CXApp Inc. (CXAI) Earnings Call Transcript & Summary

[Audio Gap] we'll take some questions in the Q&A section as well. So I appreciate that. So with that, let's get going with the business. So let's talk about our Q2 earnings. And as I said earlier, the 3 themes: number one, EngineRoom is transformative. Number two, [ Sky 2 ] out as real is available. And third, we're now seeing a clear operating model for translating growth into operating leverage and ultimately profitable growth. And we at [ Sky ] are building the [ agendic ] AI operating layer. So before we go into the business numbers, let me talk to you guys about the just make sure you have the disclaimer slide on what is -- what are the forward-looking statements, make sure you read that safe harbor. Please review the safe harbor non-GAAP disclosure in today's presentation and our SEC filings with the applicable risk, assumptions and reconciliations. We will be filing the 10-Q tomorrow, and so you can read that when you get that. So let me talk about the company we have today, right? And the company we have today is pretty amazing. We have deployed globally around 200-plus cities with more than 60-plus customers now supporting a large installed base of users. We operate inside demanding enterprise environments where security, privacy, reliability integration are not offshore, they are necessary. This matters because our AI strategy starts from something valuable, enterprise trust and real operating context. Context is very important. We aren't beginning by building an AI application and trying to figure out where it fits. We already operate inside the enterprise. We understand people, places, workflows and enterprise systems. And [ SkytudeAuto ] is about making that context increasingly intelligent and actionable. So we're headquartered in San Francisco [ Brea ]. As you know, we have teams in Toronto and Manila. And now we're excited to welcome the Australian team, which is headquartered out of Melbourne, but they're all across Australia as well in New Zealand. We're excited to have them onboard, and this gives us the global coverage. We have around 70 team members now globally, and they're all working hard in making AI successful in the enterprise market that we're in. So before we get to the numbers, let me just give you context of where we've been and where we're going, right? So [ Sky 1.0 ] established the enterprise foundation. It showed us that we have great software, workplace software that has people [ in place ] intelligence. We have Fortune 500 customers. They have high trust, high complexity deployment. This remains an important part of our business. We made some significant strides in the last 2 quarters. Chris is going to talk about those customer case studies and stuff, but it's been amazing there. But [ Sky ] really expands that opportunity. we're moving primarily from understanding places, which is really the flow product, which is where and how people work; to person, which is what we're calling [ BEAT ], what an individual and team need to accomplish and what should happen next in your life as a worker? And now we're moving with EngineRoom into business, how companies acquire customers convert demand and grow. That business context is significantly strengthened by EngineRoom, as you know. And then any dose experience is the same [ Sky agent ] platform. The strategy from here is very straightforward, proven enterprise technology, mid-market distribution, [ Prodent ] ties the eye and scale recurring revenue. We're going to run that flywheel cycle because we've got now a new agentic platform that we can leverage across multiple verticals. And more importantly, we now have a new distribution mechanism through EngineRoom. So this is the transformation I'm talking about. This is what we're executing on, and we're super excited about this opportunity. So let me go into the business for this quarter. And what happened this quarter. So this is a pretty exciting time for CXAI or [ Sky ]. As you can see on -- as you can see on our highlights for the quarter, the six main highlights. But the biggest one is the EngineRoom transaction. It is transformative. I'm going to talk more about it in detail, but it really did change the revenue trajectory for the company. And more importantly, quarter-over-quarter increase of probably 79% revenue growth from [ $930,000 ] in Q1 to approximately $1.7 million in Q2. The more important thing is what's just underneath that growth. Enterprise retention remained strong, 2 major Fortune 500 customers renewed their relationship with [ Sky ]. In enterprise software, renewals matter enormously because they valuate the product after the initial sale. Customers have continued to choose [ Sky ]. We also added a significant new win in the financial services sector. This is a 3-year multimillion dollar recurring revenue deal. We went through a competitive RFP. We're super excited to have that customer on board, and they're scaling with us at the beginning of this quarter. And it's a really, really important win for the team. And it's [ won ] for two reasons: First, it demonstrates continued demand from highly sophisticated regulated customers. Secondly, these are the type of customers where [ Sky 2.0 ] can expand over time across additional modules, users and AI capabilities. The other big achievement for this quarter is we moved Sky [ to auto ] into deployment, and that's a big win for us. And the progression is [ win ], deploy, adopt, expand exactly what we want to replicate. And with 2.0, really what we get as an [ AgentiCare ] platform that allows a user to navigate their workplace, navigate their work and navigate their experiences across the whole enterprise. And that's very exciting. And our customers, the reason why they're selecting us is because we have [ Skytra ]. That's the wins we got, that's the renewals we got are all because of [ Sky ]. And as you know, during the quarter, we completed the EngineRoom transaction. So for Q2, we only have 1 month because it was the month of June, that EngineRoom as part of the revenue. And it's been an amazing 1 month because they've continued to get new clients. We have got double-digit growth. They're going through this annual process where they've got commitments from existing clients. So it's been really good. And so all of these six factors combined really have been super successful for the company. I want to congratulate the team on the job well done, And it builds the momentum strengthens the foundation for [ Sky 2.0 ] and our scale growth move forward. So let me tell you a little bit about EngineRoom and what better than just to roll a video. So operator, if you can roll the video. [Presentation]

All right. Cool. That's pretty exciting. So when I talk about EngineRoom, I talk about it as being transformative. And as you can see from the video, it's pretty exciting stuff they do. And they've been at it for 13 years, and they've made amazing progress in getting clients and making sure that they have really solid footing. So let me tell you why this is transformative. EngineRoom room does not simply add revenue, it changes the starting point for [ Sky ]. EngineRoom brings more than $8 million of revenue, approximately $1.6 million of adjusted EBITDA, a highly recurring revenue profile and more than 50 mid-market customer relationships. But strategically, three things matter even more for me: Number one, distribution. [ Sky ] historically sold into large enterprises through an enterprise sales process, EngineRoom [ with ] the structured relationship with dozens of mid-market businesses. That gives us a much faster proven ground and future distribution channel for [ SKY AI ] products. Number two, business context. As I said earlier, [ Sky ] already understands workplace and employee context, and that's one of our moats and differentiation. EngineRoom brings customer acquisition, performance, marketing and growth data that allows [ Sky Curado ] to expand from understanding how people work to understanding how businesses grow. Number three, cross-sell, we can introduce [ Sky ] capabilities into EngineRoom's customer base. and we can induce EngineRoom growth capability in the [ Skies ] enterprise products. So the combined company has an enterprise anchor, a mid-market growth engine and a shared [ agenda ] platform. And the combination move [ Sky ] to more than $12 million of annualized revenue scale. This acquisition created scale. Our job now is to turn that scale into operating leverage. So I'm super excited about this. I think this is the right move for the company. It positions us ready for the growth engine that we've been talking about, the double-digit growth. It gives us that flexibility in terms of having the ability to innovate in a very interesting market, Australia. I'll talk more about that in the investor forum. We will have -- we'll go more deeper into it. But I just want to share this story with you and sure we do that this has been an amazing, amazing transaction for us. So with that, I want to move on to the financials for Q2. I'm going to turn it over to Melissa to walk through the quarter in more detail. As you listen to the financial results, I would focus on one important relationship, how rapidly the revenue base is changing relative to the cost structure. Melissa, all yours.

