Appen Limited

Thank you very much, Melanie, and good morning, everyone. Welcome to Appen's first half FY23 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 three, 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 FY23. We will then go into 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. Our results are far from satisfactory. They reflect the ongoing global macroeconomic pressures and continued slowdown in tech spending, particularly amongst 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 seven 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, Armagan, 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 US dollars and that all comparisons are to the half he ended 30 June 22, unless stated otherwise. Starting with the financial summary on slide five. Total revenue decreased 24% to 138.9 million. This is mainly due to a 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 period. Underlying EBITDA and associated margins were significantly impacted by lower than expected gross margin, as well as a proportionally higher cost base versus FY22. 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 cost 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 six. 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 1H22. 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. And of our non-global deals, 24 were greater than 250,000. Over to slide seven. Group underlying EBITDA loss before the impact of FX was 15.7 million, impacted by lower gross margin and a proportionally higher cost base coming out of FY22. Our operating expenses were up 9% on 1H22, but were stable compared to 2H22. 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 higher cost base coming out of FY22 also impacted EBITDA. Global services costs grew 2% in 1H23 compared to 1H22 and were down 10% on 2H22. The decrease on 2H22 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 1H22. 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 F522. Slide eight shows our investment in product development. The investment of 20.5 million for 1H reflects a continued focus on product development and maximizing customer experience. 52% of spend was capitalized in 1H23. 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 reduction program in the half year, and we expect to see the full benefit of cost reduction realized in FY24. 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 1H23 annualized. Turning to slide 9, we've made strong progress against the $46 million cost out that we announced in May. As planned, at the end of 1H23, approximately 63% or $28.9 million of our annualized cost savings target has been achieved. And 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 FY24. We continue to focus on exiting FY23 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 FY23, with the first full-year benefit of the cost savings in FY24. 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 22 customer invoicing with receipts flowing into Q1 23. Cash was used during the period to pay CapEx and fund operations, while the turnaround remains in progress. On slide 11, we present the balance sheet, noting the comparison is to December 22. Our cash balance at 30 June was $55.2 million, and there is no debt at 30 June 23. 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 24. That concludes the financial slides. I'll now hand back to Armagan. Armagan.

Thank you, Justin. On to slide 13. I'll now talk to our turnaround progress and provide an updated output 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 are 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 minimize 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. And 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 LAMA2 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 and 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 wins 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 continuously impacts 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 have 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, Sati Bahadur, who has done a great job improving our product velocity. We have achieved a lot in the first six 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 five 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 FY23 of that cost out initiative. We also deployed a new target operating model and streamed our crowd onboarding process. 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're also excited to have a new app and brand refresh coming soon. I will provide a sneak peek in a few slides 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 six layers in the organization and a spans ratio from an average of one manager managing four people to one manager now managing eight 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 with the following new appointments and departures. Ryan Colon, 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, 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. Sujata Sagaraju and Fab Dolan have decided to leave the company for personal reasons. We thank Sujata 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. And just as a reference, in January when I started, there was one model. We now have over 60 models in the world ongoing. So this type of solutions become even more important. So, for example, if a customer wants to compare performance of OpenAI's ChatGPT-4 versus Anthropic's Cloud 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 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. 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 and generative AI market. Now onto 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 with our engineering team and I'm very passionate about. Now onto 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 our 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 app and 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, RECA, 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 RECA, 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 RECA 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 a million-dollar 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 FY23 revenue to be closer to our first half FY23 revenue. We continue to focus on exiting FY23 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 FY23 with an annualized run rate operating cost base lower than $113 million. With that, Melanie, the operator, would like to open it up to questions, please.