Operator : Good day, and thank you for standing by. Welcome to Genscript Biotech 2026 interim results conference call. [Operator Instructions]. Please be advised that today's conference is being recorded. I would now like to hand the conference over to your first speaker today, CFO of Genscript Group Biotech Group, Mr. Phil Zhao. Please go ahead.

Phil Zhou : Welcome to our 2026 interim results conference call. Joining me on the floor today are Mr. Robin Meng, Chairman of the Board; Mr. Sherry Shao, Rotating CEO of Genscript; Dr. Ray Chen, President of Genscript Life Science Group; Dr. Aixi Bai, General Manager of Bestzyme; and Mr. Allen Guo CEO of [indiscernible]. During today's call, we will be making statements about future expectations, plans and prospects as well as any other statements regarding matters that are not historical facts which may constitute the forward-looking statements. Actual results may differ materially from those indicated by such forward-looking statements because of various important risk factors and changing marketing conditions. We do not undertake any obligation to publicly update any forward-looking statements. Before we begin, please note that the prior period of figures presented in this conference call are on a comparable basis excluding the financial impact of the license transaction with Renova pursuant to the license agreement that was recognized in a prior period. We believe [indiscernible] provides a more objective view of the group's underlying business performance. Today, Sherry will provide an overview of our company's performance and growth drivers. I will then guide you through the financial performance. Following that, Sheery will update on our full year guidance. We will also have a Q&A session at the end of the call. As a reminder, today's presentation and recordings will be available in the Investor Relations section of the company's website. Now I will hand it over to Sherry.