Thanks, Khurram. The quarter-over-quarter comparisons demonstrate that step-change is taking place in the business. Between Q1 and Q2 revenue has increased approximately $950,000 in Q1 to $1.7 million in Q2, representing, as Khurram previously mentioned, a 79% sequential growth. Our annual recurring revenue has increased from $3.6 million to $11.5 million. Sorry about that. Net revenue retention has increased from approximately 98% to 99.3%, continuing to demonstrate our strong retention across installed bases. Total assets increased from approximately $33 million to $36 million, and our cash EBITDA improved from approximately negative $3 million in quarter 1 to negative $2.68 million in quarter 2. EPS was approximately negative $0.10 compared with negative $0.09 in Q1. So the key takeaway quarter-over-quarter as that revenue base increase substantially while cash EBITDA improve modestly. We're still investing in integration and development of the combined businesses, but the operating model is beginning to show greater scale. The year-over-year comparison also shows meaningful progress. Revenue increased approximately 42% from $1.2 million in Q2 of 2025 to $1.7 million this quarter. ARR increases from $4.5 million to again the $11.5 million, an increase of approximately 156%. Net revenue retention increased by more than 5 percentage points to approximately 99.3%. Assets also increased 22% from $29.6 million to approximately $36 million. Cash EBITDA was approximately negative $2.7 million, which is a neutral position compared to a year ago. And EPS has improved from approximately negative $0.16 to negative $0.10 between the 2 years. The most significant change in the financial profile is, therefore, the scale of the recurring revenue base while we continue to manage investments required to support integration and future growth. And now let me put this cost structure into perspective. Total operating expenses increased approximately $275,000 quarter-over-quarter or 5.6%. However, we do need to compare that with the approximately 79% sequential revenue growth. The increase in operating costs was driven primarily by the EngineRoom acquisition and associated operating activity. Importantly, these Q2 numbers do not yet reflect the benefit of the operating synergies we are implementing as we integrate the businesses. Our focus moving forward is straightforward, grow revenue faster than expenses. We expect to accomplish that through shared functions, tighter operating discipline, productized implementation, increasing automation and a higher recurring software contribution. That operating leverage is central to the financial strategy for the combined company. And I'll turn it back to Khurram now.

Thank you, Melissa. I apologize I was on mute. This was a really great quarter. As you can see, we are finally showing the value of our technology platform, but also the engineering acquisition. But I want to put in perspective what I see the value of this company as we move forward. And this is -- the valuation is based on numbers that we get from KeyBanc, which does a monthly survey on software benchmarks and looks at all the recurring revenue-based businesses and software businesses. So as I think of our business now, it is an AI-powered software business that is at a much larger scale. And the scale, as you know, last quarter, we were $1 million a quarter. This quarter, we are now $1.7 million a quarter. And with the full EngineRoom integration, we will be hitting $3 million a quarter or $12 million [ analyzed ] by next quarter. And that shows real growth as well as shows real momentum and scale. And based on that, when you think about that business and you think about the software business with the metrics we have just on a conservative basis, we're -- it's a 9.7x multiple, right? That's more on next 12 months revenue. I'm just saying that revenue we have now, we will have now by Q3. So to me, we're at a very attractive stock price right now, given where we're at in terms of the valuation that we should command. I do believe that we will continue to perform and given our double-digit growth strategy, we believe, by in the second half of 2027, we will be growing and getting to the breakeven point. And that's where our focus is. Our focus is really to get to that level. And you can see the metrics based on that. This is all illustrative by the way, this is not a valuation guidance. I'm just taking industry benchmarks and showing you what the value of this company is and the fact that we've now built that [ agent ] platform that R&D expense has been done, and now it's about growth and distribution. And this is where we did the EngineRoom transaction, and this is where we feel very strongly about the growth and scale of the business. Can we sustain this growth? Can we increase software mix? Can we translate into great revenue scale? Absolutely. And that's where the 2 businesses have been complementary, but we're going to help each other scale up faster. Now let me talk about probably the most important -- one of the most important charts in the slide deck here, is about the path to breakeven, right? And again, this is a directional operating framework, not specific financial guidance. The EngineRoom acquisition gives us a combined revenue of more than $12 million. From here, there are several identifiable levers. First, organic growth; continue expanding the [ Sky ] enterprise business and EngineRoom's customer base. That's obvious. Second is cross-sell. Introduce additional [ Sky ] modules into existing enterprise customers. Chris is going to talk a lot about that today. Number 2 is introduce [ Sky Gent ] products into the EngineRoom's mid-market customer relationship, though that's a second cross-sell that we think is very important. Thirdly, increased software monetization. We'll talk about flow, we'll talk about analytics, events and our emerging personal execution capabilities called [ BEAT ]. All increase our opportunity to generate recurring software revenue from the same platform. And fourth, prioritize that mid-market motion. For mid-market customers, we don't want to recreate a long enterprise momentation. Our objective is to standardize the products, standardize the connectors, faster provisioning and lower cost to serve. Fifth, operating leverage. We now have opportunities to share infrastructure, technology, corporate functions and delivery capabilities across a much larger revenue base. That's the synergy that Melissa talked about. The operating model we are working towards a characterized by [non ] double-digit revenue growth, which is part of our strategy as well as what EngineRoom is already on; number two, recurring revenue, more than 95%, gross margin above 70%, software mix above 95%, increasing revenue per customer. We're already at $150,000 to $200,000 per client per year, which is really great. and a disciplined expense growth, which now we can do with the largest scale. If you -- if we execute against those levers, we believe there is a credible path towards breakeven in the second half of followed by profitable growth. So I want to now close with [ Wiki ]? Why do you want to continue to invest and be part of this journey? Why is this moment different for [ Sky ]? Reason number one, EngineRoom is transformative. It immediately increases our revenue scale. It gives us profitable operating capability. And perhaps more importantly, it gives [ Sky ] a mid-market distribution engine that we did not previously have. Reason number two, [ Sky 2.0 ] is now in production. This is no longer simply a roadmap or an AI narrative. We are ready now to deploy this across our clients. We've been successful in the in the demonstrations and prototypes and getting it through our clients, they're doing through a lot of validation, but now it is launching live with a new client. It's also launching live with existing clients. And now we have these new enterprise logos signing multiyear agreements. They would not be signing multi agreements with us unless they knew that the roadmap and the product we have is going to be long-lasting and for the future. And we are expanding the platform from workplace intelligence to personal execution, which would [ beat ] as well as the growth intelligence, which is EngineRoom. And reason number three, the financial model is becoming more scalable. Q2 revenue increased approximately 79% sequentially, while operating expense increased approximately 5.6%. That does not mean the work is finished, far from it. But it demonstrates the opportunity for operating leverage as we integrate the businesses, grow recurring revenue and prioritize more of what we offer.

So with that, I'm going to look into some questions that have come in. Let me see. Okay. Question number one. Great question. How much cash do you have? What are your liabilities after the purchase of EngineRoom? I'm going to have Melissa take that.

Thanks, Khurram. So our cash as of 30 June 2026 is $11.7 million. Most importantly, the acquisition costs have been -- acquisition costs related to EngineRoom have been largely paid. And any subsequent funds owing on that -- on the acquisition of EngineRoom room are tied to an earnout model.

No, that's good. So I think just to be clear, the EngineRoom acquisition was 65% cash and the rest was in earn-out. So the team is focused on -- it's a 2-year earnout with growth factors in revenue specifically. So that's going to earn out itself. So we have no other liabilities on EngineRoom, except the earn-out. And overall, as you can see, the asset base has increased, and it has been a very successful integration up to now. Okay. Next question I see is, how quickly should shareholders expect the EngineRoom acquisition to be reflected in [ Sky's ] report revenue? Mel, do you want to take that?

Yes. So we've actually already captured 1 month of combined revenues to that being the month of June. We will be able to demonstrate next quarter, so Q3, the full combined impact over the 3 months of that acquisition and the combined revenue.

