Good morning, shareholders, investors. It looks like we have a pretty full house, I think we're actually going to start on time today.

I'll probably kick this off as we speak. 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. 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, not going to dwell too much on that.

I'm going to start with the CEO update. 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. Are is this a car crash?

Are we crashing into the railing? Are we going to a low valuation, low enterprise value?

Or are we going to a high enterprise value? As I see as you see, I sort of feel that my from my perspective that we saved saved the the crash, and we're now heading towards a higher value.

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 from the outside as we speak. I want to give as clear picture as possible as also legally possible in some cases.

There's 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. 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. Then there's three tracks.

There's the ARR target, our sales, our sales of of product. There's the IP path, the patent path.

I'll go into that, too. Then there's the strategic review, which I'm going to give more flavor to as well in the presentation as we move along.

Teneo 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. 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.

It's all about the the debate or the the question that investors are having and are betting on is: are the LLMs, the the foundation models, the AI models, the Gemini, the Anthropic Claude, the OpenAI ChatGPT, etc., will they be able to actually make business decisions and provide accurate answers, or not? 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 a Teneo-like solution if they want to provide business processes based on the 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 $1.5 billion of financing.

They're doing very well in terms of getting attention in the market, and they published a benchmark. This is called the the TAU-voice, LLM-native voice benchmark.

What this shows is how the model So this is primarily in in the case of of Sierra, they use the LLM models only, right? They 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 it 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 try this in end-to-end benchmark, which they've tested themselves, they came up with 67% end-to-end task correctly correctly done. What that means is, of course, that a third of the tasks are not correctly done.

Now, 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%? 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.

These are not really They're not They're not apples to apples, but they're looking at the same business process. I think that's the important thing.

Businesses really need to solve a problem. They don't need the bri- 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've played around with the latest, for example, Perplexity browser Comet, but in the Comet, you can even make phone calls now to customer service.

If you want to ask something about your package, you want to ask about a policy, you want to do a make 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 Claude, 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.

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.

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. That's the first example.

The second example is a thing that that's lacking, except for the accuracy that's lacking in these solutions today, is the auditability, the ability to see what has happened, the security, and then the certifications, things like PCI, ISO, SOC. These are standards that you need to follow, and in some cases certify against, to ensure that your solution does the things that it says that it's doing according to the process that you defined.

PCI being very important, for example. 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 is liable and the the one that would have to pay damages for that.

One of the more competent organizations I would say in this in this environment right now is McKinsey. McKinsey, of course, they they bought the what's called QuantumBlack company, which are AI experts, really, really solid, real heavy-duty consultants.

They've been building internally in a system called Lilli, which is also what they're selling to customers as an internal assistant. This is the assistant where you would be able to access all your information in your company and talk about it, and and build things, build presentations, build, documents, etc., 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 NDA essentially goes into this database, and then it's accessible by Lilli internally. It's now been discovered, again, I think this is now 2 weeks ago, maybe 3 weeks ago, company called Codewall, they used an autonomous agent to just see, 'Can I get access to all this information in McKinsey?'

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 the last what, almost 20 years, maybe even 30 years. It came out in the early internet ages.

Because all this is built with AI that is a black box, right? All the LLMs are black box.

Nobody really noticed this within McKinsey, that it was easy to get to the endpoints 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 an LLM-based AI agent.

This has been going on since late 2024 when they deployed Lilli, and nobody really knows how much has been leaked. Now there's lawsuits and 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 to work in. Of course, they shut down Lilli, which is a solution that they also sold to companies as an internal bot.

This is really, really difficult material, right? As soon as you let the LLM be a part a large portion of your runtime, this becomes very, very difficult.

We are We use LLMs a lot, but we do not use them for the things where compliance and auditability and security is important. That's that's the real key.

We That's what we call hybrid AI. Then the second proof that things are happening in the 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 $1.5 billion in the case of Anthropic—Anthropic is Claude and OpenAI is ChatGPT—they've committed that to build service organizations that can build all the stuff that Teneo has for organizations, organizations can deploy the LLM models.

This is a 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 engine. That's it.'

We're not going to help you with forward-deployed engineers. They're going to be deploying engineers to build this, the next generation of Lilli internally.

