Teneo AI AB (publ)

Good morning shareholders investors. It looks like we have a pretty full house, so I think we're actually going to start on time today. I'll probably kick this off as we speak. I want to remind everybody that first of all, the presentation is available on our investor page. Also, this call is recorded and being transcribed so that you know that. So today we're going to be presenting the Q1 presentation 2026 from Teneo. The two people presenting is I and Fredrik. Most of you have seen us before, so I'm not going to dwell too much on that. And I'm going to start with the CEO update. And it is a, let's put it this way, not the best, not the report we were hoping to publish when it comes to the numbers. What I really want to do is give some flavor on what's going on. And is this a car crash? Are we crashing into the railing? Are we going to a low valuation, a low enterprise value? Or are we going to a high enterprise value? And as you see, I sort of feel that from my perspective, we saved the crash and we're now heading towards a higher value. And that's what I'm going to be focusing on in my CEO statement. less focus on the numbers from my side, and then Fredrik will go through the numbers as we move along. What I want to focus on is giving a clear picture of how you should look at the company right now, because I believe it's quite difficult to see that from the outside as we speak. So I want to give as clear a picture as possible, as also legally possible in some cases, some things I'm not allowed to talk about, But the things I am allowed to talk about, I'm going to talk about as well. So there's three paths, essentially. I want us to start off by taking stock by looking at the market and what's going on in the AI market overall. And then there's three tracks. There's the ARR target, so our sales, our sales of a product. There's the IP path, the patent path. I'll go into that too. And then there's the strategic review, which I'm going to give more flavor to as well in the presentation as we move along. Tenio is, of course, that voice AI model that has been deployed in large enterprises and shown to work. in a space where everybody wants to get in as well. So the first thing I want to do is talk a bit about what's happening in the market. There are many new entrants in the market today. We see companies come in and get huge financing checks in that crazy environment in primarily the US or in the US, I should say. And it's all about the debate or the question that investors are having and are betting on is, are the LLMs, so the foundational models, the AI models, the Gemini, the Anthropic Cloud, the Open HiChat, GPT, et cetera, will they be able to actually make business decisions and provide accurate answers or not? And that's what I want to shed some light on because there's been a watershed moment in the market in the last few weeks or months that shows, to me at least, that that's not going to happen and why everybody's going to need It's a neo-like solution if they want to provide business processes based on the latest AI technologies. The first one I want to start off with is a benchmark that was published by Sierra. Sierra is a company that at this point has received about one and a half billion dollars of financing. They're doing very well in terms of getting attention in the market and they published a benchmark. This is called the TAO Voice LLM Native Voice Benchmark. And what this shows is how the model, so this is primarily in the case of Sierra, they use the LLM models only, right? So they have an application, what I call a wrapper, but maybe that's a bit derogatory, but they have an application that then sends the questions to several LLMs and then the answer comes back and their application then tries to pool or make the probabilities of which one of these answers is more correct. When they tried this end-to-end benchmark, which they tested themselves, they came up with 67% end-to-end task correctly done. So what that means is, of course, that a third of the tasks are not correctly done. Now, so the question is how much can they increase that and what's the cost of increasing that to get up to an acceptable level, which is going to need to be about 90%. So we've shown in live production traffic and in testing even higher numbers, but in live production traffic that we can do end-to-end task completion 91% of the time in live voice deployments. So these are not apples to apples, but they're looking at the same business process. And I think that's the important thing. Businesses really need to solve a problem. They don't need the best and coolest technology to solve the problem necessarily. They need to solve the problem. The problem is phone calls are increasing and they're increasing because humans make more phone calls, but now agents are making phone calls. I don't know if you played around with the latest, for example, perplexity browser comment. But in the comment, you can even make phone calls now to customer service. So if you want to ask something about your package, you will ask about a policy, you want to do a post a claim, you can do it now with an AI agent as well, which is fairly secure and fairly well functioning a bit better than open claw. But we're getting there where humans will have AI agents as well. Phone traffic is going up. The business problem is we need to automate them because we can't hire enough people to do it. So we need AI agents on our side. And that's the gap that we provide. We