Thank you for standing by. Welcome to the Appen Limited Strategy Refresh and Capital Raising. All participants are in a listen only mode. There will be a presentation followed by a question and answer session. If you wish to ask a question, you'll need to press the star key followed by the one on your telephone keypad. I would now like to hand the conference over to Mr. Armughan Ahmad, CEO. Please go ahead. Thank you, Rachel. Good morning, everybody. Thank you for taking the time for joining us today. I'm here with our Chief Financial Officer, Helen Johnson, along with our Senior Vice President for Strategy and Innovation, Ryan Kolln. Thank you for taking the time. I want to just run through some opening comments, and then I'll walk you through some slides, if that's okay with you. I will call out the slide numbers so that you can all follow along. Just opening comments. If I have not had a chance to meet with you, been meeting with various investors. The last time I was in Sydney, which was in February, and then now over the last few days, meeting with various different investors. I look forward to meeting some of you in person in the coming weeks. Just want to give you a little background on me. I've been in the tech industry for the last 27 years. I've worked for companies like Dell Technologies, Dell EMC. We took Dell private and then public again with Silver Lake Private Equity. Also was at HP before that. Previous to that, I was with 3Com. It was Bain Capital. We also turned around 3Com with a Huawei 3Com joint venture and then sold that to HP. I've done a few of these turnarounds in the past, and I feel like this is an exciting turnaround at a very exciting time for generative AI. I really think that Appen, as I've joined Appen four months ago, and Helen, you just joined Appen two weeks ago, I believe 10 days ago, along with Saty Bahadur, our Chief Technology Officer, who's just recently joined as well, we're all coming from the tech industry, and we all felt that there's a phenomenal opportunity here, especially with the advent of generative AI, along with our current deep learning AI work. That's important. First things first. When I joined here four months ago, I really looked at the broader business and felt that the cost base was not under control, and we had to act very quickly. The first four months have been pretty busy, I would say. We have made sure that we have tried to, one, ensure that we cut the fat out of the OpEx, which we have now taken $46 million worth of OpEx actions. When I say actions, this is not just something that we're saying we will do. We've already done it. We're not cutting into the muscle. We're just cutting into the fat. What I mean by that is that we had invested ahead of revenue in many of the areas, and we now need to make sure that we are bringing our OpEx to revenue ratio in check for our global business, our enterprise business, our China business, our federal business, along with, you know, our product divisions and engineering divisions. We want to make sure that we are running a profitable business. I'm thrilled that with the actions that we have taken on the cost out and now with the equity raise announcement, we really think that we are going to finish the year with cash EBITDA positive. Not think, we will, I should say. The last few weeks have been really positive for Appen. I'm starting to see really great green shoots coming from our deep learning AI type global customers. Those are the big Apple, Microsoft, Meta, Google, and Amazon of the world. They make up almost 80% of our revenue. If I take out our number one customer, our revenue for the last four years has grown at 10% CAGR growth. We had seen some challenges, unfortunately, over the last two years with our number one customer, with their shift into newer use of generative AI along with search relevance, which has now started to see our revenue stabilize with them. Now as of late, we have started to see great green shoots where they're, our number one customer, is now giving us newer revenue and newer projects, also consolidating some really great business to us away from some of our competitors. I feel like that's a very positive thing that we're driving. We also feel that as part of our cost out, unfortunately, we had to impact on nearly 300 people out of our 1,504 person organization, along with our hosting cost and some of our recurring costs on our engineering assets. We've also made a decision to move our, a good chunk of our engineering to India and Hyderabad to ensure that we have lower cost areas to ensure that we're keeping our costs under control. I'll also say that our business is moving in the right direction with the right capitalization that we needed. That's helped us to really move our relationships to the next level with some of the largest system integrators in the world, but also some of the big tech companies like NVIDIA, for example. A few weeks ago, we announced NVIDIA, which has a $700 billion market cap USD. They represent almost 80% plus of the AI chipsets in the market, have decided to go ahead with Appen and our datasets in their conversational AI solutions that they're providing with their own large language model, which I'll refer to later. We've also announced a partnership with Reka. Reka AI, if you're not familiar with, are the AI researchers for Google DeepMind, as well as Meta's LLM, creators of Google Bard, creators of Meta's LLM. They have gone out and started their own on-premise large language model similar to ChatGPT, and they've decided to also partner with us. Our goal, as I said earlier, is to finish the run rate cash EBITDA positive. You know, even if let's say we don't foresee that, but if the revenue volatility remains, we are committed to adjusting our cost further. Helen and I call this our dynamic approach of making sure that we keep ourselves in a healthy, in a healthy area. We're excited to go on this journey. Before I go through the slides, I just wanna tell you, I made a decision to join Appen to run a AUD 300 million circa company. There was a reason for it. I left KPMG at a senior partner, president level. I worked at all of these other companies that I told you, managed hundreds of millions to billions a dollars P&L. If you take a look at my compensation and Helen's compensation and others, we are all very clearly geared towards improving the share price. That is what our KPI metrics are, set by the board. Almost 50% of our stock will only vest if we improve the stock price 190%, which takes us to AUD 7.63. If you improve it by 320%, it takes us to AUD 11.25. I would say my compensation and my leadership's compensation is fully