Today a lot of that, of course, is focused on coding. That's also what's happened in the last few weeks, that the models 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 it 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.' Marc Nachmann 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, 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. All that I've talked about here is what we call Layer 3, and that's the orchestration of the intelligence in the company.

That's where Teneo sits. You have an end user on the left side of this slide.

The end user comes in through whatever tool that might be, Messenger, WhatsApp, or or the phone, or a phone call on FaceTime, or whatever it might be. It comes in through what we call the omnichannel layer.

This is where we we cooperate with companies like Vonage, Sabio, etc., to take that and bring it into our platform. As we do that, we have an STT from that we also take mostly from Azure, from Microsoft.

Now we have a a text string. That text string has has incorrections in it, we take that into our engine, and we correct those imperfections.

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 patents 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 has been that we have access to, the knowledge base that we have access to.

Importantly 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.

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, in a few percent cases, Teneo will not be able to answer and automate, then we go to a handover to an AI agent, and then it goes over to Layer 4, to the contact center, and from there into the contact center agent in the back end.

However, if we can, we also going 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 ensure when the conversation goes back to the customer, it's a 100% correct response.

Then we integrate with all the back-end systems, such as SAP, Salesforce, ServiceNow, HubSpot, Power BI, etc. 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. That's important, I think, to understand for the M&A process, that today, what we provide is not competing at all with Layer 4 and Layer 5.

We are the orchestration layer, which is what everybody now starts to realize they will need. That's the background of the market.

I'm sorry if it got a bit technical. Very happy to answer questions on this also on email or whatever later if you wish to understand this more.

This is quite important as you look into our three lenses. I'm saying we're still keeping our ARR target of $20 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 this partner conflict that started in in December and has still been playing out in in through Q1.

We still retain that. We have the other option, which is patent licensing.

The patents and the technologies also part of the arsenal, the weapon for the M&A discussions. 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.

That is, of course, from the strategic review. Those are the three paths I want to talk about, and I'm going to start with the first one.

I've I've showed this slide, but like I said, we forgot to show it in December, but we did in September, the the 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 this solution over time. You build a solution, deploy it, but then you manage it over time in in the platform.

The so the 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 Genesys AI, which is a which is also built on an LLM wrapper solution.

They're testing Parloa, or anyone any of the others that got so much financing that they have all the marketing. They're failing with it, and I'll come back a bit more to that why that is, and why these keep in our pipeline.

It's the longest sales cycle I've ever seen, and I've been in enterprise sales since well, since last century. 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, POCs. We also won deal that just closed, which is not reported in not taken out of the pipeline here yet.

That is because it's closed to the partner. The partner has signed up a Teneo solution for our for the largest one of the largest, I'm not going to say which one it is, one of the largest telcos in in Turkey.

That one That one only, in 18 months, according to the the the implementation plans that the partner has, would be generating $1 million per month. We are also closing these out, but it is really, really, really long to get that that closed out.

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 the space. 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 patent attorney.

That we have already done. The patent attorney is not the litigation attorney, it's not the one that then starts the sort of negotiation.

That's that's a sec- 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 things 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.

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. You send a letter.

We started sending the first letter last Friday. As you send that letter out to 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, etc., but it is definitely built on a real a real claims chart by a patent attorney.

Again, the the the new attorneys are also the ones that are going to 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. Also, which is important, this is what we're discussing to go on a contingency basis.

That means that we don't pay until there's a settlement, and then we pay part of the settlement to to the attorney. 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. [coughs] Sorry.

They can speak it in any language. In our patents, we already have saying no rigid menus, 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.

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. Then natural language analytics.

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. That's where it goes into RTLML, and it's a very easily accessible to see, 'Why are customers calling?

What if we change that in our website? What happens then?'

etc., etc. Those three patents 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 to as as 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 going to say more than that. The key functionalities, of course, of the three patents from left to right, those are from top to bottom here.

It's very strong overlap in all these LLM wrappers, all these startups that have millions of hundreds of millions of dollars now to start building the technology they need. There's only moderate on the 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.

The next thing I want to talk about is the strategic review. There's a team here that is top-tier, also important to note.

JPMorgan, of course, is the number one tech M&A advisor in the world. There's some seriously heavy-duty people working on on that together with us.