provide that accuracy. And that's why customers now after testing all these other solutions are coming back to us. And that's also why we believe that our solution is important to these new players, the very well financed players. and our patents are important to them as well. So that's the first example. The second example is a thing that's lacking except for the accuracy that's lacking in these solutions today is the auditability. So the ability to see what has happened, the security, and then the certification. So things like PCI, ISO, SOC, these are standards that you need to follow and in some case certify against to ensure that your solution does the things that it says that it's doing according to the process that you define. PCI being very important, for example. So if you have a discussion and a credit card data goes from you to OpenAI or from you to Claude, then you are, according to PCI, the one that's liable and the one that would have to pay damages for that. So one of the more competent organizations, I would say, in this environment right now is McKinsey. McKinsey, of course, they bought the what's called Quantum Black Company, which are AI experts, really, really solid, real heavy-duty consultants. And they've been building internally an assistant called Lilly, which is also what they're selling to customers as an internal assistant. So this is the assistant where you would be able to access all your information in your company and talk about it and build things, build presentations, build documents, et cetera, for your customers. Now, the interesting thing with that is that it contains everything, including confidential things like M&A discussions with customers or anything under M&A essentially goes into this database. And then it's accessible by Lilly internally. And it's now been discovered, again, I think this is now two weeks ago, maybe three weeks ago, a company called CodeWall. They used an autonomous agent to just see, can I get access to all this information? in McKinsey, and it was very easy to do it through a very simple thing. It's called an SQL injection, something we've been doing for the last, what, almost 20 years, or maybe even 30 years. So it came out in the early internet ages. But because all this is built with AI, that is a black box, right? So all the LLMs are black box. Nobody really noticed this within McKinsey. that it was easy to get to the endpoint through an SQL injection. It's getting a bit technical, but I think you'll understand that really what I'm saying here is, McKinsey exposed all data internally, all client data, all their internal data, because they put it all in one solution that that database then was accessible through an LLM-based AI agent. And this has been going on since late 2024, when they deployed Lilly. nobody really knows how much has been leaked. And now there's lawsuits and all sorts of things happening and looking at who's going to go to jail for insider trading and etc, etc. Very difficult legal space to work in. But of course, they shut down Lilly, which is a solution that they've also sold to companies as an internal bot. So this is really, really difficult material, right? So as soon as you let the LLM be a part, a large portion of your runtime, this becomes very, very difficult. So we use LLMs a lot, but we do not use them for the things where compliance and auditability and security is important. And that's a real key. And that's what we call hybrid AI. And then the second proof that things are happening in this space where the models are not really going to fix this stuff with the 67% accuracy end-to-end is that OpenAI and Anthropic, they've just both committed 10 billion in the case of OpenAI and one and a half billion in the case of Anthropic. Anthropic is Claude and OpenAI is Chachi Petit. They've committed that to build service organizations that can build all the stuff that Teneo has for organizations so organizations can deploy the LLM models. So this is a very important statement by them. They're essentially saying, No, the models are not going to catch up. The models are not going to go from being probabilistic. You need to build the scaffolding or you need to build the house. You need to build a whole building or you need to build a car and we have the injection. That's it. So we're not going to help you with forward deployed engineers. So they're going to be deploying engineers to build this, the next generation of Lilly internally. And today, a lot of that, of course, is focused on coding. That's also what's happened in the last few weeks, that the bolts were initially focused on customer support, that's our space, and now a lot focused on coding. That's why we also see customers now finally coming back saying, ooh, actually didn't work. It didn't work very well, this whole customer care space, because you need the accuracy. You cannot tell a customer that they owe you 126,000 when they owe you 294,000, for example. So Mark Nechem at Goldman said, there's a big shortage of people who know how to apply these tools into businesses and then transform them. And I think that's an understatement because it's very difficult to do that. However, if you do it with Teneo, it becomes a lot easier and you would provide the value quite quickly. Next slide is quite busy. So I warn you up ahead, but I do want to show this. It is the architecture that Teneo works in to show you where we sit in relation to all of this. So all that I've talked about here is what we call