aligned with the investors who decide to invest with Appen. I would like to now walk you through a few slides with the pack that we have all provided you. If I could have your attention go to slide 10, please. I find that in the key findings of my operational review over the last four months, these are the areas that I've really touched in the business. Across sales and marketing, I felt that we were a very reactive sales culture, we needed to pivot ourselves to proactive sales culture, especially going after, you know, our big five global customers that we have, along with the Fortune 2,000 large enterprises. We felt that we needed to move away from selling to a data scientist, which is 10th level below the CEO, to really go and so start selling to the C-suite and make sure that they understand what's required. In the coming days, I'll be announcing a new Chief Revenue Officer for the company. We haven't had a role like this at this company because we have relied on, you know, our customers, and we feel this is the perfect opportunity for us to provide that opportunity. I also feel that the leadership and the culture is very important. People like Helen, who ran a $9 billion business for a very large solutions integrator in North America, and Europe and Asia, Insight, which, and she ran the North America CFO role there of $9 billion out of $11 billion P&L I believe, revenue company. As well as Saty Bahadur, who left Upwork, who is, who's got a good relevance to our crowd type of platform. He was running a 1,000-person engineering team there as their Head of Engineering, has left there and joined us to lead a 130% team, which I've now asked him to reduce and then, you know, grow in the right areas. He's super excited. He was previously with Amazon Alexa AI, along with, he was the head of engineering there for Alexa AI platform and then previously at Microsoft and Intel there. We have Sujatha Sagiraju, who was 20 years Microsoft, she's MLOps. She ran MLOps, so machine learning operations there. She's, she had joined us almost a year ago, I believe, to lead our chief product officer, and she's amazing at driving that. You will see a chief marketing officer announcement as well in the coming weeks that we're going to drive towards, which is important. I also wanna just highlight on this slide 10 around transformation, which is, you know, I really have felt that our product engineering have not delivered the roadmap that we needed to deliver. I hope you will join me on May 26th at the Barrenjoey offices, where we will be hosting an Investor Tech Day to showcase some of our products, and you'll get a chance to see Saty, Sujatha, myself, and our leadership team there. That's how fast we're moving. You'll get a chance to see some demos. As I said, you know, cost controls are going to be important. Global business has been profitable for us. China is getting to profitability. We feel by the end of this year, we're going to be positive in China as well. The areas that we need to fix is really our enterprise area. As I mentioned, if we take our top one our top customer out, we've been growing at 10% CAGR growth, and even the first customer is now adjusting. We feel that our second half will be better than first half. I know we've said this to you before, where second half was always better, but in this case, we're actually seeing how we have readjusted the revenue base for the company, that we feel like, you know, we're now seeing green shoots over the last few weeks in these new areas that I'm really positive about. Even in this generative AI area, which I'll walk you through, we've seen 32 new deals in our pipeline, which is a very positive sign. If I take your attention to slide 11. Slide 11 is what I told many of the investors when I first met them, when I first started and did our earnings announcement and our annual results. I told you these are the few areas that I wanted to focus on. I'm a huge believer of say-do ratios, and we started with operational rigor. We said we were going to put a business management system in place. We said we were going to do a zero-based budgeting exercise from bottoms up. We have done that. At that time, we told you we're gonna take out AUD 10 million. Since then, we've been really busy. We felt that we really needed to get our costs under control, we've taken out AUD 46 billion. That's nearly 300 people. In product velocity, I think in February when I told everyone that we're going to be moving into generative AI, we announced some of the generative AI products like RLHF, reinforcement learning with human feedback, a lot of people were questioning what that meant. I think thanks to ChatGPT and everyone talking about generative AI, they now understand exactly how Appen is relevant there. Those products that we launched have actually given us really good... Those 32 deals that I talked about is exactly that from our global accounts, along with our enterprise accounts. We're also, as I mentioned, reducing our cloud vendor spend as well as our engineering offshoring, to ensure that our product velocity continues to remain fast. Workouts go-to-market, that's the area where I give myself a yellow. I feel like the last four months have been full on trying to get this business under control, with the right type of cost base, as well as the newer partnerships and newer customers. Now we need a CRO to build a consultative sales go-to-market and elevate our brand, for both from a B2B perspective as well as the B2C perspective. Ecosystem partnerships, I said I was gonna go do, and we have delivered NVIDIA and Reka. Those are announced. You know, PwC, Deloitte, Amazon, AWS, Google Cloud Platform, Azure, have also become partners and customers, who are already delivering work with us, which is great. We're not at a point that we can start announcing those, but we're now seeing those as our customers and partnering with us in the right direction. We're mixed, I would say, on the progression of the certain verticals. Automotive vertical is advanced, but we need to really get going on financial services, retail, and other areas. Finally, AI for Good. I think the crowd code of ethics, and ensuring that I'm leading now the chair of our AI for Good committee, to ensure that we're driving responsibility by design is important. If I take your attention to slide 13, please. This is just explaining that how Appen is focused on deep learning AI, which is our traditional side of the business, along with generative AI. I would tell you that there is a bit of a misnomer. I've met with a lot of investors, and I think the market feels like we're an annotation company, or data labeling company, which