Thank you for standing by, and welcome to Appen Limited's 1H 2023 half-year results. 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 will need to press the star key followed by the number one on your telephone keypad. I would now like to hand the conference over to Mr. Armughan Ahmad, Chief Executive Officer and President. Please go ahead. Thank you very much, Melanie, and good morning, everyone. Welcome to Appen's first half FY 2023 results presentation. Today, I'm here with Justin Miles, our Deputy Chief Financial Officer, who will present the financials. I'm also joined by Rosalie Duff, our Head of Investor Relations. Turning to the agenda on Slide 3, please. There are two main sections in our presentation today. Justin will present our first half financial performance. After Justin, I will provide an update on our turnaround and outlook for FY 2023. We will then go into a Q&A session. Before I hand over to Justin, I want to provide some brief introduction comments, please. We are in an exciting time for artificial intelligence, and Appen continues to play an important role in our industry. Our data and services power the world's leading AI models, and we are seeing growing demand in generative AI. However, our results are far from satisfactory. They reflect the ongoing global, macroeconomic pressures and continued slowdown in tech spending, particularly among our largest customers. We remain laser-focused on resetting the business. This includes instilling operational rigor across the business, releasing new generative AI-focused products, refreshing our go-to-market and sales capabilities, establishing meaningful ecosystem partnerships, and continuing with our AI for Good focus. The benefits from our turnaround have yet to show meaningful results. We are seeing early green shoots in our generative AI product offerings. However, the revenue growth does not offset the declines we are experiencing in the remainder of the business. We believe that our go-to-market strategy, along with our strong AI capabilities and market momentum related to generative AI, will enable Appen to return to growth. In addition to our turnaround focus, we are continuing to evolve our business model to improve the quality and predictability of our revenue. Today, the majority of our revenue is services-based, as reflected in our Global Services revenue. We also have a renewed focus on our tech-enabled services business. That includes projects completed on our ADAP software platform, as a lot of our generative AI work is being delivered through this ADAP software platform. I would like to reiterate that these results are not satisfactory. However, I feel confident that the progress we are making to turn around the business and Appen as a whole will enable us to capture value from the growing generative AI market and return Appen to growth. I'll expand more on the market opportunity and give an update on our progress after we walk you through our first half financial performance. Before I hand it over to Justin Miles, our Deputy CFO, I would like to say a few good words to introduce him. Justin has been with Appen since 2016 as our Vice President of Finance and has over 20 years of experience in finance and accounting. During his 7 years at Appen, Justin has worked very closely with our former Chief Financial Officer, Kevin Levine, and has been a key leader in the finance function and in the overall business. As we continue our search for a new Chief Financial Officer, Justin continues to be an invaluable partner to me and our business during this transition phase. I will now hand the call over to Justin to go through the financials, please. Justin? Thank you, Armughan, and good morning, everyone. I've not met many of you, so I look forward to connecting with some of you over the next day or two. A reminder that we report in U.S. dollars and that all comparisons are to the half year ended June 30, 2022, unless stated otherwise. Starting with the financial summary on Slide 5. Total revenue decreased 24% to $138.9 million. This is mainly due to the lower contribution from our global customers, reflecting lower volumes as our customers optimize their spend and reduce costs in response to the challenging external environment. This also flows through to the New Markets business, where we saw a decrease in global product revenue. Excluding global product revenue, the New Markets business recorded a 5% revenue reduction on the prior corresponding periods. Underlying EBITDA and associated margins were significantly impacted by lower-than-expected gross margin, as well as a proportionally higher cost base versus FY 2022. We are also yet to see a material benefit flow through to EBITDA from our cost-out program announced in May. Primarily due to the decrease in EBITDA, we reported an underlying net loss of $34.2 million. Our statutory net loss after tax of $43.3 million included one-off restructure costs of $6.3 million. $5 million of this relates to the cost reduction program announced in May. The remaining $1.3 million relates to one-off costs associated with changes to the leadership team to align with the strategy refresh and turnaround focus. Turning to the revenue performance on Slide 6. At the group level, revenue was down 24%. Most of this decline can be attributed to Global Services, as well as the impact from global product that I described previously. Global Services revenue declined 27%, impacted by reduced volumes as customers looked to optimize and reduce costs. New Markets revenue declined 14% and was primarily impacted by lower contribution from global products. Excluding global products, New Markets revenue declined by a more modest 5% on 1H 2022. There was 10% revenue growth from Enterprise, Quadrant and Government combined, which was offset by lower contribution from China. China revenue decreased 15% to $15.3 million due to the protracted impact of the COVID-19 pandemic, which occurred in Q4 2022 and continued into the first half, as well as challenging external conditions. Despite the challenging conditions, Global Services recorded 45 new projects