layer three. And that's the orchestration of the intelligence in the company. That's where Tenio sits. So you have an end user on the left side of this slide. The end user comes in through whatever tool that might be, a messenger, WhatsApp, or the phone, or a phone call on FaceTime, or whatever it might be. It comes in through what we call the omni-channel layer. This is where we cooperate with companies like Vonage, Evoxy, et cetera, to take that and bring it into our platform. And as we do that, we have an STT that we also take mostly from Azure, from Microsoft. And now we have a text string. That text string has incorrections in it. So we take that into our engine and we correct those imperfections. And then we put it into what we call TLML. This is where the hybrid part comes in. That's the Teneo Linguistic Markup Language. This is where our patterns start to play, right? Understanding what the customer really said is important. This is where we bring it up to 99% accuracy instead of 89, 90 that you would get from just a transcription. We then run the business logic and look at the automations that can be deployed on this. We use the tools that we have access to, the knowledge base that we have access to. Important here is whoever that speaker is, that customer, They get access only to the authenticated knowledge they should have access to that's managed by Teneo. And then of course, we deploy the accuracy booster on all this to ensure that we keep the accuracy through the whole process. If Teneo cannot answer, so in a few percent cases, Teneo will not be able to answer an automate, then we go to and hand over to an AI agent, and then it goes over to layer four to the contact center, and from there into the contact agent in the backend. However, if we can, we also got to use the LLM models And we're going to generate the response so that the response sounds very natural and flowing. The conversation feels natural. We're going to use that, but we're going to inject it again with the accuracy booster to show when the conversation goes back to the customer, it's 100% correct response. And then we integrate with all the backend systems, such as SAP, Salesforce, ServiceNow, HubSpot, Power BI, et cetera. All this leads to quick time to value. You would have to build everything in Layer 3 yourself today if you want to deploy something else, and all these new entrants that are infringing on our patents would need to build it too. And that's important, I think, to understand for the M&A process that today what we provide is not competing at all with layer four and layer five. We are the orchestration layer, which is what everybody now starts to realize they will need. So that's the background on the market. I'm sorry if it got a bit technical. I'm very happy to answer questions on this, also an email or whatever later, if you wish to understand this more. But this is quite important as you look into our three lenses. So I'm saying we're still keeping our ARR target of $200 million with the current cost base. Now, why am I saying that? It's because our pipeline is still strong. It's actually stronger than last time we reported it, which was in September. We actually forgot to report it in December because of this partner conflict that started in December and has still been playing out through Q1. But we still retain that. We have the other option, which is patent licensing, but patents and the technology is also part of the arsenal, the weapons for the M&A discussions. And I call it M&A here now just to, and I will dive a bit deeper into that, but there are deep discussions with a number of top buyers around what we do and what Teneo would provide to them. And that is, of course, from the strategic review. So those are the three paths I want to talk about, and I'm going to start with the first one. So I've shown this slide, but like I said, we forgot to show it in December, but we did in September. So from the Q3 report. The investment in new sales is essentially a sale that we do We only count the subscription revenue, the revenue for the platform, which manages the solution over time. You build a solution, deploy it, but then you manage over time in the platform. So the 6.9 million total euro total pipeline, which is a weighted pipeline, is of course a lot larger than it was in September. What that implies is that we're not losing, we are adding more. into the pipeline. But what's happening in the pipeline is customers are testing the LLM solutions. They're testing either one of the LLM wrappers, like a Sierra, like a Genesis AI, which is also built on an LLM wrapper solution. They're testing Paloa or any of the others that got so much financing that they have all the marketing, but they're failing with it. and I'll come back a bit more to that why that is and why these are keep in our pipeline but it's the longest sales cycle I've ever seen and I've been in enterprise sales since well since last century and I've never seen anything like this where customers have such difficulty making decisions six late stage deals these are deals where we're in pilots pox we also have one deal that just closed which is not reported in not taken out of the pipeline here yet. That is because it's close to the partner. The partner has signed up a Teneo solution for the largest, one of the largest, I'm not going to say which one it is. So one of the largest telcos in Turkey. That one only in 18 months, according to the implementation plans that the partner