Weihui Shao : Before turning to company performance, I'd like to provide an overview of our company and the core drivers behind our long-term growth. Genscript is a leading global platform for life science services and products. We sold more than 2,260,000 customers across over 100 countries and regions, supported by an integrated R&D, manufacturing and commercial network across North America, Europe and Asia Pacific. In the first half of 2026, Genscript delivered a strong levo results that demonstrate both growth momentum and improving business quality. Revenue exceeded USD 400 million, 27.3% year-over-year growth, while adjusted net profit reached USD 62.5 million, growing more than 200% year-over-year. More importantly, these results reflect the early benefits of the most scanable growth model. AI-driven demand is expanding our addressable opportunities. Our [indiscernible] protein and deepening customer value and competitive modes. And operating leverage is translating growth into stronger profitability. Now let me walk you through key operational highlights across our business for the first half. First, our Life Science Group, set up high-quality growth, powered by gross AIDD demand, we achieved both growth at scale and margins improved. We have further enhanced global delivery with about 60% of our lab equipped with AI-driven automated workstations in operational efficiency and productivity at scale. Importantly, our gene closing platform continues to change the game by compressing turnaround from digital sequence to model-ready data to as fast as full base the purest turnaround in the industry. This is precisely the kind of speed the AI era demand. [indiscernible] maintains daily growth with accelerating all the momentum increase in top lines moving to downstream driven by AI in [indiscernible] is becoming a new growth engine. While improving scale continues to lead profit finish. For pipeline, rising custom [indiscernible] continues to bandage the commercial value of our products. We are also applying AI to protein design and engineering to accelerate innovation and the launch in the market will impact our growing IP portfolio underpins our long-term processes. As we look ahead, AI revolution in protector. I will highlight all this optive plans in AI [indiscernible] discovery unfolding [indiscernible] is perfectly positioned to leverage this set and drive this resolution goal. AIDD is approaching a critical tipping point as some [indiscernible] briefing over the past few years, AI has financially reshifted the software development industry and life sciences is emerging as the next high-value applications beyond software. We see increasing AI applications in target delivery, molecule design and candidate lesion, a calling to anatomy. Nearly 60% of [indiscernible] biopharma leaders, rent AI in research and discovery as a top out. Indeed, the potential of AI interest recovery is undeniable. First, AI has substantial to dramatically accelerate early-stage discovery, comprising a traditional 4- to 6-year time line into just 12 to 18 months Second, AI can enable researchers to explore a much broader range for [indiscernible], modalities and partial designs at computational scale, First, by identifying pipe quality winning candidates early before more costly downstream development regens, opens, AIDD models. [indiscernible] higher success rates and maximize ROI. Here is the structural shift we are tracking. Applying AI to the licenses and truck discovery is fundamentally more complex than [indiscernible] inherently more complicated and our feedback loops, demand, resorts, physical but [indiscernible] such must not affect the AI-driven transformation of our industry is in average bond. So we can reach the past between digital design and when labor will dominate the market. The key challenge facing AI-driven just salary today is no longer generating ideas and design. It is validating AI models can now generate thousands of candidate molecules in out. However, traditional experimental workflows were not designed for that scale of speed. Validation [indiscernible] weeks involves multiple disconnected steps and produce this data that is not always ready to be directly back into AI models. As a accelerates design, the bottleneck is shooting despite the later board fixed perimental plantation. We are experiencing a significant opportunity emerging around a new category of infrastructure validation platform that fast enough for AI iteration, scalable enough for their volume and structure from continuous model learning. That is where Janet is uniquely positioned. We are here to close the group. To address this industry challenge, we put towards our 4-day AI to biology validation engine. This is an integrated validation platform built specifically for the AI. [indiscernible] will continue to improve and evolve. Our platform combines 4 critical [indiscernible] scalable capacity, our modular gene to protein and as [indiscernible], allows rapidly as top as cost demand growth. Second peak, we can move from digital sequence to moderate biological data in a short as bodes dramatically reducing validation time lines, this is industry leading or BD esports execution automated and digitally target for growth reduced menu turnover [indiscernible] improved consistency and scale efficiencies. For AI ready data results are generated in format test and support model iteration and continuous learning. Together, these capabilities transfer to help close the debt between digital intelligence and biological execution transforming validation from an industry bottleneck into a next-generation solution and our competitive advantage. Here, why this matters commercially. This shift isn't just technologable is redefining our customer base and our revenue model. AI is changing to buy from us and how they buy. Beyond our [indiscernible] we announced increasingly engaging AI-native betas, model developers and major technology companies entering Life Sciences for the first half. Generously new commercial category or life sciences industry and for Genscript. AIDD is changing how our customers operate. The AI models generate more designs from long experiment and iterate faster, which transaction from a one-off and a longer cycle project into recurring ongoing stream of demand. That shift the new segment of customers engines involving operating models from our customers is what makes this opportunity structurally larger than [indiscernible] and the result is report a larger customer universe, higher order loans, faster cycles and steeper longer-term engagement. Again, they create a larger and more strategic growth opportunity for Genscript over time. all investors who are newer to the AI point in [indiscernible]. This slide illustrates where translate sits in the value channel. AI models can generate designs, such those designs must ultimately may be translated into logical contracts that stated experimentally developed into AD and ultimately, manufacture at scale. Just put artists across multiple points of that will flow. Our Life Science Group, please visitation through our gene protein and acid platform asset and matchable speed and scale. We are closely integrated into the AIDD Group. [indiscernible] helps advance promising candidates into development and manufacturing 1 pipeline advances. [indiscernible] leverages innovation and I enabled protein engineering to create new opportunities in synthetic by [ Oleg ], combined with our global operating footprint and strong balance sheet. These capabilities positions Jens as a critical infrastructure provider, supporting the next generation of AIDD labeled biotech innovation. We are not a paid in AI for science casino. We are actively building the validation infrastructure that enables it. As AI-driven discovery gaps [indiscernible] continue to strengthen its position as one of the most strategic and valuable points in the biotechnology value chain. Having discussed the strategic drivers shaping our long-term opportunity. I will now hand the call over to Phil to review our financial performance in greater detail.