and New Markets secured 89 new client wins. Of our non-global deals, 24 were greater than $250,000. Over to slide 7. Group underlying EBITDA loss before the impact of FX was $15.7 million, impacted by lower gross margin and a proportionally high cost base coming out of FY 2022. Our operating expenses were up 9% on 1H 2022, but were stable compared to 2H 2022. As expected, in 1H, we did not see a material benefit flow through to EBITDA from our cost out program announced in May. This applies to both the Global Services and New Market segments. The Global Services division reported EBITDA of $8.7 million, down 67% on the prior corresponding period. This reflects the impact of reduced customer spend on revenue and gross margins that I mentioned previously. The proportionally high cost base coming out of FY 2022 also impacted EBITDA. Global Services costs grew 2% in 1H 2023 compared to 1H 2022, and were down 10% on 2H 2022. The decrease on 2H 2022 is predominantly due to a lower allocation of indirect costs. New Markets reported an EBITDA loss of $21.8 million, compared to an EBITDA loss of $15.6 million in 1H 2022. This reflects a reduction in global product revenue, increased costs to support Quadrant growth, a lower contribution from China, and as already mentioned, a proportionally higher cost base coming out of FY 2022. Slide 8 shows our investment in product development. Investment of $20.5 million for 1H reflects a continued focus on product development and maximizing customer experience. 52% of spend was capitalized in 1H 2023. This is slightly lower than historical levels, predominantly due to the strategy refresh and update to the product roadmap during the half. 14.7% of revenue was reinvested in product development for the half. As a percentage of revenue, this is significantly higher than historical levels due to the lower-than-expected revenue. As mentioned, there is no material benefit to our cost out, cost reduction program in the half year, and we expect to see the full benefit of cost reduction realized in FY 2024. By the end of Q3 this year, we expect the annualized investment in product development to be circa $29 million. This is down 29% on 1H 2023 annualized. Turning to slide nine, we've made strong progress against the $46 million cost out that we announced in May. As planned, at the end of 1H 2023, approximately 63% or $28.9 million of our annualized cost savings target has been achieved. By the end of Q3, at least 80% of the $46 million cost out program will be implemented. As already mentioned, the first full year benefit of the cost savings will be from FY 2024. We continue to focus on exiting FY 2023 with a return to underlying EBITDA and underlying cash EBITDA profitability on an annualized run rate basis. We remain diligent with respect to cost management and will manage our cost base in line with our revenue opportunity and market conditions. With this in mind, further cost savings have been identified and are expected to be realized in FY 2023, with the first full year benefit of the cost savings in FY 2024. Over to slide 10. The cash balance at 30 June was $55.2 million, and includes net proceeds from the equity raise of $38.2 million. Cash flow from operations decreased due to lower trading volumes, partially offset by positive working capital movements. There was positive cash flow from operations despite the EBITDA loss, due to strong Q4 2022 customer invoicing, with receipts flowing into Q1 2023. Cash was used during the period to pay CapEx and fund operations while our turnaround remains in progress. On slide 11, we present the balance sheet, noting the comparison is to December 2022. Our cash balance at 30 June was $55.2 million, and there is no debt at 30 June 2023. The decrease in receivables and contract assets is due to lower revenue volumes. Our non-current assets includes goodwill of $53.1 million and identifiable intangible assets of $53.3 million. The increase in current liabilities and decrease in non-current liabilities is mainly due to the reclassification of the Quadrant earn-out liability. We note the Quadrant earn-out remains subject to performance metrics being met. If the metrics are achieved, the earn-out is payable in cash or shares or a combination of both. Method of payment is at Appen's discretion, and the payment date would be in February 2024. That concludes the financial slides. I'll now hand, I'll now hand back to Armughan. Armughan? Thank you, Justin. On to slide 13. I'll now talk to our turnaround progress and provide an update, updated outlook statement. There's a lot of hype about the potential impact of generative AI, and the level of change continues to accelerate. The market size data on the slide demonstrates the acceleration. In December last year, the generative AI market size was forecasted at $111 billion by 2030. A more recent update by Bloomberg and IDC now predicts that the market will almost be around $900 billion by 2030. That is an 8x market size increase in six months alone. My conversations with many of the CEOs and top customers and our industry experts validates the potential of generative AI. We are very bullish on the impact of generative AI and see it as a great opportunity for Appen. On to slide 14. For those of you who have attended our Investor Tech Day in May, one of the key takeaways is that humans are critical to the development of generative AI. The Transformer technology used to develop generative AI relies on vast amounts of data to train these models. The base models work well out of the box. However, they're prone to error and hallucinations, and their accuracy is not very high. Human feedback, which is called RLHF, Reinforcement Learning with Human Feedback, is required to improve the alignment of the base models with human values. This helps minimizes the hallucinations, bias, and toxicity. Also, the base, models out of the box often do not understand the specific domain or company context. Human fine-tuning and evaluation is required to provide additional context to these models. Finally, measuring the effectiveness of generative AI models