Forward Deployed Engineer

H1FY26 results and FY26 Outlook & Guidance. 1.14 -0.02 (-1.72%) Appen Limited. Le vel 8, 1 Market Street, NSW 2 0 00 Australia. ACN 138 878 298 1 ASX Announcement 27 August 202 6 H1 FY2 6 results Appen Limited (Appen) (ASX: APX), a global market leader in data for the Artificial Intelligence (AI) Lifecycle, is pleased to provide its half -year results for the six months ended 30 June 202 6 (H1 FY2 6) as well as FY2 6 outlook and guidance. H1 FY2 6 Highlights: - Revenue of $ 119.9 million, + 17 % vs prior corresponding period (pcp) - Underlying EBITDA 1 (before FX) of $5.3 million, a $7.5 million improvement vs pcp - Ongoing strong half -yearly performance achieved by Appen China, reflected by: o Revenue of $ 76 .2 million, + 80 % vs pcp; o Underlying EBITDA [1] (before FX) of $ 12.1 million, + 316 % vs pcp; and o Annualised revenue run- rate exceeding $175 million in June - Appen Global turnaround continues with solid progress made resulting in improv ed revenue mi x throughout the period o Revenue of $ 43.7 million, - 27 % vs pcp; o Underlying EBITDA [1] loss (before FX) of $ 4.5 million, - 25 % vs pcp; and o Performance improv ed during the half with Q2 +20% vs Q1, and outside of the largest client, Q2 revenue grew 65% vs Q1 - Expanded use of AI in operations continues, ~$12 million annualised cost out identified within Appen Global o ~70% to be executed by the end of FY26, remainder by the end of Q1 FY27 - Strong cash balance at 30 June 2026: $44.7 million (A$64.8 million 2) - FY26 group guidance reaffirmed: o Revenue of $270 - $300 million; and o Underlying EBITDA (before FX) margin of ~5 -10% - Investor webinar to be held today, 2 7 August 202 6, at 1 1.00am AEST (click here to register) 1 Underlying EBITDA excludes restructure costs, transaction costs, and acquisition -related and one -time share -based payment expense. 2 Converted at 30 June 2026 exchange rate of 0.6894 Appen Limited. Le vel 8, 1 Market Street, NSW 2 0 00 Australia. ACN 138 878 298 2 Commenting on the performance for the h alf, Appen's CEO & Managing Director Ryan Kolln said: "The AI market continues to grow rapidly, the competition is intensifying across Western and Chinese AI model builders. Appen is one of the few AI data partners working across both frontiers of AI, enabling us to grow as the global AI market evolves. We are proud to be supporting many of the most innovative model releases in the first half and are deeply engaged in the next wave of AI advancement." "At the Group level, we delivered 17% revenue growth vs pcp, supported by expanding projects from existing accounts and exciting new customer wins." "Appen China continues to be a major growth driver, with H1 revenue up 80% versus first half 2025. Appen China exited the first half with an annualised revenue run -rate growing to over $175 million (June), up from $135 million at the end of 2025. The sustained growth demonstrates the strength of our relationship with Chinese model builders." "Appen Global continues to also show solid progress with momentum throughout the half from expanding projects with leading AI labs. We are progressing well in our ambition to expand across frontier AI labs in the USA. At the same time, we continue to realise efficiencies as we adopt AI across our operations." "With a strong balance sheet and a dedication to delivering quality data at speed we remain focused on revenue growth from the global growth in AI, and ongoing underlying EBITDA profitability." Financial and Operating Performance Group performance Group r evenue increased 17% to $ 119.9 million in H1 FY26, reflecting accelerated growth for Appen China, and the continued turnaround of Appen Global. During the half, the small d ecrease in gross margin to 36.7 % from 37.0% reflects a change in customer and project mix. Appen China margins are traditionally lower compared to Appen Global. Group Underlying EBITDA (before FX) improved meaningfullly during the half, delivering a turnaround of approximately $7.5 million versus H1 FY25. The improvement reflects revenue and gross margin growth, prudent cost management, and operational leverage within Appen China. Appen Limited. Le vel 8, 1 Market Street, NSW 2 0 00 Australia. ACN 138 878 298 3 Appen China Appen China continued to perform well during the first half, delivering strong revenue growth (+ 80% vs pcp). The China business exited the first half with an annualised run- rate for June exceeding $175 million. Additionally, it achieved underlying EBITDA of $ 12.1 million in H1 (+$ 9.2 million or + 316 % vs pcp), reflecting 15.9% EBITDA margin. Revenue growth for Appen China continues to be driven by generative AI related projects, including supporting international expansion for Chinese technology companies. EBITDA margin improvement has also been driven by a greater mix of higher -margin generat ive AI projects and increased revenue from high -margin prebuilt datasets. In addition, a focus on opex as revenue expands is positively contributing to segment performance. Appen Global Appen Global first half revenue was $ 43.7 million ( -27% vs pcp) with an underlying