Phil Zhou : Thank you, sherry. Let me now take you through the group's financial performance for the first half. Revenue reached USD 404.2 million, up 27.3% year-over-year. reflecting strong momentum across the group. Growth was across base. Life Science services and products grew 28.8% to USD 390 million grew 34.2% to USD 61.1 million and Beside grew 7.4% to USD 30.4 million. Alongside the top line growth, we also delivered higher quality earnings. Group gross profit reached USD 26.7 million, up 48% year-over-year. significantly outpacing revenue growth. [indiscernible] effects our improved business mix, operational efficiency and scale benefits [indiscernible] growth and improved operating leverage adjusted net profit reached USD 62.5 million, up 23.3% year-over-year, a record for any half and the clear guidance, clear evidence that profitability is scaling faster in the top line. Overall, the group delivered growth across revenue, gross profit and net profit which is a strong validation of our ability to create long-term value by leveraging our global footprint, innovative platforms and scale. Now let's turn to the Life Science Group or LSG. In the first half, LSG delivered strong revenue growth alongside the meaningful profit expansion and operational efficiency gains. Revenue reached USD 319 million up 28.8% year-over-year, around 10 percentage points above initial guidance. Growth was driven by sustained global customer demand increase the penetration of the generating plant on and rapid expansion in IDD related demand. We are seeing strong demand for high-quality gene capacities, retain expression and related to research services across pharma and our tech customers and AI-driven companies. More importantly, profitability improved significantly. Adjusted gross profit reached USD 185 million up 46.1% year-over-year. Adjusted operating profit reached USD 94 million, up 102.8% surpassing million for the first half and effectively doubling. This benefits from our improved operating leverage over the past couple of years, we have consistently invested in automation, digital operations, capacity expansion and other global plans. Alongside the business growth, we see higher operational efficiency and stronger profitability enabling profit growth to outpace revenue growth. Expense trends were also encouraging. Growth in selling, administrative and R&D expenses remains the low run growth, reflecting strengthening scale effects and disciplined resource allocation. We also see improve the margins. In the first half, adjusted gross margin reached 57.8% or 55.4%, excluding the impact of U.S. tariff refunds and asserted operating margin reached 29.5% or 27.1% on a same basis, both improved significantly compared to first half 2025. The operating margin approaching 30% marks an important milestone for LSG, transitioning from investment for growth at scale and profitability. With growing demand from AI Genco discovery and expanding global customer base and increasing platform synergies, we believe ISG is well positioned to drive both round and profitability improvement. This slide shows why LSG's growth is not dependent on single product region or custom types. LSG to sustainable growth is too to its leading platforms, global reach and broad customer base, looking first at our product mix, censoring, products and services contributed around 2/3 of LC revenue. make our most important business area. This reflects both our leadership of coping platform and a strong customer demand for integrated R&D solutions. [indiscernible] our revenue base remains well balanced. North America contributed approximately 50% of revenue while Asia Pacific and Europe accounted for 29% and 21%, respectively. This diversified global plans allow us to catch the opportunities across major markets while enhancing our business resilience. Our [indiscernible] highly resilient but on a strategically diversified customer base, with over 80% of revenue generated by pharma and biotech, we are deeply indebted in leading R&D engines. Compliance our robust prices across global research institutions, ensures long-term structural collaboration well beyond our industry segments. Taken together, our [indiscernible] platform global operating network and the diversified customer base provides a strong foundation for LSG's continued growth, enabling us to capture opportunities arising from driven life science innovation. Moving on to the opportunities ahead and the key drivers that will support long-term growth, we see 3 engines powering LSG score in the years ahead. First, our integrated [ genoprotein ] platform remains the primary engine of our growth. We are tracking the structural shift as customers transition from transactional single product purchases to our comprehensive end-to-end solutions. This transition invested deeper into their R&D before accelerating top line revenue while directly driving margin expansion and long-term profitability. Second, AI-driven demand has rapidly emerged as massive new growth engine Unlike traditional discovery, ID programs required exponentially higher throughput, continuous engagement and a long-term collaboration. For Genscript, it translates directly into significant larger contract values and exceptional long-term value -- long-term revenue visibility. We expect this momentum to compound aggressively with AID orders projected to double in the second half and maintain that hyper growth trajectory over the next several years. Third, we are seeing stronger returns from our platform investments. The foundational investments we made in automation and the digital capacity are now highly accretive driven by timing utilization rates, our Genscript policing platform or service 1.5x year-over-year in the first half. Moving forward, as we scale our infrastructure to capture surging demand, less helpful capital efficiency will directly drive margin expansion and superior shareholder value. Overall, the continued expansion of the genoprotein. Rapid growth in AIDD driven demand and improving returns on our platform investments underpin LG's high-quality growth over the next several years. Turning to [ ProGel ]. The business continued its strong momentum in the first half, delivering revenue growth includes profitability and greater operational efficiency under our end-to-end CDMO strategy. Please note that all the year-over-year growth rates presented here are on a comparable basis, excluding the financial impact of the Ranova license transaction. Revenue reached USD 61.1 million, up 34.2% year-over-year, continuing the healthy trend of recent quarters, driven by faster order execution, new customer wins and the progress of causing business improvements. More importantly, that growth is now translating into profitability. Adjusted gross profit reached USD 8.3 million, up substantially from around $2.7 million in first half 2025 [indiscernible] project mix higher utilization and manufacturing efficiency all came through. Expense growth remained well below ground growth. We test investing in R&D and our technology platforms while tightening of reorganizational efficiency and as revenue scales, fixed cost of sought more effectively. Operating leverage is not clearly reasonable. This show up most clearly in adjusted EBITDA, where the loss narrowed to USD 6.5 million from USD 16.8 million in first half an improvement of over USD 10 million and the meaningful step toward profitability. These investments is made in [indiscernible], global expansion and capacity are now converting into profitability as revenue growth. Looking ahead, with a state discipline on high-quality growth driving revenue, improving operating leverage and reinforce prevailed as a leading global CDMO partner. [indiscernible] margin, we are focused on the quality and the sustainability of future growth. And on that front, our order intake so start. Our revenue per bar grew 3.2% organically, Biologics business grew 44.2% and [indiscernible] BRP business grew 16.3%, broad-based strength across both lines. The real headline is modest New orders grew 54% year-over-year, significantly outpacing remote. Our logic expats up 62.1% and advanced therapy business of 34.9%. Our backlog continues to build for enhancing the visibility of our future revenue. By region, we achieved a steady growth across all major markets. On roaming, China grew 43.1% and international markets grew 30.3% on orders turn grew 73.8% and international markets grew 55.3%, demonstrating robust demand across both markets and solid BD outcomes. Overall, Profile is delivering strong growth across revenue, new orders and market expansion, in particular, orders consistent and outpacing revenue reflects customer recognition of our ton CRM platform. and reinforces our confidence in growth outlook ahead. Finally, turning to Basin. Despite the market headwinds, backline maintained steady growth while continuing to invest in innovation and commercial execution. Revenue reached USD 3.4 million, up 7.4% year-over-year, driven by rising demand for core products and growing customer base. Our expertise in the industrial enzyme and be manufacturing continues to reinforce our competitive position. Profitability also improved. Adjusted gross profit grew 14% year-over-year to USD 13 million outpatient reveal on better product mix and improved manufacturing efficiency. Innovation remains our core driver with adjusted R&D investment reaching USD 5.6 million in the first half, semi industry enzymes, biomanufacturing and synthetic bio biology while we apply AI and digital tools to improve R&D productivity and speed consolidation. Alongside that, we continue to strengthening our commercial capabilities and global reach. expanding customer reach as demand grows for high-performance enzyme products and sustainable solutions. On the bottom line, adjusted operating loss was USD 1.3 million compared to 0.6 million loss in first half 2025, but deliver rate investment in platform and innovation led positions us to unlock larger growth ahead. Looking forward, with new product commercialization, continued market expansion and emerging scale benefits, we expect basin to lead both revenue and profitability.