that could not be far from the truth. Almost 70%+ of our revenue comes from relevance side, which requires human in the loop, and that is what's delivered through our crowd, but also delivered using our AD AP and Appen Connect platform, such as relevance, in relevance, search relevance, content moderation, ad evaluation work. Data collection is a smaller portion of our revenue. Data annotation is a much smaller portion. Relevance is the biggest portion. That relevance portion is exactly what's needed in generative AI now. The relevance is done by human feedback. That is what's required now in fine-tuning of these large language models, LLM, that we came from the language background with Julie Vonwill er founding the company 25 years ago as a linguist researcher at University of Sydney. That language piece is super important to our customers. Instructional data sets, model evaluation, all of that is done by our customers wanting to have different type of crowd, people who are teachers or people who are financial professionals or people who are gardeners, for example. How do they create those prompts so those prompts can then provide the fine-tuning of a LLM? You may think what an LLM is. ChatGPT is a brand name version of an LLM. There are other LLMs. NVIDIA makes their own LLM. Cohere has one. Reka has one. Bard, Google Bard is an LLM. All of them are now asking us to now do a lot of that fine-tuning work, which comes from our relevance area. The other area that I'm super excited about is the far right of this, is our assurance work. We're now finding that a lot of the top enterprise clients or customers of ours are looking for assurance services from us. This is after they have trained or fine-tuned the LLM. They're asking us to do the certification and monitoring benchmarking and A/B testing of that work, and we feel that allows us to further entrench ourselves. If I take your attention to slide 15, we will go into a lot more details on this, but the main moat for Appen has been our crowd and our Appen Connect and Appen ADAP platform that came through our Figure Eight acquisition. I feel like to leverage these large language model-based models, our customers are calling us to do a lot of this, not only fine-tuning, but also assurance. This is a great flywheel effect that we have created where, you know, it doesn't matter if it's NVIDIA, Cohere, Reka, OpenAI, Anthropic LLM, all of our customers are in need for this block that comes on top of it, which is us providing first instructional data sets, RLHF. That's the first stage with the customer on one project. The second stage becomes RLAIF and model evaluation, which is reinforcement learning with AI feedback. Model evaluation is, for example, if you need NVIDIA to do the contact center work, LLM. You need Reka to do a KYC type of LLM at a bank. You know, you could use Anthropic, Cohere, OpenAI in different ways. You could put it on a public cloud like AWS, Azure or Google Cloud, or you could put it on premise. Again, you would need fine-tuning, and you would need, more importantly, assurance products. We have now seen PwC at Deloitte, their risk and compliance teams, approach us and not only become clients of ours, but also are now using our services to provide assurance, risk assurance on LLM, and compliance assurance, which is to remove the bias, toxicity, and hallucination. If you go to slide 16, please. Slide 16 provides you how we are planning to go to market. Before we were waiting by the telephone, if I can still use that analogy, of having that telephone to ring and for orders to come in. Now we're becoming a lot more proactive with our enterprise customers. That's why we're building an enterprise sales team. We're working with our ecosystem partners to get out to the market. When I got the call for Appen, I did not know who Appen was. When Helen got the call for Appen, she didn't know what Appen was or Saty, when our Chief Technology Officer got that call. That's what we need to fix, so that Appen becomes much more of a synonymous name in the enterprise. That also helps us unlock our TAM. We really feel that in generative AI alone, it's an $8 billion TAM that's growing to $110 billion by 2030. We feel that's gonna be super relevant to us. If I take your attention to slide 17. Slide 17 is a example of when I mentioned that we had, I stand corrected, I think I said 32 deals. It's actually 36 deals that are in our pipeline. These deals look something like this. A global client of ours is giving us opportunities to now not only code, but also we're now delivering evaluation model performance for text-to-image generative AI models for many of the very big customer of ours, so which has been a great green shoot for us. We're now delivering that work. Another example of a customer is a very large One of the Big Four in professional services, who's now given us an AUD 2 million-AUD 5 million opportunity that we're executing on creating large language prompts for them. A very large bank has partnered with us and Reka to build out their knowledge management solution on premise because for regulatory reasons, GDPR reasons that they require that. If I take your attention to slide 24, is the leadership team. I mentioned Helen, who's recently joined us. Sujatha, I mentioned earlier, built Bing and Azure AI platform. Saty, who recently joined us from Upwork, before that, designed Amazon Alexa AI platform. Ryan Kolln, who's based out of Sydney, is now moving. He's been promoted to lead our strategy and innovation for the organizations moving to North America, that we have a whole brain trust that is executing towards where majority of our revenue comes from. We will also be announcing, as I mentioned, a Chief Revenue Officer and a Chief Marketing Officer. That would be a team. I also felt that what is the point of this, right? The tech pedigree, high-profile, large companies, why are they choosing Appen? I would ask you to maybe pause and ask that question. Why did Armughan join Appen? Why did Helen join or Saty? Why is Ryan Kolln, ex-BCG, ex-Telstra executive, AT&T and others, why is he staying at Appen, right? It's all because we see the opportunity, and we feel the, you know, where the stock's at and where the opportunity is with the TAM is tremendous for us. If you go to the next slide. Also Roc Tian, who is from China, and he runs our China business and our South Korea and Japan business. He's done a fantastic job. Our China business has become number 1. Our main competitor is SpeechOcean, who has similar revenue to us, has an AUD 1 billion valuation. We now have all of the hyperscalers as our customers in China. Most of the top enterprise