is a challenge for many enterprises. Humans play a critical role due to the subjective nature of generative AI outcomes. We mentioned these points in our last investor presentation, and since then, Meta have released a responsible use guide for their Llama 2 open-source model. In this document that's on the slide, they refer to the importance of human feedback for fine-tuning, evaluation of the models, and red teaming, which is the security and monitoring of the model. It's a great validation of Appen's strategy from one of our largest customers, that humans will remain critical for the development of generative AI models. On to slide 15, please. We talk a lot about the potential of generative AI, but clearly, this is a new and in addition to our strong capabilities in deep learning AI. We have been providing deep learning data services for 28 years at Appen, across relevance, data collection, and annotation services. Our work is underpinned by software platforms for data and our crowd services. As we expand into generative AI, we are repurposing our data and crowd platforms to fine-tune and provide these assurance and monitoring services. Our software capabilities, along with our expertise in AI data and global crowd, gives us a very strong head start in the generative AI space, and the ability to provide a full suite of AI data services for our customers. I will provide more details on the LLM customer win in the later slides. On to slide 16. While we have defined our growth strategy, our performance does not reflect the AI market potential. The broad tech slowdown continues to impact the performance, our performance, especially our customers reduce their spend across most areas. We have seen a reduction of engineering teams, resulting in lower level of activity in converting opportunities into spend commitments at the customers. As the expectation of generative AI accelerates, many of our customers are in the phase of evaluating their AI strategies, which has caused some projects to be paused or delayed. Consequently, we are seeing many of the enterprise large Fortune 2000 customers piloting large language models. However, there are very few customers using these models in full production. The combination of market headwinds in some of our large deep learning customers and nascent nature of generative AI market has resulted in declining revenue. While we can't control the market conditions, however, we can control our operations and therefore, continue to focus on our turnaround. I will now provide an update on our turnaround progress. On to slide 17, please. The turnaround started in the first half, not long after I joined the business in January. Since then, we have created meaningful impact on the operations of the business, with a focus on operational rigor across all of the business functions. We've launched our cost takeout initiative in the first half, improved product velocity. We are creating a world-class go-to-market. We have launched new ecosystem partnerships, and we have made significant progress on our AI for Good mission. In March, we welcomed our new Chief Technology Officer, Saty Bahadur, who has done a great job improving our product velocity. We have achieved a lot in the first 6 months of our turnaround journey and continue to now run the business with key metrics and KPIs. On to slide 18. In the second half, we're continuing our focus against the same 5 turnaround strategies as I laid out in the first half. We've made some great inroads here, with 63% of our $46 million cost takeout program complete. And as Justin mentioned, we would achieve at least 80% by the end of Q3 FY 2023 of that cost out initiative. We're also deployed a new target operating model and streamed our crowd onboarding process. I'll talk more, I'll talk more about our crowd experience further in a moment. Product velocity has also improved, and so far this year, we have launched new product offerings, including the RLHF and model monitoring solutions we call LLM benchmarking. In terms of go-to-market, in May, we hired our new Chief Revenue Officer, Andrew Ettinger, who's building out a sales and marketing team, including a modern sales operations function. We are also excited to have a new Appen brand refresh coming soon. I will provide a sneak peek in a few slides, for our, for your reference. We've also increased our ecosystem partnerships and have joint go-to-market approaches in place. We have hired an experienced partnership executive who is focused on maximizing the opportunity from our partnership. And finally, the most important for me from a values perspective is our AI for good focus. We have several important initiatives in place, including the active recruitment of impact source crowds from Africa, where we provide work opportunities to refugees and other disadvantaged people. We are also making great progress against our net zero pathway. As part of our turnaround strategy and continued cost management, we are also flattening the org structure from 12 layers to 6 layers of the organization, and a spans ratio from an average of one manager managing 4 people to one manager now managing 8 people for each people manager, increasing the accountability throughout the business. This will help us increase our velocity of decision-making and compete in a fast-moving set of startup competitors. Related to this, I'm making changes to the executive team, which, with the following new appointments and departures. Ryan Kolln, our current SVP of Strategy and Innovation, will take on the new position of the Chief Operating Officer of Appen. He will lead the crowd and delivery functions in addition to his existing role. To create a leaner and more efficient organizational structure, Appen will consolidate the leadership of its product functions. Mike Davey, who is the current General Manager of the Quadrant business, will be taking on the role of our Chief Product Officer for Appen, in addition to his current responsibilities. We are also combining our sales and marketing functions under the leadership of our Chief Revenue Officer, Andrew Ettinger. Sujatha