Weihui Shao : To conclude, let me share our outlook for the full year. Looking ahead, we are actively capitalizing the industry and the acceleration of AI-driven [indiscernible] revolution, the fast expansion in global Biopharma, R&D and the next-generation transformation of global biomanufacturing. In Life Science Group, our mandate is clear. We will hear our leading in holding platform potions segments to data delivery, with mature and capacity. We will keep digitalizing and operating our global network to improve efficiency and reliability. More importantly, we will be directionally integrating our online canvasing engine into our customers' R&D systems and digital infrastructure to power the future of AI products. In provide, we will continue to visit from growing biologic demand and emerging opportunities in repo-CAR-T and AIDT. We will expand our global footprint, strengthen our platforms advanced more progress from early discovery into clinical and commercial stage and stay on track for positive EBITDA in 2027. In present, we will book on commercializing switch protein, accelerating AI-enabled R&D and product optimization. And continuing to expand globally while strengthening our IP position, supported by our strong first half performance and confidence in the opportunities ahead. We are raising our full year guidance for the Life Science service segment. We now expect revenue growth of 25% to 30%. Adjusted gross margin above 55% and adjusted operating margin above 25% or provide we are increasing our revenue growth guidance to 25% to 30% and continue to affect the business to achieve part EBITDA in or better, we expect revenue growth of 8% to 10% while maintaining an adjusted gross margin of over 43%. Taken together, our platform leadership and continued investments in global reach and innovation, position Janet to deliver high-quality growth and long-term shareholder value. That concludes today's presentation. Operator, please open the floor for questions.