organizations like China Telecom and others have become our customers there, along with some of the top 8 automotive manufacturers have become customers of ours because they need the data relevance work to provide self-driving solution. Slide 25, if I can go there. To me, I can say all of these things to you, but I would like to maybe share just a personal perspective. My background is, you know, I grew up in a very underprivileged environment in Pakistan until the age of 15. For me, being purpose driven on solving income inequality is a huge passion of mine, and I feel like purpose is super important to every human that is working at Appen. It's, if you're not working at Appen, you're an investor. I'm sure purpose is very important to everybody. It's very important to me. We felt that we needed to really set a culture code at Appen. Purpose is we are unlocking the power of AI for good to build a better world. You know, AI is going to take a lot of jobs away. We wanna ensure that we're creating a lot of jobs using our crowd, we feel that the crowd's going to morph into, especially after COVID, so many people who are wanting to work from home and not wanting to come into an office, they'll have a great opportunity to use our platform in different ways. Perspective is we are learn it all culture. I fundamentally always tell my team that I don't wanna be the smartest person in the room. I'm not a know-it-all. We are a learn-it-all organization, we embrace that comfort and growth do not coexist. Right now, Appen's going through some uncomfortable moments and, you know, that, I think failure, struggle is formidable. The good news is we've got a great team, not just my leadership team, but the team that is here at Appen are really embracing this culture. The organization had become a bit lethargic, and it's now moving in this next direction, which we're really excited about. If we do purpose and perspective really well, we feel that leads to prosperity. These values that unite us are being customer obsessed, thinking about the customer day in, day out. The customer says, "Get it done for me." Let's not do that in two weeks. Let's do it tonight or tomorrow morning. Courage to innovate. You know, this RLHF, RLAIF, many of the products that I mentioned earlier, those are super important. That's how our engineering and our delivery organization is executing. Being very action-oriented. I'm a big believer in finitives. I find initiatives are interesting. Finitives are much better to finish the initiative. Finally, winning together, you know, and not being in silos. Finally, if I can take you to slide 26, I'll end with this and turn it over to Helen to talk about an important slide for financials. Is the turnaround scorecard going forward. I told you what my say-do ratio was back in February and now what you should be measuring me over the next six months. It gives you a very clear roadmap on operational rigor, exiting the year underlying EBITDA, cash EBITDA profitable, reducing our costs if we need to. We'll continue to adjust our cost base sales, product delivery structure. We're moving away from a from a business unit structure of globals and enterprise, and we're integrating into a much more of a sales product delivery structure. Product velocity. These are the products that we're going to announce. You will see that on the 26th of May, when Saty and Sujatha are here to showcase that to you. I hope you will join us. Workouts go to market. My aim is to have the CRO here as well, and I introduce you to him. We're actively going after the market and building pipeline. Our ecosystem partnerships, you should check to see how we're doing on that. That's going to be super helpful on how we're going to drive this change. Finally, AI for Good, which is. This is not just anything. To me, it's very near and dear to me on ensuring that we focus on the ES and the G part of ESG, which is purpose, perspective, and prosperity, as I mentioned. With that, if I can maybe turn it over to Helen, please. Yes. Thank you, Armughan. I'll direct you to slide 22. I really wanted to recap what Armughan said a couple of times during the call and see if I can't frame up crisply where we are on our cost reduction efforts. We announced last week that we're undertaking a cost reduction program of AUD 46 million. I wanted to take you through the components. As Armughan said, there's about 300 positions in our organization that are impacted by this action. We started that program just last week. The majority of those actions have occurred across our footprint, across North America, China and our various business units. The balance of them will happen over the balance of the year, really completed by early December. The pieces that are yet to come are the strategic decisions that we noted around consolidation of our go-to-market and delivery organizations in the United States. That we believe could provide an opportunity to get real synergies in the way we think about sales process and onboarding and productivity of our delivery resources. The second piece is standing up our engineering support resources in Hyderabad, India. That's yet to come over the next couple of quarters, and we wanted to make sure that you had a path to thinking about how we're realizing against this program. What we did say is that we expect to exit the year at AUD 113 million of cash-based expenses in the business. In the short run, we believe that these cost reduction efforts, one, they right-size our cost structure to our revenue plan for the year and for the intermediate term. Then the capital raise that we're doing today really supports fortifying our balance sheet so that we can execute against the strategy that Armughan just laid out. These cost savings were identified as part of our strategic review of the business over the last handful of months. It was not. It was a zero-based budgeting exercise that the organization undertook to really rationalize the level of cost that was deployed in the business to support the very specific revenue streams that we have today. At the same time, make room so that we can invest in the future, where we're headed for generative AI and really how we intend to invest in our sales and marketing organizations to make sure we realize on the opportunity that we have ahead. I think with that, I will open it up to the audience for questions. Okay. Rachel, are you able to open it up for questions? Let's see who has the first question, please. Yep. Thank you. If you wish to ask a question, please press star one on the telephone and wait for your name to be announced. If you wish to cancel your request, please press star two. If