Sagiraju and Fab Dolan have decided to leave the company for personal reasons. We thank Sujatha and Fab for their valuable contributions to Appen, and we wish them all the very best. On to slide 19, please. Those who attended our Investor Tech Day would be familiar with the tech stack on this slide. This diagram represents the building blocks required to develop a generative AI application. Appen plays a key role in fine-tuning and monitoring and assurance of the various models in the market, as I mentioned earlier. Fine-tuning aligns the generative AI models with human values to minimize hallucinations, bias, and toxicity. Assurance provides model monitoring and evaluation solutions to ensure that the models meet performance, risk, and regulatory requirements for our customers. I will now provide an update on our fine-tuning and assurance offerings that our product and engineering teams have recently launched. Turning to slide 20, please. As we know, human feedback is critical to the performance of large language models for the reasons I've just explained. Fine-tuning a model requires a process called reinforcement learning with human feedback. We have launched that RLHF product earlier in the year, and we have now updated it to include multi-turn conversations. This allows model developers to capture feedback across an entire conversation rather than a single interaction. It sounds simple, but there is a complex set of product requirements to achieve the routing of different conversational elements to different crowd workers. We're seeing strong customer demand and have recently signed a very large deal with a leading model developer using this specific product. On to slide 22, please. Turning to our benchmarking solution, benchmarking is a methodology for customers to evaluate performance of different generative AI models. Just as a reference, in January, when I started, there was one model. We now have over 60 models in the world ongoing, so these types of solutions will become even more important. For example, if a customer wants to compare performance of OpenAI's ChatGPT-4 versus Anthropic's Claude model, they need a way to gather performance metrics against a variety of tests. Our benchmarking solutions enable customers to test different models with our crowd, to capture feedback against different dimensions, including model accuracy and toxicity, et cetera. On to slide 22, please. Our generative AI products and solutions are showing strong momentum, and let me try to provide some details to you. To date, we have delivered 42 large language model projects. This is, and pilots, and have 40 deals in the pipeline. I am pleased to say that all of our top hyperscaler customers have completed a generative AI project with Appen or have a project in the pipeline with Appen. On the right-hand side of the slide, you see the examples of various large language model projects we have delivered. Some of these projects have been for generative AI model builders, but we also count global financial services firms as our customers, along with social media companies as our large language model customers... As discussed earlier, the market is early in generative AI, therefore, the revenue impact is small, but the customer deals are moving in the right direction. I'm very pleased with the progress we are making as a team, and we will continue to evolve our products, services, and software to capture the growth in generative AI market. Now on to slide 23. Our crowd is clearly extremely important to Appen. We love our crowd, and we continue to invest in improving their experience with Appen. That's why I'm very excited to be announcing a new crowd interface that we have launched to improve our crowd members' interface with Appen. The big focus here is making it easier for our new crowd members to join Appen and easily identify tasks that are best suited for their needs. It also helps the business by reducing project delivery time and improving fraud signals through the mobile telemetry solutions. This is just a start towards a set of improvements that we will be making to our crowd experience, and it's something that I am closely working and with our engineering team, and I'm very passionate about. Now on to something exciting on slide 24. I would like to share and provide you a preview of our upcoming new Appen tech-forward branding. Appen is a technology company, but in the past, our brand has become dated, and our website didn't have the look and feel of a modern technology company. I'm very excited to be launching a new brand with a much cleaner and tech-focused look and feel. On the slide, in front of you, you can see the various applications of our new Appen branding to be unveiled in September, starting with our new website. Moving on to slide 25, please. Now on to the progress against our ecosystem partner strategy. As we outlined in May, we have been focused on increasing our channels to market. As discussed, we have hired an experienced ecosystem channel leader, who's driving the value of our partnerships, along with our sales and delivery teams. We are delighted to be collaborating with, large partners like NVIDIA, Reka, and other cloud hyperscalers, and along with other professional services firms, this provides important access to enterprise customers for Appen and will enable Appen's sales organization to reach more customers. We have made some really strong early progress. We have made a small minority investment in Reka, which is a model builder, along with Snowflake and a large venture capitalist firm, DST Global Partners, and have a go-to-market plan in place with Reka to promote the best practices for deploying generative AI models, including the involvement of humans to reduce bias and toxicity. We have signed our first $1 million deal through the NVIDIA partnership to service a global Fortune 500 company together, and we have many more in the pipeline. Finally, we are in multiple advanced conversations with global professional services firms, cloud hyperscalers, and we are excited to be closely collaborating with them on joint