EBITDA loss of $ 4.5 million. The decrease in revenue reflec ts the continued turnaround with lower volumes from traditional work, not yet fully offset by growth in new areas. Appen Global made strong progress during the period to capture growth in the generative AI market and to diversify revenue. Outside of the largest client, Q2 revenue grew 65% on Q1, reflecting growth from projects that were directly related to some of the most innovative AI releases. The new projects the Company is winning cover areas that Appen has long -standing strengths (including speech and relevance). Appen is also winning new work in domains including coding, STEM, finance, and robotics. Cost reduction program Capturing cost efficiencies via AI enabled operations remains a focus for Appen Global. This focus has identif ied an incremental ~$12 million in operational efficiencies. ~70% of cost out will be executed before the end of the year and the remainder in Q1 FY27. The cost -out does not impact the ability to deliver high -quality data at speed for its customers. FY26 Outlook & Guidance The Company remains confident on the AI data market, and the potential for Appen to meaningfully contribute to the development of leading foundation models. The Company continues to see positive signals on LLM related growth including from Appen Global and Appen China customers. Listcorp remain highly focused on driving technology led efficiencies across its operations. As in previous years, Appen Global revenue continues to be mostly derived from project - based work and seasonality skews revenue to H2. Appen Limited. Le vel 8, 1 Market Street, NSW 2 0 00 Australia. ACN 138 878 298 4 Considering this, Appen reaffirms the following FY26 group guidance: - Revenue of $270 - $300 million; and - Underlying EBITDA (before FX) margin of ~5 -10% Investor webinar The Company will host an investor webinar to discuss the results with Ryan Kolln, CEO & Managing Director and Justin Miles, CFO. The webinar will be hosted at 1 1.00am AEST today, Thursday, 2 7 August 202 6. Register for the investor webinar via the link below: https://us02web.zoom.Listcorp/webinar/register/WN_emwiBN10TtGhyBiP8ZqJ6g Following the presentation, participants will have an opportunity to ask questions. Authorised by the Board of Appen Limited. For further information, please contact: Ryan Kolln Justin Miles Sam Wells CEO CFO NWR Communications [email protected] [email protected] +612 9468 6300 +61 427 630 152 About Appen Appen is a global market leader in data for the AI Lifecycle. With 30 years of experience in data sourcing, data annotation, and model evaluation by humans, Listcorp enable organisations to launch the world's most innovative artificial intelligence systems. Its expertise includes a global crowd of more than 1 million skilled contractors who speak over 500 languages 3, in over 200 countries 4, as well as its advanced AI data platform. Its products and services give leaders in technology, automotive, financial services, retail, healthcare, and governments the confidence to launch world -class AI products. Founded in 1996, Appen has customers and offices globally. 3 Self -reported. 4 Self -reported, includes territories. Appen Limited (ASX:APX) is a global leader in the development of high-quality, human annotated datasets for machine learning and artificial... APX Profile Links APX Information Share Price: 24hr Change: 24hr Change %: Market Cap: Join Listcorp to create a personalised news feed, follow your favourite companies, save useful news, and more. 27 Aug 2026 29 Jul 2026 22 May 2026

Micro1 hits $500M run rate as AI training data gold rush accelerates. AI data startup Micro1 reaches $500M gross run rate, signaling explosive growth in training data market PUBLISHED: Fri, Aug 21, 2026, 12:49 AM UTC | UPDATED: Wed, Sep 2, 2026, 1:32 AM UTC The race to feed AI models just hit a new milestone. Micro1, a startup specializing in AI training data and data labeling services, has reached $500 million in gross run rate, according to TechCrunch. The achievement underscores how the AI boom isn't just enriching chip makers and model developers - it's creating massive opportunities for companies that provide the fuel these systems need to learn. As OpenAI, Google, and others race to build more capable models, the infrastructure powering that development is becoming a billion-dollar business in its own right. Micro1 just became the latest proof that in the AI gold rush, selling picks and shovels can be just as lucrative as mining for gold. The startup's climb to $500 million in gross run rate represents one of the fastest growth trajectories in the AI infrastructure space, fueled almost entirely by insatiable demand for training data. The numbers tell a story about where AI development bottlenecks really exist. While Nvidia grabs headlines with GPU shortages and OpenAI dominates conversations about model capabilities, companies like Micro1 are quietly solving a less glamorous but equally critical problem: how do you generate enough high-quality, human-labeled data to actually train these models? The answer involves armies of human