you're on a speakerphone, please pick up the handset to ask your question. Your first question comes from Bob Chen with JP Morgan. Please go ahead. Morning, guys. Just a few questions from me. Just on the cost base, you know, obviously significant cuts this year, but you've also made some comments about reinvesting around the go-to-market and the sales and marketing. How should we think about that reinvestment going into next year? Well, we intend to keep our cost base aligned to the revenue trends that we're seeing in the business. The cost takeout contemplated some reinvestment in the business and we'll that will accelerate that opportunity as, you know, revenue performance improves. You, you should expect that it's incorporated. Okay, cool. I think, Armughan, on your comment earlier around, seeing signs of stabilization with your top customer, can you give us sort of a rough split of how much they sort of contribute to your revenues now and what signs you're seeing that gives you that confidence that the sort of decline in revenues is stabilizing with them? Yeah, great question. Unfortunately, I'm not able to give you exactly revenue numbers, but I'll give you just directionally, the comments that I made earlier is that we're seeing our revenue stabilize there. We're seeing newer, generative AI as well as deep learning AI type solutions, from them. We're also seeing that we're now starting to win business away from our competitors. Okay, great. Just finally, with some of these newer, relationships with Reka and NVIDIA, I think you outlined a couple of sort of green shoot programs, but can you talk a little bit about sort of the revenue model or the business model there? Is it sort of, incremental projects that you're working on, and, what's the revenue contribution we might see from these opportunities? Yeah. Great, great question. I think I would like to direct you to that slide that I showed you. It goes there. It's slide 15. If you think about how that works is that we see different stages with different customers. Just like, you know, when we do work with Google, Meta, Apple, Microsoft and others, right? Amazon is they do multiple projects with us. Just like that, we're now seeing enterprises do multiple projects. For example, they'll start with instructional datasets and RLHF, then they'll move to RLAIF, then they'll ask us to do the model evaluation work. Once that's done, that becomes fine-tuning phase. That's like two, three phases just to do fine tuning. That's just in the contact center area of a bank, for example. You have the KYC area, then you have, you know, retail banking, then you have open banking, open payments, right. There are areas that we can go after. There's multiple stages, and then there is a stage of assurance. How do you do the monitoring and A/B testing? We feel like, you know, enterprises, you know, we wanna win a customer for 10 years. You know, in AI, I don't believe AI becomes a recurring revenue business. I believe AI becomes a repeating revenue business where you go in and win a customer, and you do a really good job in these areas, and that's how we have done it. It's been a repeating customer. Some of our top globals have been our customers for a decade plus, that's what we want to do now in enterprises as well. Great. Thanks, guys. Yeah, pleasure. Thank you. The next question comes from Josh Kannourakis with Barrenjoey. Please go ahead. Hi, Armughan. Hi, Josh. Helen, thanks for taking my question. Just one regarding the your new set of the LLM data products. Obviously, if we go back in time, Figure Eight, you know, was bought that was targeted at the enterprise segment, obviously too early. Just to help people understand, what is the step change here in terms of, I guess, the market's readiness to take on these products? Like maybe you can just reference, you know, in terms of the open source nature of these algorithms, like how that's leveling the playing field for guys like you to, you know, be competing for guys like Reka and things like that in the market. Keen to talk about the opportunities there, who some of the key players are, and your competitive advantage. Yeah, no, that's a great question. Thank you, Josh. You know, I would tell you that these LLMs are fast becoming, you know, available by everybody, right? Because it's a foundation model, and it's a large language model. How do you train it becomes your differentiation. You know, a lot of our, you know, we obviously have these public LLMs that, you know, people have LLM models, like NVIDIA has that they're now shipping in their conversational AI box with GPUs and their own software. They need our datasets as part of that, instructional datasets. As the customer deploys it in their contact center, then they'll need to fine-tune and assure it. In Reka's case, Reka is more, you know, going after a market where people, even if they have a VPC, a virtual private cloud, think of a bank, think of a large retailer who has their own private cloud who's using Azure or AWS or GCP. If they use OpenAI with Azure on it, their data still uses the base LLM, which makes OpenAI better, right? Reka is going after that to say, "We wanna keep it on premise, either on premise on an NVIDIA box or on premise on a VPC, private cloud." They get to own the LLM, meaning the customer gets to own the LLM. We're seeing that then there are public LLMs, open source LLMs that are now coming out, right? Where they're again going to need fine-tuning products and assurance products. Our view is that, we become relevant regardless of which LLM, you wanna use, if it's OpenAI or Reka or NVIDIA or Cohere, Anthropic. That's, that's our differentiation. I think, Josh, it's also important to note that, when I said something earlier, where almost 70%+ of our revenue in deep learning AI comes from the relevance side, and that requires a human in the loop. In this generative AI, in order for you to do the fine-tuning, you need the human in the loop, and that is our differentiation. You obviously need a much different subset of different humans, and that's why our Appen Connect and Appen platform, that came from the Figure Eight acquisition works really well. After that, assurance products is what we are now building. We will show you a few demos on the 26th. We're doing a tech day and an investor day to show you how assurance products will work. It's not just fine-tuning, it's also assurance products. That's why we feel it's much more relevant. Did that answer your question, Josh? Yes. No, that's really helpful. Just as a follow-on to that, if we think about, 'cause as you mentioned, of 70% of the correct, you know, relevance work with