Yes. Okay. I think the next question was -- one more question. What do you think of the revenue growth over the next 12 months? So look, I gave you some illustrative graph on our potential. As you know, we are focused on double-digit growth. We really believe that the scale we're getting with EngineRoom, the wins we have with our existing enterprise business and new logos coming in that are multiyear, multimillion dollar contract; we're pretty positive on that. And we're also positive on EngineRoom because they've also increased their -- they've increased their revenue profile, the number of clients and their [ annual ] process has been super successful. So anyway, we are pretty positive on that. I think our goal is, like I said, is to have breakeven by second half of 2027. If we execute our plans that we have and the growth vectors that we're working on, I'm pretty confident in that. And we're also focused on expense management. And with [ AgentiKI ], we're leveraging the eye across our enterprise. All our functions are using AI. So we're seeing a lot of efficiency there. As you can see, in terms of our team members, we're very cost efficient. And so I'm pretty positive that in the next 12 months, we will achieve much higher growth, and we will get to the breakeven target that we have. So okay. We're running to the end of the call here. So thank you, everybody. I appreciate it. We're going to take a brief pause, and we'll join you back in 60 seconds or so for the investor forum. Thank you.

All right. It's 30 Pacific, 5:30 p.m. Eastern. Welcome to the investor forum. Thank you for people who joined the earnings call a few minutes ago. We're going to be more strategic here, more product focused when you talk to you about the products, the business, the customers, the things underneath the hood that we're working on and show you the path that we believe is going to be super successful for [ Sky ]. And so I think we shared the agenda before. I'm going to start off with the strategic view of the business and more strategic thinking about where we're at, where we're going. And then the team is going to tell you how we're doing what we're doing, what we plan to do next, And then we'll end up with a very interesting fireside chat. So thank you for being here, and we wish to do this next time live in person, but we're going to do our best to do these demonstrations and these discussions on the webcast. So number one, I want to start with something I believe very strongly. And I've been involved in lots of technology transitions. I was involved in the first mobile phone. I was involved in the 4G network, which is involved in the first WiFi systems. And then I was involved in 5G and cloud and all this interesting kind of technology [ demons ] that have happened. And I believe we are at the beginning of another major technology transition in enterprise software. And what I mean by that is [ Sky ] started by solving a very real problem, how people interact with the workplace? And that happened after the pandemic. As you know, COVID kind of created this hybrid environment. [ But ] we have built underneath that experience is becoming much bigger than a workplace application. We have enterprise integrations. We have proprietary contacts, we have AI orchestration, we have data, and we have security and trust. And now we're bringing all these assets together into [ Sky 2.0 ] or agentic AI operating layer. So our strategy has three priorities. Number one, we pushing Sky around this generic operating layer, what I talked about is the context. Second, used EngineRoom to give us immediate scale, mid-market distribution and a much larger customer base. And thirdly, is prioritize what we learn into repeatable vertical AI solutions. This is not simply an evolution of our product. I believe it can be an evolution of the company, right? So we're going to talk about that. We're going to go through some real strategic focus on why we're doing this. So let me explain why the timing is important in the industry right now. Enterprise software is evolving as we speak. The first generation of enterprise software created systems of record. Then SaaS and analytics give us applications, dashboards and visibility. But visibility is no longer enough. The next generation of enterprise software is about action about getting stuff done basically. AI agents will increasingly understand context, make recommendations, coordinate workflows and actually complete outcomes. And that is the layer I want [ Sky ] to own. Not another chatbot, not another dashboard, not another AI feature added on to an application. The operating layer between the enterprise systems, its data, its people and the actions that need to happen next. Employees want fewer applications, [ executing ] want decisions rather than more dashboards and mid-market businesses when practically that produces value today without having to assemble teams of AI engineers to build it themselves. This is the opportunity that we are designing [ Sky ] around. So we're building the agenda I layer for enterprises to work and grow, and that is our focus. Let me put it into a little bit more detail and show you what I mean by that, right? This slide shows me where we came from and where we're going. We started with place. [ Skyflo ] understands where and how people work, workplaces, spaces, resources, presence and experiences and maps and locations. Now we are moving into person with [ BEAT ]. [ beat ] is about personal and team execution. What do I need to accomplish? What has changed? What matters most right now, what should happen next? How am I going to be become more productive? And eventually, what can the platform safely do for me, right? In an enterprise, you want to be in a secure environment, you want to be able to get your stuff done. Now we're adding business through EngineRoom. How does the company find customers? How does it convert demand? Where is the marketing working? Where is it not working? What is the revenue being lost? All those questions need to be answered. And what actions should happen next to grow the business? So think about what we're assembling. [ Place ] gives us workplace context. [ Beat ] gives us personal and team [ contact ]. EngineRoom gives us customer and growth [ contact ]. And underneath all these three is one shared [ Sky ] platform. It senses, it prioritize it, it acts, it verifies and critically, it learned. And also it gets it done. We're about the outcome business. We're about contact and not just another insight, context should lead to an outcome, and this is what we're focused on in really creating those amazing outcomes for our clients. So next, I'm going to talk about the market, right? So this is study taken from one of the vendors, the [ Grand View Research]. And you look at the market starting [Audio Gap] amazing. We're participating in three large categories that are all growing digital workplace platforms, enterprise gendeKI and now marketing automation and growth intelligence. The individual market growth down here are significant, but the bigger number is the compounding 75x [ plus ] effect plus compounding effect of growth over the next couple of years into 2030. It is not claimed that our addressable market sometimes becomes [ 75% ], but the opportunity for us is 75x. So we're not exposed to only 1 category now. We're exposed to 3 categories. We sit in an intersection of workplace intelligence, [ agendiI ] and business growth [ interten ]. And my conviction is that the intersection matters because enterprises don't ultimately buy AI because AI is interesting. They buy it to make employees more productive, make better decisions, reduce cost and grow revenue. These are precisely the outcomes that these businesses allow us to attack together. So let me talk about what are we building, right? And we spend a lot of energy and time with our Silicon Valley team. And as we integrate our folks in Australia, they've also been thinking about it. And the reality is all great minds think together, and we've had a great interaction with our teams. This gets to the heart of what we're building. Across the top, you see the context domain, the work intelligence, the place in person, the growth intelligence, the business and the future verticals that we can add over time. But I want you to focus on what's underneath. This is the [ Sky a generic ] platform. The philosophy is simple: Understand the context, recommend the action, get the right approval, complete the outcome. As I mentioned in previous events, [ bond ] is our agenetic engine. [ Bond ] is a multimodal, multi-agent orchestration system that provides the genetic execution capability. [ Cortex ] provides intelligence, context, knowledge graphs, personalization and analytics. And we surround that with the requirements of enterprise actually care about. They care about identity, they care about [ adiability ]. They care about human control, they could bid connectors, they care about governance. They care about all the things that are important to make an enterprise successful. And that's why we are -- we have designed this for the enterprise. We've designed it with all those controls. And we've also integrated with all our partners, all our cloud partners. As you know, we have a strong relation with Google Cloud, also partner with AWS, and we have also one of our clients using Azure. So we are multi-cloud. We have access to all their models, all their information, and we're using the best-in-class technology to deliver this agentic operating layer. And the most important part of that discussion is we're not betting on [ Sky ] on one foundational AI model. [ More ] will change. [ Malls ] will get cheaper. [ Malls ] will become more powerful. Our value is the enterprise context, orchestration, permissions, actions and outcomes layer from these models. That's why I call it the operating layer. The [ modem ] price intelligence. [ Sky ] makes that intelligence useful inside the enterprise. We are the outcomes. We are the actions, and that's what we're focused on. Another key part of this, as we looked at EngineRoom and other opportunities to partner with folks is that this architecture that we built gives us tremendous leverage. We don't have to build a completely different technology stack every time we enter a new use case. The same orchestrational here can support workplace agents can support growth agents, analytics agents, automation agents and eventually, industry-specific agents. A meeting attribution agent may solve very different customer problem. But underneath, they need many of the same capabilities. They need the data, they need the contact, they need the permissions [ being ] the workflow orchestration, they need orderability and the ability to complete work in the system where that work belongs. That is where I believe the leverage come from: One platform, many specialized agents, real business outcomes. And the more repeatable those agents become, the more efficiently, we can take them to the mid-market. So that's where we're really focused on, is we've built a really strong technology architecture. And now we're looking for with that amazing product we're looking for the distribution model. And this is where our new friends at EngineRoom come in. So as I think about EngineRoom, I think I mentioned in the earnings call, but I want to reiterate, it is strategically super important for us. It is simply not an acquisition that added revenue. EngineRoom changes how we can take [ Sky ] to market. [ Sky ] gives us the enterprise anchor, technology improvement in complex environment. EngineRoom gives us a mid-market customer base, recurring revenue, commercial data and people who understand how to drive measurable business outcomes. In Australia, gives us an excellent launch pad. We can launch, learn and scale. We can work directly with businesses in trades and fuel services, construction, automotive, health care, professional services and manufacturing. These are incredibly important parts of the real economy. A plumber doesn't need another chat bot. A construction company doesn't need another AI demonstration, a health care operator doesn't need another dashboard. They're very practical folks. They need more customers, they need faster response. They need better scheduling, they need lower acquisition cost, they need higher employee productivity. They need better visibility in what is driving revenue. This is where practical, vertical AI becomes incredibly powerful. EngineRoom gives us more than 50 customer relationships and a recurring revenue foundation. Our objective is to identify the workflows and repeatedly create value, praise them on the [ Sky ] platform and distribute them more broadly. Services help us discover the problem, software gives us the scale. So this is why I'm super excited about EngineRoom. It's getting us a head start into the mid-market strategy that we've had. We're working closely with them. This quarter, they start identifying customers. They've already been a lot of great interest. And as we get [ flow and beat ] and events and other products that Chris is going to go through, there's a huge opportunity to leverage that channel. All right. So next, let me talk about a little bit more detail about the combined platform, right? All of these strategies and these product regions ultimately have to translate into economics. And I'm going to go a little bit more deeper. I know I went a little bit on the earnings call. But the acquisition gave us the scale. It gave us that home revenue. Now [ Sky. ] has to give us operating leverage. Today, we have that combined revenue north of $12 million -- we have enterprise customers on the [ Sky ] side. We're growing those customers. We have those 50 mid-market relationship to EngineRoom. We have recurring revenue, we have data, we have distribution. The next phase is about pulling 4 levers. Number 1 lever is grow and expand existing businesses. And both businesses are really working really well. The enterprise business is expanding and EngineRoom customer growth is happening. Secondly, cross-sell and distribute across the combined customer, that's job one, and we're doing that right now as we speak. Third is the exciting part of prioritizing the AI and new modules, increasing the software component of our revenue, which is already 95%, but not growing it in the new AI economy. And fourth, training their operating leverage as the company scales. And we talked about it's already starting to show the signs in Q2 here. This means that ultimately means that revenue should grow faster than the infrastructure required and supported. Our ambition is very clear, higher recurring revenue, higher software mix, higher gross margins, more revenue per customer and a path with breakeven and then profitable growth. So the acquisition creates the scale, the platform has to create the leverage, and that's what we're focused on executing. And I'm pretty excited that this is a path that we're on. As I said in the earnings call, we have all those metrics. We're diligently working on them as part of the integration. I'm showing some directional synergy targets that the team has. We're already realizing some of those synergy targets in the second half of this year. Next year, we believe there could be more not only on cost synergy but also revenue synergy. And then finally, the flywheel effect with the [ Skytra ] product, we really implement much higher growth factors here. So all of this is great plans, but none of it really happens unless I have a great team to execute. I'm super excited to introduce some of the team members here, where we're working on a very lean operating model. Chris is running enterprise business in North America for us. Adam is kicking on Australasia as well as the EngineRoom business. And then Melissa stepped up as being our interim CFO. We also have proud to have a global CTO team that brings together technical leadership across Silicon Valley, Canada, Australia and Southeast Asia. And that is important. AI innovation is global. Our customers are global. Our engineering capabilities should be global as well. This structure is designed around speed, accountability and execution. We don't want any unnecessary organizational areas. We want talented people close to the customers globally, close to technology and closer to the results. So that's where we believe we have a huge opportunity. And so anyway, I'm super excited to introduce the team. So I'm going to transition now to Chris, who's going to talk about the North American enterprise business. Chris, go ahead.