customer opportunities. On to slide 26 for the 2023 outlook. I will now share some views on our outlook for the remainder of 2023. As I commented earlier, headwinds from the broader technology market slowdown are persistent, and customers continue to evaluate their AI strategies. Due to ongoing uncertainty across all customers, we now expect the second half FY 2023 revenue to be closer to our first half FY 2023 revenue. We continue to focus on exiting FY 2023 with a return to underlying EBITDA and underlying cash EBITDA profitability on an annualized run rate basis. We will achieve this by prioritizing our growth investments into a smaller set of higher potential areas. In return, this will simplify our business and deliver incremental cost savings, but may have a negative impact on 2024 revenue. We now expect to exit FY 2023 with an annualized run rate operating cost base lower than $113 million. With that, Melanie, the operator, I would like to open it up to questions, please. Thank you. If you wish to ask a question, please press star one on your 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 for question. Your first question comes from Bob with JP Morgan. Go ahead. Morning, guys. So a few questions for me. Just on the outlook, I think previously you'd made comments that you've seen some stabilization with some of your core customers, but it seems... The outlook sort of seems to suggest that, you know, the second half still looks pretty weak. Like, has anything materially changed in your discussions with your customers? Thank you, Bob. I appreciate the question. So your question was about stabilization of our core customers in second half looks weak. We're seeing ongoing cost management at our large customer. We're also evaluating their AI strategies. They're also evaluating their AI strategies, as I mentioned earlier. So it's a, it's a base of, we have a very large Global Services revenue, while we're seeing these green shoots that I mentioned earlier, Bob. Okay, sure. And then your comment as well on sort of reprioritizing some of your growth investments that might have an impact on 2024 revenues. Is that just on the incremental stuff, or do you expect that to impact your core 2024 revenues as well? ... Well, you know, as I made the comment, it's more about looking at what are the higher priority areas that provide Appen the growth that we need in the coming years. So we're looking at both our deep learning and generative AI areas, Bob, to ensure that we're very focused on the areas where we do want to spend our dollars and our OpEx dollar stores. Okay, cool. And then just the final one. Yeah, obviously, the product investment as a percentage of revenue has ticked up a bit. How are you thinking about this longer term, given the traction with some of these new products seems to be taking a little bit longer to come through on the revenue side? Yeah, and, you know, the number you're seeing on product investment is the first half number. And then, and as, Justin and I both mentioned, our cost takeout strategies haven't been fully realized in the first half. So, if you take a look at, some of the information that we provided on our, product, slide that Justin mentioned, it, it will show you that it's not going to be ticking up as we are, moving towards, more of our July, and along with going into August, we do see a lower spend on R&D. Okay, thanks. Yeah. Thank you, Bob. Thank you. Your next question comes from Wei Sim with Jefferies. Please go ahead. Hi, Armughan. Just- Hi, Wei. Hi. Just in regards to, you know, the OpEx comments that Justin made before, I'm just... What's the OpEx split between Q3 and Q4 historically? Are you able to give us some sense of that? I'll let Justin take that. Yeah. Thanks, Armughan. Wei Sim, we don't, we don't generally provide that split, so there's nothing kind of extra to give there. Historically, the business has been growing in Q3, and Q4 has seen an uptick in, and obviously, the focus now has changed around getting that cost base aligned with the revenue and the market conditions. Okay, great. And my next question was just really on the China business. That weakness that we're seeing, you know, we called out COVID. What, how do we think about, you know, the impact of COVID? You know, when do we expect it to, I guess, start to ease off? And, you know, something that I did read about for the competitors was, they were also impacted by some of the changes in terms of, data privacy laws, which came through. Is that something that also impacted on our China business? Yeah. Thank you, Wei Sim. On the China business, as we mentioned, coming out of COVID, that obviously had a downturn, and you know, the macroeconomic situation in China at this time. We are, however, seeing that we're taking market share away from our competitors there, and we continue to see green shoots, particularly in large language models in China. And we don't see much impact of data privacy. Most of our work is domestic in China, so other customers who are doing global work outside of China are the ones experiencing the privacy issues. Okay, great. Thank you. That's it for me. Thank you, Wei Sim. Thank you. Your next question comes from Siraj Ahmed with Citigroup. Please go ahead. Hi, Siraj. Hi, Armughan. Just, the first question, just in terms of the further cost out and impact on the fiscal year revenue, and then just, I mean, any way you can quantify, I think it's early stages, but just how much we should be thinking about and also the impact on revenue, that we should expect for next year? Yeah, we're not providing what additional cost outs we need to provide. What we are providing at this time, Siraj, is that we're going to continue to commit to delivering cash EBITDA positive run rate as we exit December. You know, as we do see any types of tech downturns and the tech spending downturn with our top customers, we'll continue to take action. But as I laid out in my talk, that you know, we're really investing in key areas that are now showing us those green shoots while we are doing the spans and layers exercise of our organization