Operator : [Operator Instructions]. First question comes from the line of Yang Huang from JPMorgan.

Yang Huang : I have two questions. First one, then a follow-up. So we noticed a significant a revision to your to understand the guidance for the Life Science segment compared with the outlook provided earlier this year. So could management discuss the key drivers behind the kind of upgrades and the relative contributions from different areas like AIDD related demand, customer expansion and project volume growth. And also, if we kind of look ahead giving AIDD demand and IDD demand remained very strong. How should we think about the likelihood of further upside to the current last since guide. Are you seeing any signs that such demand from AIDD will continue to outpace our existing assumptions? That's the first one.

Ray Chen : Thank you, Yang, for your questions. I'm happy to answer. This is Ray from Genscript Life Science Group. And according to your questions, let me answer in this way. There were 3 things to drive our growth, and they reinforce each charter rather than spending alone. First, the IBD demand itself has more AI-related biotax foundation model developers and the innovation-focused pharma groups scale their investments in AI labeled discovery we're seeing strong growth from sensitized to protein expression and candidate validations, especially in the sequence data generation solution that would cater specifically for AIDD project sizes are increasing and engagements are becoming deeper and more strategic. Both are showing us directly in order value and revenues. And second, our customer base is compounding and getting higher quality, we're winning new AI-focused accounts while maintaining the healthy demand from our traditional pharma and biotech base. More importantly, a growing share of customers converting from single project work into Monty states, [indiscernible] service partnership, which is what turns one-time projects into recurring revenue as partnerships. And third, we are now reaping the fruits of our years of platform investments, sustained spending on automation high-support capacity building and digitalization is translating aim to shorter turnaround, the higher utilization and greater scalability. And that operational leverage has become foundational to how fast we can further grow. And for the second part of your question, we do believe the ADB is still early. And customers are moving from proof of concept into large-scale validation and operations and optimization. And that's exactly the phase where demand for high throughput in the protein production and the high positive data accelerates. We are seeing that in 3 concrete signals the sizes of the order is growing the customers' relationships are decently and the share of high complexity and structured recurring orders an area that we are uniquely strong is rising. And that last point matters most because it's what gives us confidence and visibility for long term rather than just the momentum. And so we wanted to be clear, this growth isn't the result of larger one -- larger customer or one project. It reflects a structural shift in demand and our unique ability to convert that demand into revenue and profitability at scale. Looking ahead, we are continuing to manage guidance prudently, however, and the underlying demand signals project volume, size of the order, customer debts and the growing mix of complex recurring AIDD projects are all point in the same direction and big farmers are evolving and also adopting as well. So it's a fascinating time in the industry. If these trends continue, and our unpresent execution remains strong, and we're confident about that, too, and we will see a real potential for continued upside versus our current assumptions.

Yang Huang : Okay. Great. Yes. Great. My second one is a competitive landscape. So our understanding, tab is one of our companies primary competitors in the gene services market. So how does management view the competitive landscape between taste and the Genscript in the AIDD space-related business.