Well, thank you, Khurram, and welcome all. Chris Wiegand, and I'm General Manager of North America. I'll let you know, I am an octaheart, and I couldn't tell you how excited I am about this whole AI transformation. It's truly changing things as I'm sure you have in your personal life, but especially in the workplaces., And what's also exciting, just on the tail of that, we've had the best year we've ever had. We've signed the largest deals I'm going to take you through. We've got our 2.0 product deployed and working -- we've got a new module, I want to tell you about in our events. And then Khurram also told you a little bit about the new product beat. So Khurram been telling you all about strategy and where we -- what our vision is. What I want to do for the next 20 minutes, I'm going to tell you through what's happening on the ground. How are we doing our business? What are the customers all about? And most importantly, we've got some live videos that we've recorded to show you the product itself. And then we're going to go through and talk about what's the rest of the year look and how are we going to do it? Okay. So what I really want to emphasize here is there's not names on the page, but these are the largest and biggest companies in the world, some of them. They're leaders in their space. And I'll tell you this. They have gone through super diligent [ Superdigital ] call it. These are some of the toughest RFPs and diligence processes you can go through. And that's how it should be, right? We're working with very secure complex environments. And so by these customers doing this, they've really gone out to market. They have the resources they can choose whoever they want to. And by sandbox trials by many, many questions and answers and meetings, we've come out on top. So that's the pattern I really want you to know, is that we keep winning in the regulated environments, the enterprise environment. And these are, again, some of the toughest places to get your products deployed. So I'll take you through sort of from left to right here. One of our biggest wins this year is a top financial institution. They are actually global. They've got dozens of sites around the world, thousands of users that are going to be coming online. This is actually more than a 12-month pursuit. And again, they went out to market and [ Sky Cavita ]. Next, we have a global asset manager. So we're closing this right now. They're starting at the end of this year. So there's going to be a quick turn on our implementation. Again, 5-figure number of users. Very similar use cases in terms of what they're doing. And again, they're starting with an entire population that we're going to go live with. Next is a leading U.S. insurer. I'm going to spend a little bit more time on this because it's going to tell you about how we deploy. This is an interesting customer for many reasons. One, it's really our bridge to the mid-market. So it's a few thousand users. [ We're ] still in an enterprise environment, but this is how we really took our product and decide and learned how are we going to productize this so we're configuring, not making custom [ code ], and I'm going to talk more about that. And they're going to go live in September. They've got a brand-new headquarters, and we're in deployment and testing for that right now. And let's not forget our amazing installed base. We've got enterprise customers today that are choosing to stay with us, same rigorous environments. We had one of our largest financial services customers renew. We had our largest media and entertainment company. They renewed and expanded. And so where is this all going? Well, this is all leading to more revenue. That's the goal. And so not giving you guidance, but directionally, the new customers are coming online, the things that we're not even seeing yet in terms of revenue, it's about 1/3 uplift. So that's pretty significant when you think about it and in addition to the other things I'm going to talk you through here. All right. So validation is really the key here. You can go win these deals, but you have to deliver them. And that's really what our customers are expecting is exactly what we're doing. So this is the company, I'm going to take you through sort of a quick time line of how we're delivering for this leading U.S. insurer. And again, it's a brand-new headquarters for them. So it starts that we have an enterprise agreement. And this is a very detailed scope of work. We understand exactly what we're delivering, how we're going to do it. and then we go and build it. So with that, we have integrations into their core systems. Remember, the full value of what we do here in [ flow, Sky ] is we're taking disparate systems, and we're putting it all into one cohesive system that an employee can just get what they need quickly and needs, and you're going to see that in the demo. Now we're in testing. So we deployed 2.0 to them. We've got most of the integrations done with a brand-new headquarters. As you can imagine, there are things that are staged. So right in the next 30 days, we've got really important next steps in terms of finalizing, testing. But I can tell you the client is extremely happy. We're right on schedule, and then we're going to scale. And so that goes live to the population. And there's a few really important points I want you to remember here. This is our point that we've really transitioned from custom code. This is not custom development for a customer, this is configuration, which means it goes faster, okay? So this is how we're going to deploy it to the mid-market as well. We've also -- if you've been on our earnings calls before, we've talked about how we're moving away from the big onetime upfront fees to -- and campus fees to per user software. The market is demanding value-based pricing. And value comes from people using the product. So when we deploy it, we expand it through utilization and through people actually adopting the product. So we've got a common goal with our customers to get everybody using it, so they realize value, we realized revenue. And so again, a key message here is that we've taken what we've learned in the enterprise, the really complicated environment, and we're taking that into more deployment and into a repeatable, scalable model that I'll talk you through a little bit further here. Okay. So what I want to also -- as I'm going to introduce you to the products that Khurram has already, I want to highlight a point that we've proven ourselves in the enterprise, and that's revenue. That's great. But what it's also doing is it's giving us the ability to productize what we've done and go down market. So I'm going to work through the product that is out there today [ flow ], the ones that our customers are using to book spaces, to way fine, to interact to get news; this is what's out there. That's what's [ flow ], and we've got this transition now that we've built 2.0 to transition those customers and new customers on to that. All the data that they're creating goes into [ Sky View ], [ View ] is our analytics platform. So this is what's not just dashboards, and this is going to be one of the demos as well. you're going to see it's taking that operational data and turning it into insights. That's really exciting. Next, [ Events ] module. This is a brand-new product. It's coming out in just a few weeks, we'll be [ GA ] in September. And we've solved a major industry problem. And I bet you everybody who works in enterprise is going to recognize this right away. I'm not going to talk about it now because I've got a couple of minutes. I'm going to just go into more detail on that. And then Khurram also told you about new product [ beat ] coming. So [ BEAT ] is really this tool that keeps everything on track, starting with the personal level. This is a productivity tool. And I'll tell you that people working in companies today are overwhelmed with the number of messages they're getting. They've got systems for Jira [ Slack], Teams. They've got things coming at them. It's duplication or all over the place. And it becomes anxiety. They don't know what to do next. So we've created a system that keeps everything moving, keep you prioritized on what's most important next and also prepares or does the work for you to keep the team moving. So stand by for that 1 that's coming in Q4, and we'll certainly tell you all about that as soon as it's live. What I also want to make sure that we recognize is that we've got the same agentic platform driving all of this. So underneath all of this is the [ SkyAgentic ] platform. So this is the thing that's going to really, as you can see here, sense prior like what's the proximity, what's happening? What's the priority, act, [ meaning ] do something for you. That's what a genic means. It's not just giving you a message and reminding you it's actually, in a lot of cases, executing on something and then verifying. So it may give you a plan, you can approve that plan. So what we're going to do now, we're going to go into 2 videos. They are live demos of both [ flow ], we'll call it the [ Nomi ] scenario. This is an employee's view of how they're going to go with their day. You're going to hear me talking conversationally with the platform to do several use cases. That's about 2 or 3 minutes. And then we're going to transition to the next video, which is [ View or SkyView ] analytics. And this is from the manager's perspective. So they're going to be there asking the strategic and insights that they want to get out of the data that they have. So with that, David, if you wouldn't mind, let's go to the video, and I'll see you all back in about 5 minutes. [Presentation]