that I also highlighted, so that we are fit and and competing against much nimbler startups. And that's the process that we are following. So- But maybe... Sorry, go ahead. Yeah. No, I was just gonna say we're managing to the EBITDA breakeven, and no major goals that will impact revenue materially, and also being much more diligent on the ROI in our investments as well. But maybe, under the platform, is there any sort of business that you think the revenue that you're generating is not really core, critical, that you think going forward? I'm not sure it's moderation or something like that, or what are you doing today? Yeah, we're evaluating many of the areas, Siraj. You know, LLM changing daily these days, as I mentioned earlier. You know, that they were one model six months ago, and there's, you know, over 60 models now. I shared how the market has changed from, you know, $111 billion by 2030 to over $900 billion. So we're seeing much more nimble. We're being much more nimble in our investments so that, you know, we're staying ahead of a fast-growing market here. The second one, in terms of gross profit margins, it seems like compared to your trading at this meaningful, it's actually improved in the last few months. Margin is actually up year on year. Anything to call out there? And secondly, are you just in terms of outlook looking ahead, are you seeing any pricing pressure from your largest customers? So I would say, when I take a look at our gross profits and how we are delivering a lot of our solutions, we continue to look to optimize and look to automate a lot of our delivery capabilities. So we're not seeing much pricing pressures from our customers. We are also, you know, we have a long-standing price agreements with our customers that remains in place, Siraj. Just a quick last one. Last one for you. In terms of competition, you sort of mentioned a couple of times being in big competition. Are you seeing any, you know, increase in intensity or competition from any of the players out there that's impacting you as well? Yeah, Siraj, a lot of our competitors are not the legacy competitors of Appen anymore. As you can see, some of our competitors are also seeing a similar kind of downturn who are focused on the deep learning AI side. A lot of the competitors that we're seeing on the generative AI side happen to be VC-backed startups that are moving a lot faster, but with smaller... But, you know, LLM work is much more competitive, but it's, as I said, with smaller players. We're seeing more opportunities as customers look at, you know, scaling their large language models work globally in multi-country. And, you know, Appen's been doing this for a long time, and as I mentioned, majority of our hyperscalers have completed or have a pipeline with Appen. You know, similar to the NVIDIA comment I made, where we have now closed a $1 million Fortune 500 customer deal with them, and we have a lot more in the pipeline, professional services firms, cloud hyperscalers. So this is where Appen, you know, being a publicly traded, reputable company, moving a lot faster versus, you know, some of these private, high valuation startups. That's our differentiation, remains a differentiation for us. Thank you. Your next question comes from Andrew Gilbey with Macquarie. Please go ahead. Hi, Andrew. Good morning, guys. How you going? First one from me. Just wondering if you could provide any color on the revenue guidance to be flat half on half. I appreciate, you know, this assumes no change to macroeconomic conditions, but can you maybe clarify if it assumes any normalization in the trends you're seeing in your key customers, please? Yeah, I'll take that one, Andrew. Hi, Andrew. It's Justin. What it does assume is, historically, and when we gave that update in May, those assumptions built around in terms of the 1H, 2H SKU, and that's what Appen has seen, you know, year-on-year, and particularly geared towards Q4. What has changed now is there is this level of uncertainty around that SKU, and that's come about for all the reasons that Armughan talked about before, right? The customer's optimizing their spend and focusing where they put their money. And just through discussions with the customers, you know, the signals are not giving us a great level of confidence that that SKU will be there. That's why we've called out the uncertainty and think it will be, you know, closer to H1. I don't think it's necessarily a trend for forever, but it's what we're seeing right now. Perfect. Thank you. And then just one more on gross margin. I was wondering if you could flesh out a little bit more, just in particular, crowd costs. Are these going up, and discounting? And if you can maybe give a feel for, kind of the percentage changes in each of those elements, please. Yeah. So in terms of discount, discounting, we're not seeing anything there. If you look at our crowd costs, they're pretty flat on the same period last year. So again, not seeing a great deal of pressure there. Perfect. That's it from me. Thank you. Thank you, Andrew. Thank you. Your next question comes from Josh Kannourakis with Barrenjoey. Please go ahead. Hi, Josh. Hi, guys. Thank you very much for taking my questions. First one, just with regard to some of the larger customers, you previously mentioned that your sort of number two customer had been a bit more stable than your first one and continued to grow. Has there been any change in trend, you know, in the last, you know, three to six months in that customer particularly? Our number two customer continues to stay strong. When we provided that information during the equity raise, we were just providing all of the context, and we'll look to provide a lot more information at the end of the year. Okay, that's great. So it's primarily that, number one customer. Yep, got it. Just in terms of second question around the working capital move, there's a pretty significant positive working cap benefit in the period. Could you maybe just talk through that and just to give us a bit of context around maybe how much of that has unwound or, you know, we should, we