has, will be generating a million dollars per month. So we are also closing these out, but it is really, really, really long to get that closed out. So that's one of the paths to unlock the value, to make sure the car goes right, doesn't crash and doesn't go to the left. The second one is the patents. I'm going to start with showing a patent process here. The way these things happen is you start with noticing that people are infringing. Now, all the AI LLM wrappers All the ones you see that are talking about doing customer care with AI, all of those companies today are essentially infringing and they have no patents in this space. So you do the DD, we've done that. That's where you confirm that the patents are actually being infringed on. We call that a claims chart. You take the technical documentation of the company and then you compare that to the claims and that's done by a patent attorney. That we have already done. The patent attorney is not the litigation attorney, so it's not the one that then starts the sort of negotiation. That's a second line attorney. We just retained the best attorney in the United States for this. This is, of course, a United States thing that we're going after because that's where the money is. Also, that's where these competitors are that do not have the tech nor the patent. So this is a dual approach, right? We're looking at approaching them to talk about licensing and using our tech. But at the same time, of course, it's something that goes into the strategic review, because if you don't have the tech, it's easier to acquire the tech. And it's easier to also have the patents as defensibility going forward. So you send the letter. We started sending the first letter last Friday. As you send that letter out to a company and that letter then gets treated in there. And then hopefully you never get to filing a complaint, step four. Instead, you go to the yellow one, and you start negotiating on the settlement, which would be a license fee or some other kind of business construct. The first letter we're sending is very, very nice talking about cooperation, et cetera, but it is definitely built on a real claims chart by a patent attorney. So again, the new attorneys are also the ones that are gonna be now taking over the partner conflict. The attorneys we had during Q1 got very caught up in the tariff debacle that happened in the US and have been very short shifted on time for us. The new attorneys, which again are number one in the US, it is definitely a top tier law firm. The new attorneys will take on the partner conflict, which I'm not allowed to talk about more than that, and the patent litigation. And also, which is important, this is what we're discussing to go on a contingency basis. So that means that we don't pay until there's a settlement, and then we pay part of the settlement to the attorney. So important to understand those points. There are infringements. We started the process. The potential is for M&A or for licensing, but we're using this as an argument for both, right? The patents we're talking about that are the prime suspects or the one that has the sort of heaviest infringements, are these patents. I'm not going to read the patent numbers, but it's one. The first one is natural language intelligence. Customers speak, of course, natural language. Sorry. They can speak it in any language. And in our patents, we already have, say, no rigid menus, so no IVRs, right? No scripted paths. And then Teneo instantly will select the right resolution path. That is exactly what everybody wants to provide to the market. Then we have the multi-agent orchestration. This is where agents can talk to each other without losing the context. And because agents cannot do that natively, you need a layer above that. That's called the orchestration layer. That's another one of our patents. And then natural language analytics. So once you have all these customer dialogues going, where you're calling into Microsoft, you're solving a support issue, once that's happened, You want to be able to mine that knowledge. And that's what it goes into our TLML. And it's very easily accessible to see why our customer's calling. What if we change that in our website? What happens then, et cetera, et cetera. Those three patterns are the most important. Here's the chart of how strong the case is for four different companies. And I'm not mentioning these again since the attorney has told us not to. The no name is the only one on here that we might want to do something legally with as well. which is not an LLM wrapper. I'm not gonna say more than that. And the key functionalities, of course, are the three patterns from left to right. Those are from top to bottom here. And it's very strong overlap in all these LLM wrappers. So all these startups that have millions of, hundreds of millions of dollars now to start building the technology they need. And there's only moderate on the network side for one of them, but that's not the one we compete with on a daily basis, but that's a different conflict. without saying more than that. So the next thing I want to talk about is the strategic review. So there's a team here that is top tier, also important to note. JP Morgan, of course, is the number one tech M&A advisor in the world. There's some seriously heavy duty people working on that together with us. And then, of course, Redeye is the number one in the Nordics. and has done several transactions in the Nordics and provides that Nordic spice that