Okay. I'm so glad everybody got to see that. And I get excited every time I get to demo that. Certainly, it feels like we've got the hot cakes. And I say that because this is how people want to work. They don't want the friction of having to dive into stuff. And even if you make something super easy and user-friendly, you just -- you'd rather ask it through a conversation. So parking lot that, and I'm going to move on to [ events ]. And so this is our newest module. And what we see on the screen here looks like chaos because it is, this is what people are living in the enterprise environments when they're talking about managing events. And I'm not really referring to thousands of people at a large public event. Yes, those are confusing, too, but that's not what we're doing here. What we're doing is we're helping people manage events that are happening at the workplace. They happen every single day in all of our customers, both mid-level in the enterprise. They're going to be all-hands calls. They're going to be sales kickoffs. They're going to be training events. And this is really managing the part that you need a room that you can't request yourself. It's not a reservable space. And so for the people that manage this on the other side, the admins, they're dealing with everything you see on the screen. They're going to get a calendar invite or request. They're going to get an e-mail. They're going to have to open up a ticket in the catering system or even to send an e-mail. They're going to have to send an e-mail or a ticket to security and AV and all of these things and not to me. This is not just 1 room in 1 place. This is happening potentially around the world. in 10 or more places, and they have specific requirements for every location. And so what happens is that the event changes, things keep on piling up and there's somebody there and when we talk to them, they're literally in tears almost because it's so stressful. We're working with somebody that we're going to [ launch ] right now and their quote was, "I am the integration layer." There is no system that brings it all together, which is great news for us because we have done that now. And I believe that nobody has done this before because they don't understand corporate workspace, like we've got robust rules. We already have the user interface. We've already got the integration. So we are so far ahead of that. And so what we leave people with in this current state is high risk. You've got things that have to happen on time. It's like a wedding, right? There has to be food. There has to be a room, there's executives involved, there's maybe external customers. So it's really high stakes, high risk stuff. So what we've done to answer that we've got it all into one workflow. This is all one orchestration. You start with the user requesting everything they need. They can see what's available. they can request what they want in terms of space, catering, AV. It doesn't mean they're going to get it, it has to be approved. So there's an approval workflow, which is the real key here. It's going to send automatic workflows for approval to the various departments that need to approve it. And at the end of the day, you've got 1 system here that's wrapping all that up. So this is super exciting for us because it's an add-on, not just for our customers we have today. We are going to market with this as a stand-alone as well. And we've got campaigns that are starting right now, full demand campaigns. We're also leveraging the engine rooms platform that will help us even further promote this. So I'll talk more about that in a second. But as you can tell, I'm very excited. And so if there's a slide here or a message that I want you to take away today, it's really this. It's the enterprise market for us has proven our model. It's proven our technology. We know we have product markets that we know we can operate in a very complex environment. It's now the mid-market, the scales. And I want to be really clear about something. We are not leaving the enterprise market, we've got great customers, and we're going to continue. I'm sure we're the best in the world when they go looking for it. But as I described, it's a grueling process. It takes a while, but when you win, you win big. So what we've done here is we're taking everything we've learned in enterprise, we've productized it, and we're going to now take this to market and deploy it in a rapid provisioning, okay? So this means that the connectors, as Khurram described, they're preconfigured. They don't have to be built out. They're going to be drop plug-and-play basically. And then we have opportunities we've never had before. This is truly different. We have EngineRoom as their customer base. So we've got, they've got growth-minded customers that this would apply to as well, the products that we're talking about. Not only that, we've got their technology to super promote from a lead generation perspective that we've never had before. We've got resellers that are signed up and ready to go for this, and we've got our marketplace partners, where somebody is going to be able to go into the marketplace where they're already buying software, AWS or Google buy it, start using it. So time to value is extremely fast, which is, of course, is going to result in scale. So an important point about this is that we're not just recreating when we did the enterprise and doing it down market, that would mean hey, we're just doing smaller deals and more of them in the same hard way. It's not that we have productized what we're doing. We can do it fast. We can do it easy and that's what's going to allow us to scale up. Okay. So when I wake up and think about every day, here's our operating principles. And the same goes for Adam, who's running Australia. We now have one P&L. So we've got the same set of metrics for the Board and for all of you as shareholders, EBITDA, bookings, revenue, growth scale. And the way we do that and the way that we're going to do that in our business here is we got to deploy. So we are mid-flight. We've got huge projects going, they're getting deployed flawlessly. We're getting them out there. That's the #1 goal. All those customers I mentioned to you, they're going to get out there. And what does that mean? That means we're going to start generating recurring revenue as soon as they're and being used. We've got adoption. So I mentioned to you events. Literally, everybody we talk to, they have this problem, and it's a burning problem. So we believe that we're going to do a lot of upsells with our existing customers. We're also going to do, as I mentioned, a stand-alone product. But some of our customers -- most of our customers are still on our previous platform, and it represents a great opportunity to enrich their experience but also for upsells and add-ons. So things like Agentic AI and other modules like the events and other things that may not have today, those represent opportunities to increase revenue at the base. Then we're talking about major expansion. This is what I get really excited about. We have everything I just talked about, we've got pipeline deals were enterprise, we've got add-ons, but we've got this new productivity tool at the employee level that will go up and down market. This is something that's going to apply the product beat for enterprise customers. It's going to apply for mid-market. It's going to help people do their jobs better and teams deliver, which is going to really result in expansion for us. So all of that combined by Q4, we're going to have a new cohort of revenue. These are customers that we don't have today, they will be generating new recurring revenue, and that's the goal here. SP-20 All right. So to wrap things up for me, 2 engine has just become one. And I think that's really what Khurram has been talking about today is that we are at 1 company and we are way better for it. So what we've learned in the enterprise we're now taking into the mid-market. I mentioned to you that Engineering already has customers today that are going to be great candidates for us. We're going to use their tools to grow. And really, the whole second part of the flywheel here is engine room. And I think a really important message we also want to get through to everybody today is that we now have a common backbone. So the Sky Agentic AI platform, although servicing very different use cases and workflows. We are leveraging a low-cost model through bonding [ Cortex ] that allow us to deliver maximum value to our customers. And so I'm going to turn it over to Adam here in just a second, and this is great news for us as a company. It's such a lift because Adam already has scale. He's already got profitable growth, and you've got a great product. So I'm excited to turn it over to Adam.