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 in this strategic review process. The strategic review process, I want to share a few things around this because that has to do with financing.

It has to do with the market interest as well. 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. There's high interest in the Teneo AI technology.

This is a space that's hot, 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, Claude.

It's the McKinsey Lilli big big data breach. Then, of course, you have the 67%, 68%, 69% that we've seen on the the TAU-voice index from several of the LLM wrappers.

The primary goal is exit here. Today, the board has been shifting, and the primary goal has gone sort of from finding a distribution channel as well to really doing an exit based on on that market interest.

We believe that that is the way to maximize shareholder value today. To go this alone at the bottom bottom right here, the standalone path is going to require more interim 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 the LLM wrappers that in order to get ahead of them, we would need a larger sales cater and we would need a larger more marketing. We could get to the $20 million ARR with the current cost base, but if you really want to utilize the momentum in the market, you would need to bring in more money.

That's why the primary goal is exit. Then there 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. As we have a covenant holiday expiring during this summer, which is contingent on and working towards that exit goal, right?

That's all connected. There is an AGM where we will also announce a financing plan in order to conclude the strategic review.

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 I phrase myself in the same way, but it can come from different things.

That revenue shortfall, there is a a discussion on the other side of that revenue shortfall, which, of course, comes from from one partner that we have discussed before, but which I'm not mentioning more than that. 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 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.

Near-term definitely headwinds, right? I would never have expected to be able to show anything else than growth, and, of course, it's it's the absolute opposite.

It's still a very strong foundation. 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, it's still the same thing. If we add revenue, it contributes a lot to our our cash flow.

The sound underlying business is sound, but we do, of course, need more revenue, and that's what we're working on. The $20 million is still our target.

It's not going to be achieved within this fiscal year anymore. It's going to be something that we need to look at to to have in Q1 or Q2.

It is, again, dependent on that attorney-led discussions, putting it correctly again. The pipeline is definitely on track.

It's also, and this is important, right? Enterprises are now coming back to us after internal builds or builds with LLM wrappers, these new entrants, maybe we call them LLM-based companies going forward.

As they fail to deliver, we're getting back. One of those is the the project FTS launched.

FTS is our partner in one of our partners, and they launched a first Teneo 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.

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 9 to 10 months, and have seen that they couldn't really do what they wanted to do with the LLM-based approach.

Then Sierra AI, I'm going to mention the name here, one of their flagship customers invited Teneo 2 weeks ago and called us and said, 'Guys, you need to come back and have the dialogue with us because it's failing on the voice AI side. We need voice AI to work.

We budgeted now having fewer people. Or actually not, we budgeted having a larger volume with the same amount of people, and it's not working the way it should.'

Now we're in dialogue with them to create that the pilot to show that we can actually solve the problem that Sierra did not. It's all about the accuracy.

It's all about making sure that the agent gives the right answer, but also understands the question. 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, to customers, after the EXL EXL's investor days, which are this later this week. EXL is a BPO BPS company based on AI.

It's a US It's a US company that became Partner of the Year for Genesys last year as well, they're heavily into contact centers and providing technology into contact centers. They selected Teneo for voice AI delivery after testing several of the the new solutions, what I call the LLM wrappers again, but also testing, of course, the Genesys native solution, which is also an LLM-based approach.

The hybrid AI won because they needed the effects of that. Very proud of that.

It 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. Again, there will be a market announcement which is more that shows a bit more of that for for customers and for the market in general.

I wanted to share it here since we did sign it we start signed it about a week ago, started training them a week ago. Then the IP and legal, it is a top-tier counsel this, right?

This is number one, New York-based. They will both take over the partner discussions, this partner conflict that we have, which is impacting the revenue, and that's going to put more more speed onto that.

Like I said, the the attorneys we had been very good, but didn't really have the time at this point to to support us. The scope is also expanding to patent licensing, where we're planning a contingency engagement.

That would be where we don't pay them upfront, but we pay them with the proceeds from from licensing and 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 it's, of course, discussions of where our technology fits in this new space, in that orchestration layer, in Layer 3 that we talked about. With that, and I'm sorry if it 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 will all see in the numbers, let me first, just explain a bit what has happened. The deviation in sales and SaaS ARR in the first quarter 2026 is, to a large extent, linked to the decline in sales from a former reselling partner.