the crowd already. If we look at the sort of the economics almost of some of the work within that category versus the generative AI category, how do you describe that in terms of comparing, I guess, the economics of those projects as you're sort of obviously just starting to price some of them up now? Yeah. I'm gonna have Ryan start, who's here with me, and then I'll add on to that. Yeah. Hi, Josh. We're starting to see some greater specialization and the need for the, for the type of crowd, and that comes with a different set of economics that's, you know, going to be favorable for us. We're also seeing, you know, like what, relevance has been for us, very, ongoing in the nature of the type of work. The need for generative AI, we're starting to see that ongoing need. We expect it to be, you know, a very, very positive business for us, like relevance has been for a long time. Yeah. I would just add on to that, Josh, that based on what Ryan said, that I think we're winning generative AI projects and deep learning AI projects in the global accounts. We have lately seen a lot more generative AI projects in addition to our deep learning projects. you know, our number two customer has also, you know, continued. It grew for us 20% last year. It's continuing to grow. In the areas of generative AI, pretty much the top out of the five, I would say the top four have given us business in generative AI. In the areas of enterprise, as I mentioned, we've got almost 36 new LLM based generative AI projects across different sectors. you know, we're seeing the demand move really fast. We're also working very closely with IDC, which is a very large tech analyst firm, industry analyst firm. IDC, Forrester, Gartner, they're all in the same bucket. I think this area is moving so fast that they're starting to sort of, you know, put their numbers on it to see what the TAM looks like. You'll see more from that as well, upcoming on the 26th. We'll share more about that, but where how a third-party industry analyst looks at the space. Got it. Thanks, guys. I'll jump back into the queue. Cheers. Thank you. The next question comes from Darren Leung with Macquarie. Please go ahead. Good morning, guys. Thanks for taking my questions. I've just got two, please. The first one was just an extension of an earlier one just around the cost base. You know, it's obviously been well documented around, you know, softening macro conditions and the amount of cost reductions that your largest customers are going through. Can you give us a feel as to how much flexibility is left in that AUD 113 million cost base? You know, if I suppose the go to market strategy doesn't come to fruition or if there's other sort of costs that need to be reduced, please. I'll have Helen take that one. Sure, sure. The cost base is largely variable to the delivery of the revenue. As we are seeing revenue trends decline, we'll rightsize, if we need to, our cost base. I think that this was the appropriate action at this time, given current visibility in the pipeline and plans for positioning in the generative AI space. Certainly what this business has operated at a level of profitability, seven or eight years ago, a $60 million business was running at 16%-18% EBITDA margin. We know that we could operate this business at a smaller scale with more profitability, and obviously have a bit more scale as we grow. That is not what you saw over the last couple of years. We grew notably, but the cost outgrew the top line. That will not be the model operate under going forward. That's something I've mentioned in my prepared comments earlier, where we want to make sure that we are staying on top of our cost on a regular basis, right? Helen and I are used to running our 13-week shop, which is week one to week 13. Our sales teams and others have to give us commits on week six and week 10, we want to make sure that we're running a stabilized cost base. If we have to take additional cost out, we will take additional cost out to ensure that we are profitable. Well, understand. Thank you. My second question was, you know, if we think about what we've talked about so far, you know, it's, it looks like it's green shoots into second half in relation to those enterprise customers, new products. You know, as you've rightly pointed out, the second half has a seasonally stronger skew, presumably revenue accelerates into next year. You've done well on the cost out program. I suppose my question is, why raise equity now? Yeah. Listen, I, you know, as I take a look at, the revenue base of where it is and where our profitability is, you know, as we take the cost out, the cost is a run rate cost out that we're trying to get to, right? This is not all just coming out in one day. As we do that and we have to run our P&L, we have a debt facility available. We want to make sure that, you know, as we draw on to any debt facility and others, that we're giving ourselves enough room to maneuver. As I talked about, I need to, you know, invest in sales, marketing, and others. We want to do it in a prudent way, to ensure that while we're doing all of this and ensuring that as we leverage our debt facilities, that we stay positive. Anything you want to add to that? I think I would only add that we did have a benefit in our working capital trends in the first four months of the year. We have a slightly inverted cash flow cycle, and with the decline in revenue, we did see a benefit in cash growing despite the EBITDA losses in the first four months. As we revert back to growth in the second half, we have guided or given directional input that we expect to be up in the second half. We'll use a part capital there. With that working capital benefit unwinding and just really ramping up to the run rate expense base at the end of the year, this is the right amount to position us solidly to get to that and have some cushion going into next year. That makes a lot of sense. Thank you. Thank you, guys. Thank you. The next question comes from Garry Sherriff with RBC. Please go ahead. Good morning. Hi, Garry. Armughan and Helen. How are you? Good. Doing well. Good morning. Two questions. One on the go-to-market and the second one on the pipeline and revenue visibility. If we start with the go-to-market, it certainly sounds like that market strategy appears to be shifting. You talk about expanding the partner ecosystem. Can you maybe just remind us, your direct sales force in the U.S., you know, how much of your revenue is generated by them? What are the plans going forward from a growth or otherwise perspective from a direct sales force? Secondly, the shift to the indirect channel. I just wanna maybe sense check