Thanks, Chris. I appreciate that. And a big hello from Australia, everyone joining us from around the world. My name is Adam Laurie, and I'm the co-founder of Engineering and our General Manager of Sky's Australian operations. Speaking personally, [ Andrew ] has been such a major part of my life for 13 years. So I'm really excited today to have the opportunity to introduce it to all Sky shareholders and people are on this call for the first time. So the purpose of today, I want to bring you into the world of engineering, show you what we've built, why it works, give you an understanding of what Sky is acquired. And most importantly, to showcase the opportunity we have to build something collectively bigger together. Okay. So what's our purpose and what are we here to achieve as a business? We use data digital and AI effectively to enable smarter decisions and unlock greater growth potential for our [indiscernible] that's what we do. We are revenue generators, profitable revenue generator for our clients, and that's why they utilize what we provide. We're in establish business, and we have a very strong proven track record. Our Australian base, we serve businesses across the Australasian marketplace at this point in time. We have new history. We'll first established back in 2013. We're multi-award winning across multiple assets, including performance, innovation and most importantly, for any business, our people. What we do as a business, we're fully integrated growth marketing solutions designed to capture high intent demand and drive sustainable profitable growth for our clients. So we have 3 major divisions. We have our March platform, which we'll go through shortly fractional CMO and then marketing as a service. What problem do we solve? And everything that we do always comes back to the genesis of what's our purpose and what problem are we sold in for our business? So why do they want to spend with us? So a business these days has difficulty building a cost-effective and scalable customer acquisition engine. And without customers, businesses should obviously struggle the growth. They are difficultly measuring marketing ROI and demonstrating commercial impact. They have disconnected business, customer and digital data that don't communicate and don't speak. And they have a failure to convert knowledge, data and AI into a commercial advantage. And that's the problem that we solve. We create growth marketing solutions that transform these strategies into measurable scalable and profitable outcomes. We build cost-effective acquisition engines for our clients. We deliver clear, measurable ROI and commercial performance insights. We uniform data strategy and execution into a single source of truth and retransform the knowledge and data into a sustained commercial and competitive advantage for them. The key is also what we do and just as importantly, what we don't do. So in the world of digital execution, there's 2 primary markets, there's awareness and there's intent. Awareness is obviously when I am not aware or I'm not thinking about making a transaction or purchasing the transaction, but I might be induced by a commercial I mean to think about it. We don't focus on that market, we focus on the intent market for our clients. And those are people who are actively already out there looking for a product and service our client. And we do that because that's the most profitable part of a market that a customer can access. They're high-intent customers. They're not necessarily discount orientated and they're high converting. And that's the market that we focus on for our customers. It's also very measurable because it's towards the end of their journey. Why do customers choose us? We have proven results in delivering for over 13 years now. We have cutting-edge technology that powers smarter data-driven decisions. We have solutions that achieve substantial and measurable ROI. We have a fully integrated end-to-end solution profile. and we have unmatched in-house expertise and support. So if we look at the Martech platform that I touched on personally, which forms the foundation of everything that we do and so critical to our success. So our technology is designed to empower marketers, owners and advisers to make data-driven decisions to optimize growth and drives success. We effectively have 3 main parts to our platform. We have strategized, analyzed and optimized. And they're all meant to be interlinked to form a cohesive end-to-end solution. So the purpose of strategize, where are we going? What's the purpose of what we're doing here? So we have context, set the direction define objection -- objectives. Analyze, how are we performing, measure and understand performance, maximize opportunities, identify risks? And then optimize what should we do next? What's the actions that will drive improvement and gain me a commercial advantage. And those 3 parts are all important because ultimately, if you don't have all 3 parts, then you're going to be missing out on the keep either growth. Each module that we then build within the platform has a specific application within those sectors. And we have a whole host of different modules we won't go into detail today, but they have very specific applications that we can pull and draw on as required when we're engaging with our clients or the clients are working through the platform. So what's important to understand about how we utilize AI and how our technology gains a commercial advantage. LOMs understand language. We all know that. Okay. The key with the engineering platform is it teaches AI to understand the business. And that's the key difference. And to do that, we really have to base our AI in a strong foundation. So what we do is we bring in core parts of dark of a business. We bring in their business aspects. So what the goals objectives are? What their brand identity is? We're bringing their customers understand the target market, understand how they're trying to engage with them, understand their commercial advantages. We're bringing information in relation to the competitors, what the market is doing. And then we bring in, obviously, the information in relation to their individual performance. That forms that framework for us. And then when we are driving through AI, it gives us the foundation to effectively produce stronger outcomes and stronger recommendations. And you'd know that when you're using a lot of tools and in the marketplace that maybe use AI very generic in nature and they'll basically say these two business because are in the same sector, want the same things, but they really don't because they're all individual businesses who have different needs, different competitors, different sectors, different profit margins, et cetera. And without that context, it's going to be lower quality insights and we call information. us grounding it in this real core knowledge database enables our customers to gain a single advantage. The other thing important is that when we're using AI, it's a continuous learning application. So we store all this data. And every month that we're storing this data for our clients we are improving the functionality and the output of what it can deliver. So it's a living, breathing, learning tool that enables us to continuously move forward with our clients. And that's a really important part both the knowledge center and the time aspect to continuously gain that commercial advantage for our clients. And that's where you get back to ultimately a prompt an answer versus knowledge and action. So traditional AI, given the prompt MLB like here's the answer that we recommend and it's a very generic component for a generic answer because it's done in the context of everything in every one. Whereas of engineering, we have that specific knowledge, and we have that specific reasoning from learning and that enables us to do a very high-quality actions specific to that client's needs. So today, we're going to show you an example of the platform. So you're going to go through a few modules. The client I'm going to show you is a smaller client, but they're enable us to showcase their data. But it doesn't matter where it's a smaller or a larger client, but the same principles apply. And I'm going to give you an example into just some of the modules in how we apply them and how we discuss them when we talk with our clients. So David, if you look the best plan.