should consider as unwinding into the sort of, second half? Yeah, sure. Hi, Josh. Yeah, and a lot of it is to do with the strong Q4, where customer invoicing was quite high, and that cash flow through flowed through into Q1. The majority of it has unwound. Yeah. Got it. That's great. And just final question, just with regard to some of the green shoots you're seeing across the GenAI stuff, could you maybe give us some context around the enterprise customers? And you've talked to the hyperscale projects, but in terms of the enterprise levels, just where do you think people are at in their sort of life cycles for GenAI? How long, I guess, do you think in your minds, before some of the contracts they start committing to going to be a bit more material for the business? ... Yeah, Josh, Armughan. So we find it very early at this time. We're working with financial services, top retailers, insurance companies, manufacturing companies around the world, and we're finding that there's lots of exploration going on, where they have a pilot going on. There's a lot of need for support to ensure that these models, as I mentioned earlier, they're all fine and dandy when it's, you know, you're using it for fun and games, as a B2C approach for consumer use case. But as soon as you look to use it in an enterprise, especially in a regulated market, there's a lot more challenges for them to deploy it in production. We think that next year will be where enterprises will seek to invest more heavily in generative AI, aligned to their budget cycles. Got it. And final really quick one, just on the exec team and changes. Is the majority of that largely sort of positioned now, like in terms of the go-to-market strategy, in terms of the different segments that you've now aligned? Like, maybe just to give us a bit of context on how stable, I guess, you know, hopefully the HR team is, or if there's further hiring you need to do, maybe just a bit more context on that comment. Yeah. Thank, thanks, Josh. You know, as we're continuing, continuously adjusting Appen to become a lot more nimbler to compete against these startups, we're always looking to see how we can optimize ourselves. As I mentioned, I provided you some spans and layers numbers, and how we're trying to adjust Appen into a much more of a, startup-like, much more nimbler organization. I feel that the current leaders that we have in place are solid, and we're going to continue to evolve. As I mentioned, that the CFO recruiting is ongoing, and that's probably going to be our next big hire. Okay. That's great. Thanks, guys. Appreciate the questions. Thank you, Josh. Thank you. Your next question comes from Karan Siraj with Ethel. Please go ahead. Good morning, Armughan. Thank you for having us. Hi, Karan. So my first question was, is China's stagflation a concern for Appen, given that a lot of businesses moving to India from China? Yeah, you know, our China business continues to, as I mentioned, you know, be a very strategic part of Appen. There are some macroeconomic conditions, that, you know, China is going through, as I mentioned earlier. We do continue to see a huge potential in China. India, we have, recently opened, our Hyderabad engineering facility there, and we'll continue to invest in that area. LLMs are getting big in China, and they've created a lot of great opportunities, for us there. A lot of hyperscalers, along with enterprise and telco and others, are, are working with us. And, you know, as I mentioned, we're actually taking share from our competitors there. Okay, awesome. Thank you for that. So my next question was: so we've seen the NVIDIA story, right? We've seen in the last few years that they've been achieving multi-bagger gains, and, Appen is a partner of NVIDIA, yet, we haven't seen any of this trickle down and reflect in the share price. Is this possibly a one-sided partnership? Well, if you take a look at our revenues and where our revenues come from, it's very much a Global Services revenue. As I mentioned, large language models are still getting up to speed with a lot of large enterprises. So it doesn't matter if it's NVIDIA or if it's any of the other LLM providers or hyperscalers. I think everyone's seeing a similar kind of process in customer adoption on large language models. So the benefits from our green shoots are not offsetting the declines in other areas, as I mentioned. It's early days in our partnership with NVIDIA. I did mention that we have a $1 million win that we already have had with a Fortune 500 customer. We're very bullish on our partnership there, and particularly as large language model picks up. Okay, thank you. Thank you for that. I just had a final question. So has there been any consideration that maybe the crowd model is dead? Maybe there's a disruption somewhere that Appen is not able to take advantage of, and we're just working with rebranding the old stuff. Like, maybe there's something new, and maybe the old needs to be gone, you know? So, Karan, I would encourage you to take a look at some of the slides I shared earlier in terms of what Meta calls their Meta Llama 2 user guide. That was in particular to answer that question that you just asked, which is the human in the loop continues to be very important, which is through the crowd to ensure that there is less toxicity, less bias. We still see strong demand for the crowd models. I speak to our top customers regularly on this, and we're exploring, you know, software opportunities that are less reliant on the crowd, along with the crowd capabilities. So almost think of it as, you know, our enterprise customers want internal crowd as well as external crowd or a hybrid crowd kind of a model. Those are some things that we're seeing a big uptick on. So crowd continues to be very important for us. Thank you. Your next question comes from Ross Brous with Wilsons Advisory. Please go ahead. Hi, Ross. ... Hey, everyone. Thanks for taking the call. And the questions, just a couple from me. In terms of where you're talking about the customers are reconsidering their AI strategy, can you share a bit more color