who you're partnering with and how you get that indirect channel firing. You know, how do you measure the effectiveness of those partners? Any color would be appreciated. Yeah, Garry, I would tell you that the sales organization that I've assessed here is not a sales organization that I'm used to in the tech sector. It's a very reactive sales culture. You know, it's more of the customers reaching out to us and us reaching out to customers directly. It's not a much more of a focused on how are we going after it based on different regions, what's the C-suite executive, what's their pain point, and then driving it that way. It's pretty much all direct sales at this time. There's no channel sales motion at this time. That's what we're trying to create, right? Multiplying our feet on the street. You know, obviously, we can't build an empire of a sales organization. The CRO that I'm hiring is very focused on... He's done this for different companies in cloud native world and data world, where basically built out revenues from zero to like upwards of $700 million, right. Without building out a huge cost base of sales. That's why we feel that, you know, using a channel go-to-market. By the way, Helen used to be my channel partner in a way at Insight, right. When I was at Dell EMC, they were a huge systems integrator or solutions integrator now. I think like, I know the current CEO of Insight, Joyce Mullen, they used to be the previous colleague of mine at Dell, previously Ken Tsunoda. They were huge channel partners. How Like, when you think about how big your sales force was, right. We would multiply the sales force at Insight. It's the same kind of model we wanna create here. The sales organization here is what we have to upgrade to ensure that they have the credibility and the relevance of what I have done or what, you know, what others have gotten used to like Helen in the past. That's what we have to create here, Garry. Yes, understood. In terms of those targeted partners, or is it even too early to say, like, are you targeting the system integrators? You know, is it cloud providers? Have you gone down that path yet or you're effectively waiting still for the CRO to start? Yeah. I would tell you there's a slide in here. Let me just go to that slide one second. That actually talks about the go-to-market slide. Slide 16. If you go to that, it'll give you a bit of a better understanding of how we're thinking about it, right? We have system integrators and IT consulting firms like the Deloitte and PwC that I mentioned. You have, you know, NVIDIA of the world that become much more of our compute partner. We have AWS, Azure, GCP that we are partnering with to take that to market. You have the LLM companies, the Reka of the world, so Cohere of the world. That's how we're, that's how we're already engaging and working with them. We just need to, you know, get a CRO, strategic alliances person and others to start to now do that, right? This is just all me while I'm trying to do all of this other stuff. Just imagine if you have a lot more of Armughans running around, what we will be able to accomplish. I hope you guys would feel the last four months we've accomplished quite a bit. Now we need a lot more. Yeah. No, that's clear. Last question, just on your pipeline. You talked about 36 deals at present. How are you thinking about lifting the revenue visibility for Appen? This has been a big bugbear for the stock historically. Should we expect a level of recurring revenue or net revenue retention metrics that you might look to report on in future? How are you thinking about lifting that level of revenue visibility? Yeah, Garry, good question. At this time, I think where I'm at is I've done a few of these turnarounds in the past, and I'm in turnaround mode. You see my scorecard on slide 26. That's how you should be measuring me and my team on that turnaround, right? Ensuring that we build all of this, get this moving. I think once we've got that done, I'll be able to then tell you, I'll have more visibility. I'll be able to tell you how the revenue, how you should be measuring us at that time, right? That's why I did a strategy reset here, to say I'm taking all that stuff off the table to really restructure this company, get the right capitalization, and then start to come back to you after the six months of my turnaround scorecard when I made all of this green, then my goal is to provide you exactly what you're just asking. Yeah. That's helpful. Thank you. Yeah. Pleasure. Once again, if you wish to ask a question, please press star one on your telephone and wait for your name to be announced. Your next question comes from Wei Sim with Jefferies. Please go ahead. Hi, Armughan. I can hear me? Hi. Yes, can hear you, Wei Sim. How are you? Good, thanks. Thanks for doing the call today. Just a couple of questions. The first one is just in regards to kind of the outlook. It sounds like the top five, we've still got a relatively large concentration from our top five largest customers. I begin to notice in terms of, you know, the outlook going forward, if you were able to talk a bit more about what the order backlog is looking like at this point in time. For example, looking at slide nine, outside of the top five, how much of the backlog then may be making up at this point? Let's see. We're not actually, we haven't updated and provided publicly the order backlog. That hasn't been a metric that we've updated over the last couple of quarters. I think what Armughan was talking about now is we're resetting the business and putting a new motion in place. With that, we will be able to come back and lay out operating targets, guidance for the short term, and then ultimately the metrics by which we'll measure the business. Right now, we're not taking a public position on order backlog. Yeah. Wei Sim, I would just maybe add to Helen's point. As I mentioned, I do feel that there are green shoots now, in the last two weeks that is now giving me enough visibility to say that 2nd half is gonna be better than the 1st half, and we're starting to see those green shoots now, right? We'll, we'll provide more info after the six months of the scorecard. Okay, got it. My next question is just, you know, having a view on revenue certainty versus growth. The prior management of the company, you know, they were talking about, well, I guess how the contracts were set up were such that there wasn't really any penalty for, you know, not achieving year-end targets if the customers didn't use all the services that they said they were looking for at the start of the year. I'd like to know just with the new customers whether we've changed that model