Thanks. Hello, and welcome to engineering. Today I'll see you [indiscernible] in practice through a real customer example. So casing just a few of the platform features we've used to help you form this strategy, optimize performance and ultimately drive their growth. While these smaller customers agreed to share their data, the same principles apply across our entire customer base, including significant and larger businesses. So ultimately, where would we start? We would start with how the business is performing because ultimately, that's what we help them achieve. And we can look at this particular customer and came onboard back in January 2025 were generating a small amount of revenue of about $64,000 a month, and the majority of it was existing customers and a smaller proportion from you. And we can see over the course of the last 1.5 years that they've grown significantly relative to their starting size, about 4.5x in revenue and the majority of that growth is reactor revenue. So they're all good signals. But then if we look back and what does that ultimately meaning in the context of what the business is seeking to achieve, we can have a look at the plans that we put in originally private study. And they're looking to achieve about $1.6 million in revenue and what that translated through to new customers and ultimately, conversions and their priorities and challenges. And then now that we've finished the financial year, we can look back and say, well, what have we achieved, what worked, what could be optimized, what risk could be minimized. And we can see that for all the major metrics being revenue yield and customers, they outperformed the original targets. And if we drill down into more micro information, we can see different elements and then ultimately go how do we maximize these areas. Other things that we look at is things like how are they going relative to their competitors. So if we look at the last financial year. And ultimately, one of the things they're looking to do is gain market versus their competitors. And that's our particular customer, we can see that they're growing and we can look to identify and go, well, who are they actually capturing market share from? That would be important operation. Other things we'll be discussing with them is what's happening in relation to the leads. So if we can drill down into an individual lead, we can see for this particular customer, which aspects are they looking at and inquiring business and which parts of their websites are they consuming to ultimately make a decision to contact them. And then from a macro point of view, we can look at their new customer opportunities, once again, if we have a little bit last financial year. And we can drill down and see that things like. Okay, so what was the main thing they're looking for or what business segments were they inquiring about all these considerations when deciding next phase of the program? We'll also be looking at things like attribution. So once again, if we look at not the last month, the last [indiscernible], we can look and go, okay, or that was their overall marketing investment, and that was the attributed revenue. But then how did that break down for first versus secondary transactions by period in time, ultimately, all the way down the channel, we can look at individual customers, for example, the conversion that journey they talk or the invoice that they purchase with. Also things like which campaigns you were falling better in Google ads, et cetera. relative to revenue and spend. So this is the sample of the things that we look at. There's a old plethora of information on the left-hand side that we could drill down look at. But ultimately, we would determine that on a case best and insight. Thank you.

I hope everyone enjoyed that. So why EngineRoom room and Sky? So -- the CXAI striation, we are looking to be CXAIstriation growth engine. Khurram really touched on that before. We are business that has grown substantially year-on-year that has generated ongoing growth strategies. We target customers who are in that 50 to 500 historical customer range. average client yield is around about $200,000 per annum. We have 93% recurring revenue and average client extends beyond 4 years in life. Our customers across a diversified industry sectors, professional services, home services, manufacturing, industrial, et cetera. So we have a strong diversified mix, which is a great foundation for the next stage of our growth. We have a proven track record of scalable growth. Year-on-year, as you can see over the last 5 years, we have consistently grown and that's profitable growth we consistently move forward with Importantly, for any company, we have a proven team and we have leadership who are staying onboard. We have an award-winning culture, which has been recognized, I think, for the last 5 years and experienced leadership, and we have a very strong specialist capability capacity that who are being retained across technology, AI, data engineering and growth marketing expertise. What does that mean for the future? Well, there is enormous growth opportunity even in the Australasian marketplace. We are in a sector -- we are fortunate to be in a sector that has high growth in all capacity, whether it be [indiscernible] the fractional CMO or marketing as a service. And even in the context of Australia, even though we turn over $8 million the context is that the growth opportunities in Australia are so, so significant. And that's one of the things that is exciting about CXAI and Australia coming onboard, is that it will enable us to hopefully unlock so much of that growth opportunity that we know is about. So what's the next steps from here on the pathway forward? So accelerating engineering with Sky. So combining [ Andre's ] expertise and customer relationships with Sky's Agentic AI capabilities. So we can look to improve -- we already do a semblance of AI, but we know that Sky has strong agent capabilities. And we have the capability or capacity to look where that can be integrated and improve what we do as a business. We will be looking to accelerate our product development, once again, leveraging off Sky's expertise and expand our data and intelligence capabilities. So to that end, EngineRoom Business knowledge plus Sky Agentic AI, we're looking to improve the intelligence, the reasoning and the action outcomes. To give you some context from a development architecture. So at the moment, we have done a lot in the data source of truth and the business knowledge, which I touched on before. And we've started with the reasoning and the decision engine. What we look for in the future road map is to strengthen the reasoning and decision intelligence, but then also look at taking the next step, and this is where Sky's capabilities come into play with agents and autonomous business execution, which we see as a big opportunity for the next steps. So the commercial opportunities, we are strategically positioned to capitalize on key market opportunities that will drive future growth and value creation. We look to expand into new verticals, growth through strategic partnerships and channel expansion, technology innovation to increase customer value, retention and lifetime value, look to use AI to drive efficiencies and scalability and profitability and strengthen the competitive differentiation between us and other people out there in the industry. But as I touched on before, the capacity for growth is just enormous as long as we execute to that high level. So I just want to say thank you. Lovely to meet everyone today. I love we introduce the EngineRoom story. We're very excited about it, and we're very excited about the next steps. And I'll hand it over next to Zoe, who we're going to be doing a fireside chat with.