around that? Like you have mentioned the, you know, there are some smaller engineering teams, but are they trying to do more in-house? Is it just overall reduced spend? So maybe some color around that would be great. Yes. Thank you, Ross. I think what I meant by that is lots of evaluation of LLMs going on. And, you know, considering the year of efficiency that a lot of these big customers of ours, especially the hyperscalers, have continued to slow down their internal spending. That's one. The second part is really that evaluation that they're doing on large language models. That's what I was referring to, that their engineering teams are focused on looking at both deep learning and large language models as they make their decisions. That's what I was referring to earlier, Ross. Got it. Thanks. Just a question on staffing, I know I'm likely to get it later in the day, but just there have been a few hires that haven't really played out in terms of tenure, I guess, from the CFO to the CMO, case in point. Can you share a little bit of color or some other information around, I guess, those roles and, I guess, why they didn't quite pan out in terms of duration? Ross, you know, there are the changes that we're going through at Appen, and we obviously put our best foot forward to have the folks join for this transformation that we're going through. We don't always get the fit right, particularly during a turnaround, and you know, we have to respect people's personal reasons to depart. Okay, thanks. And just the last one is around Gen AI. Obviously, it's an incredible opportunity, and you're very well placed to participate in that. I guess balancing that against some of your comments where some of the competitors there are probably newer, younger, PE-backed, et cetera, for example, well, they might have more niche offerings as opposed to the broader skill set that Appen could bring. Maybe just help us understand the, I guess, your ability to and capacity to invest and grow into those opportunities, acknowledging that R&D obviously come off considerably this year versus the PCP. Then maybe just contrast that with, you know, maybe some of the competitors that do have some capability to invest going forward, either organically or acquisitively, and could potentially go a bit quicker into that opportunity. Yeah. Thank you, Ross. So competitors don't have a unique advantage. It's because of a lot of our relevance work we've been doing for a long time, especially, you know, coming from this reinforcement learning with human feedback that's required. Relevance plays a very important role there. We were a bit earlier, but we are now comparable now, if not in many areas ahead on fine-tuning and monitoring assurance capabilities in certain areas. That's the - when I announce some of the products. We'll be increasing our investments in generative AI, and this is what I mean when I say we will be reviewing other investment areas. We will focus on high growth, large language opportunities. I'd also say our engineering team, you know, we're moving to that low-cost model in Hyderabad. So it's not like we are, we're just reducing our spend. We're also being very mindful of how do we do more with less, right? And, you know, those other companies you mentioned, who are startups that are mostly VC-backed, you know, they're doing a lot of that stuff in very expensive areas, and we're just trying to make sure that we are getting fit to ensure that we have a long-term play here. Very helpful. Thank you. Thank you, Ross. Thank you. Your next question is a follow-up from Siraj Ahmed with Citigroup. Please go ahead. Hey, Siraj. Thanks, Armugh an. Just, just a couple of quick follow-ups. First one, in terms of deep learning versus LLMs, I mean, have your view changed in terms of, you know, the shift, the mix shift, that it's gonna be... Deep learning is gonna be becoming quite a bit faster? It's all gonna be in a month. Just keep your thoughts on that. Yeah, no, our views haven't changed. We're just seeing, you know, deep learning continues to be in production for many of our customers, whereas generative AI is mostly a lot of pilots going on that will get into production eventually. But deep learning continues to be, as I shared last time when I met you, in the Investor Tech Day, that according to IDC, almost 70%, or 70%-80% of the market is still deep learning-based, right? It's just a lot of our concentration with the large customers, and the tech slowdown that we're experiencing there, is the reason behind it. Understood. And I guess follow up on that. In terms of, and this comment on, you know, some of the relevant projects competing in large projects, right? Early days in there, like, just your expectation, I mean, I know it's for... It might not happen, but just when you reckon this enters production? You previously said, you know, you're working with a large customer, on their, you know, service, right? So just in terms of when you reckon this come into this, some of the large projects. So, you know, we're starting to see multimillion-dollar opportunities in these large language models since the last time I was here in May till now. I mentioned that we had 40-plus deals in the pipeline. I've now come out and told you that, you know, we have closed 40-plus deals in large language models. I've also told you that, you know, our large language model deals with hyperscalers. We've completed either a project or have pipeline with them. So again, just think about end of May till now how much it has progressed, right? So again, these are smaller dollar amounts, Siraj, compared to the bigger dollar amounts in deep learning. And again, we have very high expectations that this will expand in the future. Lots of human alignment is required to get large language models to work at scale. We have big opportunities for Appen, particularly, in global large language model work, multi-country. Understood. Thanks. Thank you, Siraj. Thank you. There are no further questions at this time, and that does conclude our conference for today. Thank you for participating. You may now disconnect.