or, you know, whether there's actually better certainty in terms of the revenue outlook in terms of some of these green shoots that we're seeing now versus what we've seen historically? Yeah. You know, listen, we're continuing to assess how that is working. I am like four months in, Helen's you know, 10 days in. We're assessing that. We're seeing how that customer operates. I've got Brian Haskett running our deliveries, ex-IBM, global services delivery, and we're just trying to continue to assess how crowd operation and our delivery is operating. Once I have more visibility, I'll be happy to provide that. Okay. Got it. Maybe just a final question. In regards to, you know, the debt facility that we're now able to access, is that still the same size? Is that the one that was AUD 58 million, if I couldn't see the portal, has that size changed? Also, you know, what covenants are attached to it at this point in time? Right. The facility is AUD 20 million. It's been in place since April. We haven't disclosed the lender or the covenants publicly, but that facility is available to us and we did note today that they've been supporting us in this transaction and as we ramp our way back to product, to profitability. They've been really good. Yeah. It's one of the very large banks in Australia. Okay, great. Thank you very much. The next question comes from Ross Barrows with Wilsons Advisory. Please go ahead. Hey, good morning, Armughan and Helen. Thanks for taking the questions. We have two for you. Just the first one's on Appen's customers. It's kind of been asked a little bit, but maybe I guess if I can reframe it. I guess the concentration has been and does remain a bit of a consideration when thinking about Appen. You've noted that top five customers have been anywhere between, you know, 80%-90% of revenue historically, and one customer is a large part of that, which you've more recently disclosed. Can you help us understand what that concentration could look like going forward? I understand it's probably a difficult call to make, but I guess any insights on, you know, kind of order of magnitude or how we can think about these new customers would be helpful. Maybe I'll start and I'll ask Helen to add. You know, at this time, you're right, where that's the concentration. We feel, you know, we have an enterprise business, we have a China business, we had a, you know, we have a federal business, but which has declined. I think if I look at, you know, getting the sales structure going, getting the marketing going, having more pipeline, to see exactly how do we look to grow that, we do know that it's a TAM that's growing and massively. As we get more visibility on the pipeline, we will share that with you. Helen, anything you wanna add? No, I think that was a good summary. I mean, I think the clear piece of the strategy is expanding our presence in the enterprise space with generative AI solutions. That it won't just be the large tech company, global techs that are buying generative AI solutions. There's very applicable solutions at the company level to unlock productivity, to provide new access to markets, to improve their own solutions. That's the strategy. With that, we fully expect that there'll be some diversification over time. Yeah. I would even say not just in enterprise adopting generative AI, I would tell you that in the past, the deep learning AI was very challenging for large enterprises. I was at KPMG and Dell before, you know, that's what we were helping customers do, and it was a lot of bespoke type of work. Now generative AI, it's a much faster adoption for enterprise. I would say that we were three years ahead of our time, you know, trying to take deep learning AI to enterprise, and I think that'll be much faster with generative AI. Also in deep learning AI, we're now seeing a lot more, as I said, relevance work in the big five global accounts alongside that in China. We're seeing that's continuing to grow for us, along with generative AI in the globals as well, right? We're seeing both of those growing. Okay, great. That's helpful. Just a quick follow-up. One last. Oh, sorry. Sure. Go ahead. Yeah. No, go ahead. Sorry. Thanks. Just a quick follow-up on that one was, as the, you know, the big customers, continue to grow and to invest and the non-big customers or the customers outside the top five continue to grow and invest, I guess it's difficult proportionately for those smaller customers to become meaningful if those bigger customers do return to spend. I guess that's what I was trying to explore a little bit then. Yeah. I think I'll stick with what I just said. Yeah Earlier about that, right? That's great. Thank you. The second one was just around the human in the loop capability. Look, it's been a genuine differentiator for Appen. Just noting that, you know, there is some competition increasing in that space with others having, you know, approaching similar offerings in terms of number of people, maybe not the tech around the human in the loop, but maybe just exploring that a bit. Could you just help us understand how you kind of differentiate that offering versus competitors? Thanks. Yeah. Listen, we don't see a lot of competitors in the crowd area. Many of those customers actually come to us. We've got maybe one or two max in that. A lot of people can say that, but their SLAs are breaking pretty quickly. We've been at this for, you know, a few decades now on how to work with the crowd, how to pay the crowd, how to recruit the crowd, how to train the crowd, how to have them do the work with a higher quality than our NPS and others. A lot of, you know, early-stage startups are wanting to do that. Very quickly. You know, our customers are very quickly, like especially in enterprise, they do a bake off. They see what Appen's been doing. I think when it goes to show that we've got Googles and the Metas and the Microsofts of the worlds as our customers, you know, and these small Tom, Dick, and Harry type of startups are saying, "Oh yeah, we could also do this." Let's just say we have an upper hand here, right? That's positive. That's great. Thank you. Yeah. Pleasure. Thank you. I think we wanna thank everybody for joining us. That's it. I think that's all. it. I think that's all. Thank you, Rachel. Go ahead. Yeah. I think. Yeah, I think that probably brings us to a close. We really appreciate everyone's time. Thank you for the thoughtful questions. Hopefully, we'll see you all on the 26th of May for our Investor Day and our Tech Day that will be taking place at the Barrenjoey offices. They've got really nice new offices I just checked out. Thank you, everybody. Have a great day. Cheers.