Per has mentioned that quite a bit earlier in the presentation as well. As also mentioned, counsel-led 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 customers is continuing to develop favorably. We have a record-high pipeline, as you could see on the previous slide presented by Per.

Teneo 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 2026. Year-over-year, we have a 9% negative impact on net sales.

Net sales in constant currency amounted to 12.3 million versus 25.3 million Q1 2025, a 51% decline in sales. SaaS ARR in constant currency amounted to 27.5 million versus 75 million last year, a 63% decline.

Significant drops as you can tell as well. 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.

We reported 80% gross margin despite the volume decline in the quarter. On cost side, I will come back a bit on that.

Going forward, we will continue to invest in sales and marketing. 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.

We still keep cost control, we have control of all the costs and follow and track this continuously, obviously. Adjusted EBITDA in Q1 2026 amounted to -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.

API call volumes on SaaS 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.

This KPI is obviously an indicator of how our customer application and the usage of them are growing. The more applications, solutions, covered regions, etc., the higher API call volumes.

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. 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 also finalizing.

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. In that regard, I think it's very important also, given the decline we have on volumes, to also highlight the currency-adjusted growth rates.

SaaS ARR in constant currency amounted to 28 million, as mentioned earlier, versus 75 million last year, a 63% decline. Similar negative growth rates on total ARR as well.

I think we can move to the next slide, Per. Gross margin, as we have presented as key metric earlier, it's stable despite the volume decline, 80% in Q1 2026.

Obviously, higher SaaS API call volumes 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 opex side, 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.

Despite this, we have also managed to keep cost control, we actually have a lower opex run rate Q1 2026 versus '25. Essentially, we are keeping cost control.

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. Still, obviously, keep costs under tight control.

As Per mentioned, we have retained a new top-tier legal counsel with an contingency engagements. 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. With that, I think we can go to the next slide, Per.

Cash position: we started a quarter with a strong cash position. We had a cash position, including collected receivables, an adjusted cash position of 29 million at the beginning of the quarter.

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. Part of that is obviously where we have different alternatives.

One is obviously that we can go the counsel-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.

Thirdly, obviously, there is an alternative to also go to all the shareholders to ask for money. This has not been concluded yet on the way forward in how we will ensure that the financing will be secured for this process to be reviewed.

We will come back on that later on here in May. I think with that, leave over to you, Per.

Great, thank you, Fredrik. I wouldn't really want to be an analyst and try to model this right now, but I will again try to summarize and give you as good as possible picture of where we stand right now.

Obviously, the revenue impact is big from this. There's so many things you could say about this, but I'm not allowed to, essentially, our attorneys have told us not to.

We still have the capacity to deliver with current cost base $20 million ARR, which, of course, would make us very cash flow positive. That is one path that the company can still take.

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 that are very well financed from a sales and marketing perspective. We've seen a lot of competitive validation where the LLM wrappers are failing.

Three of the more important ones here is the FTS project that they won after the major telco working with another one of those wrappers. We saw one of Sierra's flagship customers invited Teneo to come in and fix the voice AI, or rather replace the solution with something that works.

EXL selected us, a very very important partner for us since they are 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 only the calls need to go to a human go to the contact center, since we're front-running in.

Companies like Genesys and Five9, etc., are not too interested in working with us; they view us as competitors. EXL is because they have those customers, which then would reduce the payment that they have to pay to one of the contact centers, so.

Then, of course, the M&A discussions are intensifying. That is something that is definitely a strong interest for the technology itself.

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.

As usual, there's a double mute, you raise your hand, I unmute you, and then you unmute yourself after that if you wish to ask a question. There's so many people on here, I'll see if I can find—

Per, just I think we have a question in the chat here from Morten. I can respond on that one.

Essentially, the question is in earlier reports, we have written that we expect to win back a lost customer. I would say that this is very much our expectation,

and I think— Fredrik, the reason it's not in there is we're not commenting that, we've been advised to not talk about that. Morten, I'm sorry to say, the US is just complicated.

There's so many things you could say, but we've been advised to not talk about that.

