be reinvesting in the business, but we could do it from a break-even profile for the subsequent years. Can you give us a little bit of, because you have such a good EBITDA margin, right, you say you're going to try to invest more, right, to bring it back down, go on the offensive side. What are the things you're thinking about to invest? Yeah. I think organically, we want to voice enable the world. We want to go further in new industries and grow deeper in the restaurant stack, for example. Just in the U.S., alone, to give you a data point, there's probably 250,000 quick-service restaurant drive-throughs. Drive-throughs, on average, and I won't give you specific names, but there are customers north of this. Average, roughly, it's $1,000 per lane per month recurring revenue. If you take the hundreds of thousands times that, you quickly get billions of dollars opportunity. I'm not even talking about phone ordering, which might be a smaller footprint, but $100 per location per month. From a recurring revenue basis, it's massive from the scale we're talking about. We have a running start. That's a huge TAM. Healthcare, financial services, millions of interactions a year that could be automated. By getting customers, and one of the things we've done with the acquisitions, you've seen a little bit of a reduction in our gross margin, is we're going in with some parts of our business that are call center oriented. We're not trying to be in the call center business. What's great about it is you get access to production-ready data that you can utilize into our engines and automate over time. If we can get more and more of these interactions, more and more of these orders, we can just continue to build and leverage that and scale. This last quarter, we talked about entry into new industry energy, large electric utility, for people to call in, like, "My power's out. What's going on with my billing?" All these use cases of how the world is moving, we want to aggressively go capture that and be first movers in this business. Please. Just another CFO question. You mentioned that you're going to delay your 10-K because of the acquisitions. What's the hang-up? Meaning, what is complex about these two acquisitions you've made? Is there an estimated time that you will file? Yeah. We filed this morning, so it's out there for everybody to see. It was just a few-day delay. Thank you for the question. First of all, everything was materially exactly what we talked about a couple of weeks ago in earnings. You can go through it. There's obviously a lot more content with the notes. Let me go to your question on complexity with the acquisition. We bought companies. As a small company, we have three ERP systems. We had a lot of processes that were manual that we're automating and improving over time. Fully disclosive on where we are in a control environment. We're an early emerging growth company. We're trying to aggressively scale. We're going to continue to make meaningful investments in our infrastructure and processing controls. Obviously, we don't want to delay. We got it done. We are going to, this year, integrate our ERP stacks. We are integrating payroll systems. All these things are just as a small company with limited resources. We are trying to do a lot. So proud of the team to kind of that we are getting through this. Again, we got it filed today, and nothing really meaningfully different than what we said a couple of weeks ago. Just maybe one more just on the competition in the pure cloud AI space. I mean, there's Teneo AI, and there's some other competitors. Can you talk about when you talk about, basically, versus Nuance, which is sort of maybe you could say it's old tech, right? There are other competitors. How do you feel? Any market shares you think you can give us a sense of where you dominate and by how much? Who would be the competitors you worry about? Yeah. First of all, I think any new breakthrough technological era, there's going to be a lot of new competition. We welcome it. It's a sign of a good, healthy market, I think.