is needed and all the knowledge that is needed from a Nordic perspective in this strategy review process. And the strategic review process, I want to share a few things around this because it has to do with financing. It has to do with the market interest as well. But let's start off with it is on track. It is taking some time, but it wasn't expected really to be much faster than that. But there's high interest in the Teneo AI technology. This is a space that's hot. So a lot of companies are looking at what to do now, especially since this has happened in February, March that I mentioned in the market. It's the expansion of the service team for OpenAI Cloud. It's the McKinsey, Lilly big data breach. And then of course you have the 67, 68, 69% that we've seen on the TAO voice index from several of the LLM wrappers. The primary goal is exit here. Today, the board has been shifting. The primary goal has gone sort of from finding a distribution channel as well to really doing an exit based on that market interest. And we believe that that is the way to maximize shareholder value today. To go this alone at the bottom right here, the standalone path is going to require more than just interim financing. It's going to require a lot more money coming in from shareholders because what's happening in the market is that there's so much revenue spend, so much spend on the other, the LLM wrappers, that in order to get ahead of them, we would need a larger sale caterer and we would need more marketing. We could get to the 20 million ARR with the current call space, but if you really want to utilize the momentum in the market, you would need to bring in more money. So that's why the primary goal is exit. And then there will be an AGM announced. We have initiated the debt financing. Sorry, I need to mention that first. The current debt, of course, matures in end 2026. And as you know, we have a covenant holiday expiring during the summer. which is contingent on and working towards that exit goal, right? So that's all connected, but there is an AGM where we will also announce a financing plan in order to conclude the strategic agreement. Now that financing can come from at this point from shareholders or from one of those attorney led discussions. I think it's very important that I phrase myself in the same way, But it can come from different things. That revenue shortfall, there is a discussion on the other side of that revenue shortfall, which of course comes from one partner that we have discussed before, but which I'm not mentioning more than that. So I'm going to move over to a summary before I leave it over to financials and talk about the numbers, which again is a depressing thing. That's why I wanted to give you this sort of framing before that. I think it's very important that we understand where we are so that from a shareholder perspective, you can make your decisions fully informed. So near-term definitely headwinds, right? I mean, I would never have expected to be able to show anything else than growth. and of course it's it's the absolute opposite but it's still a very strong foundation so the revenue is from this loss of the key customer which is a partner dispute if if we look at the the underlying business the margins remain strong so it's still the same thing if we add revenue it contributes a lot to our our cash flow So the underlying business is sound, but we do of course need more revenue and that's what we're working on. And the 20 million is still our target. It's not gonna be achieved within this fiscal year anymore. It's gonna be something that we need to look at to having Q1 or Q2. It is again dependent on that attorney led discussions, putting it correctly again. But the pipeline is definitely on track And it's also, and this is important, right? Enterprises are now coming back to us after internal builds or builds with LLM wrappers. So these new entrants, maybe we call them LLM based companies going forward. As they fail to deliver, we're getting back. And one of those is the project FTS launched. FTS is our partner in, one of our partners, and they launched a first Tenure project now. with a major telco in Turkey. That project alone is projected to in 18 months be generating $1 million of revenue. And that is with the growth of a very, it's a very large volume and it's with the growth of the project there. So that is the first one that sort of come back from trying with something else. This is a discussion that's been ongoing for probably nine to 10 months. And I've seen that they couldn't really do what they wanted to do with the LLM-based approach. And there, Sierra AI, I'm going to mention the name here, one of their flagship customers invited to Neo two weeks ago and called us and said, guys, you need to come back and have a dialogue with us because it's failing on the voice AI side. And we need voice AI to work. We budgeted now having fewer people, well, actually not, We budgeted having a larger volume with the same amount of people, and it's not working the way it should. So now we're in dialogue with them to create the pilot to show that we can actually solve the problem that Sierra did not. And it's all about the accuracy. It's all about making sure that the agent gives the right answer, but also understands the question. And then very importantly as well, I'm announcing this in the quarterly report only as an investor news. It will be announced to the wider market, so to customers after the Excel Excel's investor