Yeah. On that note, I think it's also worth mentioning that Per mentioned the FTS partner or the partner that we have signed in Turkey, the potential in that deal is more or less $1 million monthly.

I think it was in our Q3 report in 2025 where we also highlighted how large the customer deals that we actually are working on and the impact it can have on our revenues. I think there it's also important to note that we are still continuing a lot on working on those large deals as part of also being in our pipeline that Per described.

The potential is very much that we can quite quickly, once we sign a deal, we can actually have a revenue upside coming very quickly in our P&L. I think that's the key here.

Let's see. If you raise your hand, I will unmute you, and then you unmute yourself after that.

Are you saying that Fredrik and I made a very clear case here, there's no questions? 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, Fredrik, for example, you can just hit unmute on him.

Where is he? Now I've unmuted you, Thomas.

You need to unmute yourself, and then you can ask.

Yes, good morning. Can you hear me?

Yes.

Good morning. Thanks for a great presentation, Per and Fredrik.

Just a quick question on the Turkish client so that I understand. The implementation period, is that 18 months, is that correct?

Not necessarily. It's the scaling period, I would say, is 18 months.

You're talking about $1 million per month in income, is that correct?

That's correct. That's when it's fully built out.

Given that they run according to the plan, and it's somewhat easier than others we've seen, there's less unions and other things in that geography.

Let's assume if now it takes, let's say, 12 to 18 months to implement, and $1 million per month, is that going to bring you to a cash flow positive situation?

We need to come back to the $20 million ARR. I don't want to state a forecasted goal here.

I don't want to state a goal here because it's very heavily dependent on this attorney discussions, right? So

Okay.

Yeah, $1 million per month would be cash flow positive, right? So.

Also to add there, Thomas, we state clearly, right, that our opex run rate cost, excluding then variables and also cost of sales, is 9 million per month. Then you can obviously do your math yourself, more or less, that if fully built out, yeah, 9 million is very close to $1 million.

Thank you very much.

There is life in the pipeline here, for sure. Like I said, that it has been going quite slowly.

However, Shandan, can you provide some color on the ongoing JPMorgan review? The project with JPMorgan and Redeye is progressing.

We're now at the stage which I would call technical due diligence stage, we're presenting very deep technical dialogues with a few of these companies. That's sort of expected.

That's a part of the process. When it comes to the financials, we are publicly traded, it's not that difficult to sort of We don't have any lik i garderoben, as we say in Swedish.

I'm not sure what the English expression would be, but there's no real surprises in our financials. We've always paid our taxes and everything, it's really about the tech, and that's the stage we're at.

We have a question from Alexander. Let me find Alexander in the list.

Teams actually puts the people that raised their hand at the top. Alexander, I'm allowing your mic, and now you need to unmute yourself, and then you can speak.

I believe it was March 18 where Microsoft was publicly one of the key customer reference cases. To what extent can you comment on this question?

Is the business relation with Microsoft as a core end user or key customer intact, or is that also impacted or affected by this litigation-related issues?

That's almost like the Elon Musk asking the attorney, 'Have you stopped beating your wife?' like he did yesterday in the court case on OpenAI.

I believe I cannot comment that. What I can say is that Microsoft is one of our best references when it comes to talking about how the technology provides great value.

We are also a majority of our late-stage, the six that we are in proposal stages are actually through Microsoft, Microsoft selling that. That's probably what I can say.

I'm sorry, it's difficult to understand the US system, but, yeah, we're not allowed to talk more than that. Any other questions?

I tried to provide as clear picture as possible. I hope that we conveyed it as well as possible.

Due to the ongoing process there, we really cannot comment more, which is kind of a shame because there's so many things I'd like to say about that, but that's where we stand. Thank you all.

Thank you for your continued support. Bit of a rocky ride here the last few months, but I do believe we're getting closer and closer to the market understanding that you need scaffolding.

It's not going to be the steel and concrete that wins; it's going to be the ones that can actually implement this technology in the enterprise. Certainly OpenAI and Anthropic are showing that with saying that they're going to put all these services people in, so.

Very happy that you are still supporting us and listening in. We're going to work our best to make one of those three paths provide the highest possible value for shareholders.

Thank you all, and have a great day.