Hi, everyone. So my name is Zoe Chen. I'm a workplace strategist at Hilton & Company. I spend most of my time inside companies while they're in the middle of changing how they work, not the strategy deck version, the actual version. So it's the park where somebody has to tell 300 people that they're losing their assigned seats and we'll be sharing that in the future. What's really interesting in this particular moment is that everybody in the building is talking about AI, even when the project is about building out the physical space. So I want to give you three things I think are true right now. They are not predictions. They're just what I keep running into, and then I'll invite Chris, Adam and Khurram to ask me some questions. So the first one, Here's what I would have told you 10 years ago, and I would have been right. Automation starts at the bottom and works its way up. That's the pattern. The assembly line, the ATM, self-checkout, the scanners in a warehouse. Machines were good at doing the same physical thing over and over and bad at basically everything else. So the safe advice was get more education, get further from the repetitive stuff and you'll stay ahead of it. That was a real deal for about 40 years, and then this technology showed up and completely ignored it because it turns out the things that took us the longest to learn, writing, analyzing, summarizing, coding, those are cheap ones to replicate now. And the thing that a kit can do without thinking like walking into an unfamiliar room and picking up an oddly shaped object, those are still incredibly difficult. And there's the data on this now, not just anecdotes. Anthropic has been publishing something called the Economic Index, where they analyze millions of real conversations with their AI to see what people are actually using it for, map against the government's occupational database. And what comes out is pretty clear, the heaviest to uses clusters and mid- to high wage occupations, both very low paying and very high-paying jobs show low AI use because those tend to be the ones involving a lot of manual dexarity. The example is shampoos and obstetricians, which tells you something about how little these two have in common, except that both require hands. So it landed on information work, the desk jobs, and it's not creeping in slowly. About half of all jobs have already seen at least 1/4 of their tasks touched by AI. The flip side is that there is a large part of the workforce sitting in a near zero exposure zone, electricians, plumbers, HVAC technicians, mechanics. So if the job requires you to physically be somewhere and put your hands on something, this wave mostly isn't coming for you. But being protected isn't the same as being unconstrained. Think about the 3-truck plumbing company. What's actually stopping that from becoming a 10-truck business. It's not the plumbing. They're great at plumbing. It's everything that happens away from the job site, whether the quote went out the same day or 4 days later, whether somebody followed up on the estimate from 2 weeks ago, whether the reviews are getting answered, whether there is a next job lined up when this one is done. So there's a whole back office of a small business, and it's the part that the owner is least equipped for and probably least interested in. And that's the frustrating bits. There's no shortage of software for them. There is a tool for the quoting, a tool for the scheduling, a tool for the reviews, a tool for the follow-up. But that's the problem. Every one of those needs to be set up, connected to others and baby set by somebody. Nobody started an HVAC business because they wanted to become a CRM administrator. So the choice they've been offered for 20 years has basically been stay small or spend your evening learning the software. And that's what this feels different to me about this wave of tech innovation. The promise isn't another tool to master. It's the outcome without the operating burden. And if that lands, the small operators really can get the back office that used to require real scale to afford. Okay. Second thing. Everyone on this call probably already used personalized intelligence at least 3 times before breakfast and didn't even notice once. Your phone sorted your e-mails before you looked at it. Your news app put out top 3 stories that you actually care about on the very top. Your grocery apps already know that you were low on coffee and your Maps app rerouted you around something before you even knew that it was there. And none of it felt like technology, it just feels like things are working. We've gotten completely used to systems that know us. And when you walk into the office, it all kind of stops. Every -- when every app is doing its own thing, nothing knows you, nothing talks to anything else. As Chris said earlier, you are the integration layer. You are the one holding it together. Now I want to be fair here. AI has already changed a huge amount about how we handle information, notes, e-mails, transcripts, catching up on a meeting you missed, the part is real and people feel it every day. What it hasn't done yet is meet people where they actually are, in the building, in the physical space. The building doesn't know you're in it. The room booking system doesn't know your whole team came in today. Your calendar doesn't know you're on the other side of campus with 8 minutes to get to your next meeting. And this is a part I push back on when people talk about workplace productivity. The exhausting part of the day usually isn't the hard problem that you sign up for your job. It's everything around it, finding a room, doing the time zone math, figuring out who's actually in today, working out where to sit when half of your team is scattered across 3 floors. So every one of these takes 15 seconds and none of them are your job. But you do 40 of them and by 3 in the afternoon, you've burned real mental energy on decisions that should have been made for you. Think about what GPS actually does for you, right? It's not that you wanted a better map. You never wanted a map. You wanted to arrive, you wanted to stop thinking about the path. And that's what people want out of their workday, not more tools, but fewer decisions. And none of this is new, really. Work always lags behind life. It did with the phones in your pockets and it did with video calls. It did with every tool that felt normal at home for years before it felt normal at the office. So people improvise, they find a workaround. They'll use AI on their phones, on tools, nobody bought them because it makes their workday a little better. And nobody made them do that. There was no rollout, no training, no e-mail from IT. They found something that helps and they kept using it, which is usually how you know what's coming. What people do on their own eventually becomes what they expect at work. And right now, there's a real gap between the two. The last one, there is some research that's been getting passed around about how AI pilots don't show a measurable return, and people have taken that to mean that the technology doesn't work. I think it's worth knowing what that study measured. It was an MIT report. It looked at whether a pilot moved the P&L within about 6 months. And a lot of what it looked at was sales and marketing, where 6 months is still mid-cycle. So they were essentially measuring before the thing finished happening. A new hire doesn't move P&L in 6 months either. So it's not a damming finding. It really is just a short window. Within that same study, there's a second number that almost got no attention. When companies brought in a specialist to deploy, it reached production about 2/3 of the time. When they built it themselves, about 1/3. So we're looking at twice the success rate here. And here's why it's interesting. It's not a technology gap. Everybody has access to the same models. You can buy the same capability on a credit card. The gap is entirely in the execution. A few reasons for it, and none of them are exotic. The specialist has done it before. They solve the integration problem, the permissions problem, the governance problem 100 times. The internal team is solving each one for the first time while also doing 17 other things. The tools that work great for you individually often stall inside a company because they're flexible, but they don't learn the specific workflow you dropped them into. And internal projects always underestimate the boring half, the plumbing, the data access, the edge cases, demos run on clean examples. Real companies are nothing but edge cases. That's how you end up in pilot purgatory for 1.5 years. There's also a control thing. Building in yourself feels like control. In practice, it usually means fewer people, slower iteration and a pile of technical bits. But the reason I find this encouraging rather than discouraging is that none of those are technology problems. Every single one is solvable by a team that's done it before. Nobody is waiting on a breakthrough. The capability is here. The practice is just catching up. I'll say one honest thing, though, because I don't think it helps anyone if I only give you the tidy version of the story. By first isn't universal. If you got proprietary data, a general model can't touch or genuinely unusual workflow or in a regulated high-risk situation, building can be the right call. It's just not the default anymore. So three things. The pressure landed on information work, not physical work, which means the businesses that were hardest to grow might be the ones this helps first. And the second, we all got personalized intelligence everywhere in our lives, except the place we spent 40 hours a week. That gap is the opportunity. And lastly, the technology is proven. What's still being worked out is how you put it in, and that's the variable that decides whether any of this pays off. Happy to get into any of it.

Yes. And thank you, Zoe. That's great table setting for us in the context. And we're really lucky. Zoe is flying around probably the world, but I'll say at least the states going to different customers, and she's really seeing what's happening out there. And so I think you mentioned that these are not like just trends that you're reading about, you're actually seeing them. And I was really taken away by a lot of that. So what we're going to do now and just to make this more interactive, we're each going to ask you a question. We have a bit of a conversation. So this is a fireside chat part of things. And we're just going to kind of build on everything you just talked about. So -- why don't we go in the order that you started from? And Adam, you're the expert on trades and with your business. So go ahead.

I think you guys call home services over there. And Zoe, thanks for the chat, and I look forward to you taking the short flight over to Australia at some point. My question is trades and home service businesses generate enormous amounts of operational and customer data every day. Where do you see the biggest opportunity for AI to turn that data into better decisions and ultimately, better business outcomes?

Yes, that's a great question. I think the thing is the data is all there. That's the thing. Every job a treat business does throws off information, right? What broke, what it took to fix, how to actually get customers, what -- and it actually worked. But it's scattered. It's in a scheduling tool in a text spread, in a stack of invoices in somebody's posted notes, a fair amount of it is just in somebody's head. So the person -- also the person who has to pull all of that together and make sense of it usually is the owner who might be on the roof all day. And if it happens at night or if it happens at all, it's not really analysis at that point. It's whoever is still awake trying to remember whether the job was done successfully. And I think that's the gap. It's that the data exists, but nobody in the business has the bandwidth or the training sometimes to really sit with it and find the pattern. And the patterns are also right there, which jobs are actually making money once you count the drive time callbacks and things like that, which estimates are consistently wrong and by how much and what kind of work you should be taking more of and which you keep saying yes to out of habits. And I think that's the opportunity. It's maybe less fancy or exotic than it sounds. It's just showing a business what it already knows that has never been able to see in one place and turning that into something they can really act on, on Monday morning and for this to be not something that just relies on the owner. But as the business grows and scale, it could become shared understanding that the team can mobilize together on.