days, which are this later this week. So Excel is a BPOB BPS company based on AI. It's a US company that became partner of the year for Genesis last year as well. So they were heavily into contact centers and providing technology into contact centers. And they selected Teneo for voice AI delivery after testing several of the new solutions, what I call the LLM wrappers again, but also testing, of course, the Genesis native solution, which is also an LLM based approach. So the hybrid AI won, because they needed the effects of that. So very proud of that has taken us a long time there as well to be benchmarked against all these different solutions. But we came out on top, signed the partnership agreement and started training them last week. And again, there will be a market announcement, which is more that shows a bit more of that for customers and for the market in general. But I wanted to share it here since we did sign it We started signing about a week ago and started training them a week ago. And then the IPM Legal, it is a top tier council this, right? This is number one, New York based, and they will both take over the partner discussion. So this partner conflict that we have, which is impacting the revenue, and that's going to put more speed onto that. Like I said, the attorneys we had were very good, but didn't really have the time at this point to support us. But the scope is also expanding to patent licensing where we're planning a contingency engagement. So that would be where we don't pay them upfront, but we pay them with the proceeds from licensing and potential damages that might come out of that conflict. The IP and the patents are also important for the M&A discussions and they are intensifying. It is something that I end up spending quite a lot of time on. And it's of course discussions of where our technology fits in this new space, in that orchestration layer, in layer three that we talked about. So with that, and I'm sorry if you got too technical, but just ask me questions afterwards. With that, I'm going to hand it over to Fredrik to go for the financials.

Thank you, Per. Let's move to the first slide there. You've all seen the numbers. So let me first, I mean, just explain a bit, you know, what has happened. So the deviation in sales in SaaS ARR in the first quarter 2026 is to a large extent linked to the decline in sales from a former reselling partner. Par has mentioned that quite a bit earlier in the presentation as well. And as we also mentioned, council discussions are underway due to this and where we also will be pursuing patent licensing deals with organizations that are actually infringing on our patents. On the positive note, the company's pipeline for new customer is continuing to develop favorably. So we have a record high pipeline, as you could see on the previous slide presented by Per. And Tenio is progressing the sales pipeline and continues to have a strong momentum with new customers. Intention is obviously to replace lost revenues here in Q1 with new customers coming in. What we also see is obviously, as for many Swedish companies selling abroad, currency has had a significant negative impact on our ARR and revenues during the first quarter of 2026. So year over year, we have a 9% negative impact on net sales and net sales in constant currency amounted to 12.3 million versus 25.3 million Q1 2025 so what 51 decline in in in sales and says there are in constant currency amounted to 27.5 million versus 75 million last year, so a 63% decline, so significant drops as you can tell as well. So even with this decline, we also record a stable gross margin, which also show that we have very good scalability in our operating model underlying and so we reported 80% gross margin despite the volume decline in the quarter. And on cost side, I will come back a bit on that. Going forward, we will continue to invest in sales and marketing. And also linked to that, we will also have some investments related to the legal pursuits that Per has mentioned quite extensively here earlier in the call. But we still keep cost control. So we have control of all the costs and follow and track this continuously, obviously. Adjusted EBITDA in Q1 26 amounted to minus 12 million. Significant decline due to mainly the volume drop in the quarter. positively also in Q1, we secured 25 million in subordinated debt from key shareholders and we are very grateful for that support from these key shareholders. I think we can move to the next slide, Per. And API call volumes on SAS is obviously a key indicator of how our business is doing. Unfortunately, we are not growing in the quarter as can be seen from the graph on the slide. And this KPI is obviously an indicator of how our customer application and the usage of them are growing. And the more applications, solutions, covered regions, et cetera, the higher API call volumes. So we recognize a decline quarter over quarter as well as year over year. As mentioned earlier, new volumes are underway from our pipeline as we close new customers and new projects with existing customers. On that also, once again, mention the deal that we are pursuing now in Turkey as one positive example that we can highlight as well. But as Per also mentioned, the pipeline is very strong. And we have a number of long developed deals that we are continuing to work on, on also finalizing. So we see a lot of faith in the pipeline going forward. I think we can go to the next slide, Per. As already said, currency had a negative