annotators, sophisticated quality control systems, and increasingly complex workflows for reinforcement learning from human feedback - the technique that helped make ChatGPT feel conversational. Micro1's platform connects AI companies with skilled workers who label images, rate AI responses, and provide the feedback loops that turn raw compute into useful intelligence. What makes Micro1's growth particularly striking is the timing. The company is hitting this milestone just as the industry confronts a looming shortage of quality training data. According to research from Epoch AI, we could exhaust high-quality text data for training by 2026, forcing companies to get creative about synthetic data, better labeling, and more efficient use of human feedback. That scarcity is driving up the value of platforms that can reliably deliver quality annotations at scale. The competitive landscape reflects these high stakes. Scale AI, one of Micro1's chief rivals, hit a $7.3 billion valuation in 2021 and counts the Department of Defense among its clients. Companies like Labelbox, Sama, and Appen are all vying for contracts with the big AI labs. But Micro1's approach appears to be resonating - particularly its focus on reinforcement learning workflows that have become essential for training models like GPT-4 and Claude. The business model itself is revealing. Unlike pure software companies, data labeling operations blend technology platforms with managed workforces, creating gross run rates that look impressive but come with corresponding costs. Still, reaching $500 million signals that Micro1 has found a way to scale both sides of that equation effectively. For Google, Meta, Microsoft, and other companies racing to deploy AI across their product lines, reliable access to training data infrastructure has become non-negotiable. Internal teams can only scale so far. Outsourcing to specialists like Micro1 lets them move faster while maintaining the quality controls necessary for production AI systems. The growth also highlights how AI development is becoming more industrialized. Early models could be trained by small academic teams with modest budgets. Today's frontier models require coordinating thousands of labelers, managing complex feedback loops, and maintaining consistency across millions of data points. That operational complexity creates moats for companies that can execute it well. What's particularly interesting is how this market might evolve as AI capabilities advance. Some believe that as models get better, they'll need less human feedback - potentially reducing demand for labeling services. Others argue the opposite: that as AI tackles more complex tasks, the need for nuanced human judgment in training only increases. Micro1's bet is clearly on the latter scenario. The startup's trajectory also raises questions about market saturation. At $500 million in run rate, Micro1 is already processing enormous volumes of data. How much bigger can this market get? The answer may depend on how quickly AI adoption spreads beyond tech giants into healthcare, finance, manufacturing, and other industries that will need custom training data for domain-specific models. For now, the AI training data sector looks more like early innings than late. OpenAI is preparing even larger models, Google is embedding AI across its product suite, and enterprise adoption is just beginning. Each of those trends creates demand for more data labeling, more human feedback, and more infrastructure to manage it all. Micro1 appears to be capitalizing on that wave at exactly the right moment. Micro1's climb to $500 million in gross run rate isn't just a startup success story - it's a signal about where the AI industry's real infrastructure challenges lie. As models get more sophisticated and AI deployment accelerates across industries, the unglamorous work of labeling data and managing human feedback loops has become mission-critical. The companies that can deliver that infrastructure reliably and at scale are positioning themselves at the center of the AI economy. With training data scarcity looming and model complexity increasing, Micro1's growth trajectory suggests this market has plenty of room to run. The question now is whether the startup can maintain its momentum as competition intensifies and the technological landscape shifts beneath everyone's feet. More Topics:

Clover Corporation, an Australian producer of natural oils and encapsulated powders, has demonstrated strong earnings growth of 96.3% over the past year, despite a five-year decline. The company, with a market cap of A$166.07 million, is debt-free and maintains stable weekly volatility at 10%. Recent half-year results showed sales of A$44.09 million and net income of A$4.25 million, reflecting improved profit margins. The company's short-term assets of A$60.5 million comfortably exceed its combined short-term and long-term liabilities of A$13.7 million. Clover has announced a fully franked dividend and provided revenue guidance for fiscal 2026 between A$92 million and A$96 million, signalling confidence in its operational performance.