impact in our ARR in the first quarter. So in that regard, I think it's very important also then also given the decline we have on volumes to also highlight the currency adjusted growth rates. And SAS ARR in constant currency amounted to 28 million as mentioned earlier versus 75 million last year. So it's 63% decline. similar negative growth rates on total ARR as well. So I think we can move to the next slide. And gross margin as we have presented as a key metric earlier. It's stable despite the volume decline 80% in Q1 26 and obviously higher CES API core rooms is important for us to continue to expand the gross margins to levels we have recorded previously and also where we can further improve as well with higher volumes. Next slide Per. On the OPEC side, I just want to acknowledge that in Q1 2025, we guided for somewhat increased cost as we carefully continue to invest in sales and marketing activities. We have done that since then. And we'll continue on that path as well. But despite this, we have also managed to keep cost control. So we actually have a lower OPEX run rate, Q1 26 versus 25. So essentially we are keeping cost control. And as also earlier mentioned, we will continue to carefully invest in sales and marketing. since we also have a very strong pipeline and interest in our underlying technology from partners and end customers as well. But still obviously keep cost under tight control. And as Per mentioned, we have retained a new top tier legal counsel with a continuous engagements. So essentially where we are doing a kind of sort of a revenue share agreement based on outcome. This will cost some money, but less money than if we would have pursued this on a standalone basis, obviously. So with that, I think we can go to the next slide, Per. In cash position, we started the quarter with a strong cash position. We had a cash position including collected receivables. So an adjusted cash position of 29 million at the beginning of the quarter. And also as mentioned in the earnings release and also brought up here by Per, the company plans to secure financing for ensuring there is sufficient time to conclude on the strategic review process. And part of that is obviously where we have different alternatives. One is obviously that we can can go the council-led pursuit where we would potentially end up in a settlement situation where we could finance the company and the strategic review process that way. The other alternative would also be, which I think Per did not mention, and that is obviously that we could lend money from our external parties and or key shareholders to finance this pursuit of the strategic review process. And thirdly, obviously, there is an alternative to also go to all the shareholders to ask for money. But this has not been concluded yet on the way forward. in how we will ensure that the the financing will be secured for this process to be reviewed but we will come back on on that later on here in in May I think with that leave over to you Per great thank you Fredrik I wouldn't really want to be an

analytiker and try to model this right now but I will again try to summarize and give you a good as good as possible picture of where we stand right now so obviously the revenue impact is big from this there's so many things you could say about this but you're not allowed I'm not allowed to because of the essentially our attorneys have told us not to and We still have the capacity to deliver with the current cost base, $20 billion ARR, which of course would make us very cashflow positive. That is one path that the company can still take. And if we then would also like to expand that even more and take momentum, then of course we would need a different financing regimen. Since we are competing with companies who are very well financed from a sales and marketing perspective. We've seen a lot of competitive validation where the LLM wrappers are failing. uh three of the the more important ones here is um the fgs project that they won after the the major telco uh working with an another one of those wrappers and we saw a sierra one of sierra's flagship customers invited to neo to come in and fix the voice ai or rather replace the solution with something that works excel selected us a very, very important partner for us since they are a partner in the contact center space. What's happening in contact center, which maybe I didn't talk too much about when I showed that architecture, is that since now the call, only the calls need to go to Hume and go to the contact center, since we're front running and companies like Genesis and Five9, et cetera, are not too interested in working with us, they view us as competitors. But EXL is because they have those customers which then would reduce the payment that they have to pay to one of the contact centers. And then, of course, the M&A discussions are intensifying, and that is something that is definitely a strong interest for the technology itself. And that's probably understandable with the rest of what I spoke about here. With that, I'm going to leave it over to Q&A. And as usual, there's a double mute. So you raise your hand, I unmute you, and then you unmute yourself after that. Oh, here we have a question. Let me open Thomas here. I need to find you on the list first. Thomas, Thomas, Thomas. If anybody finds Thomas before me, yes, Fredrik, for example, you just hit unmute on him. There he is. So now I've unmuted you. Tomas, you need to unmute yourself and then you can ask.