Ray Chen : Thank you, Yang, for your question. Again, this is Ray. I would like to be a little bit more specific here. because we think the data speaks for itself. At Genscript, we don't compete on commodity volume, we compete on value per delivery results the speed to data and the data quality that customers can actually rely on. Let me give you some numbers behind that. First, on economics, [indiscernible] capturing more than twice the revenue per delivered item versus the company you mentioned. And that gap has continued to widen -- we're processing in rail more than 4,000 designs per day, meaningfully ahead of the publicly reported numbers from the company that you just mentioned, which is in thousands per week. The third above peak was delivered from physical sequence to binding data in 47 cameras depending on which expression route customers taking compared to more than 2 weeks reported somewhere in the market from the company that as you mentioned. That's -- the number is important here because this is 3x to 5x faster iteration cycle, which matters enormously for customers who was doing AI model depends on the continuous experimental feedback in the loop. And we think the most important are actually is the data quality in 1 recent customer loan valuation now have variability that can be 110% compared to close to 30% for the company that you mentioned in their workflow. So in the AIDD area, reliable, low variable data. It's not in the like to have. It's a master up. And that's where we believe our uniquely strong and clear advantage is most durable. As I can explain a little bit more about our fundamental business model differences as well by comparing the company that you mentioned Much of the competitive landscape, especially they stop just at DNA or fragments, go over, and we delivered the full path from sequence through expression to model-ready data reliable at scale with speed. And we have already built critical downstream capabilities at closer look end to end. Our infrastructure is built differently too. We built and modular intelligent workstations rather than large fee-format systems. And this allows us to add capacity faster with meaningfully lower capital intensity. And eventually, we're targeting doubling the throughput of our capacity. Every quarter, and we have the confidence to do that. And we have -- we have to sustain an industry-leading pace. That's what we have been committing to. So looking ahead, our objective is quite clear, serving the customers to be very definitive and always industry-leading biology validation engine. Especially for the AI drug discovery in euro. And in years for the speed, the scale and reliability the industry now demands and requires and we need to build -- to stay there. Thank you, Yang, for your person, and allowing me to have the opportunity there to explain.

Operator : Next, we have David Chang from Jefferies.

Unknown Analyst : My first one is about pro we noticed that [indiscernible] began [indiscernible] in the first half. Could you please briefly discuss the turn the pipeline of discovery related orders and profile technology capability. It's about we found both Life Science and the CIB has to do with the meaningful acceleration in the growth to the management elaborate on this capital allocation and CapEx plans to support this opportunity and also good investors, we expect any incremental financing requirements all firm racing PCs as company continues to expand its capacity and capability.

Ray Chen : Thank you, David. So for the first question, Allen, will cover [indiscernible] second one, I'm happy to address some questions.

Zhang Guo : Okay. This is Allen of [indiscernible] so for the first half of 2006, [indiscernible] totally signed USD 9.7 million AIDD related orders, including both for discovery and also CMC product and actually, we delivered around $2.5 million in revenue. So the AR generated drug candidate presents a unique development requirement and increasingly demand integrated solutions across discovery and also development. Based on our experience with the AIDD program to date, we have several common characteristics. First, so our credits clarity or optimized by ER, a typical complex molecule, including bits or tried which require further validation and operation to address the viability and provability contribution. Second, we're talking to the selection and state applications are becoming increasingly diverse spanning multiple disease areas and modalities. Third, customers typically require significantly accelerated development time line to maximize the efficiency of TD delivered by AI-driven discovery. And fourth, some customers will advance multiple candidate molecules simultaneously and this creates demand for high sulfur and also airline development facility. To address this need from AIDD, [indiscernible] has quickly established a strapline solution across both the discovery and also CDMO value chain based on our extensive experience, new house and partworks. First, leveraging our more than 20 years experience in the biologics discovery segment, for whole discovery provides a comprehensive retailization platform designed specifically for AIDD program. The key capabilities include customized data generation and experimental support for AI model training and automation; second, highly automated and high-throughput workflow capable of processing thousands of samples a day and third, interpreted in retreat platform across multiple at formats; and fourth, [indiscernible] screening strategies that optimize both biological that optimize both biological activity and availability through this end-to-end approach, providing help customers advanced AI generated candid to PCC in as little as 4 monthly. And secondly, for our biologic CMC platform, we have introduced a combined devility assessment and extract PMC offering talent for AI even molecule. [indiscernible] can advantages include early-stage viability assessments, leveraging the same wholesale system and expression lectures employees in downstream CMC development and rapid identification of sequence liabilities and potential CMC challenges before adding formal development meaningful reductions of downstream technical and manufacturing risk. And we expanded our accelerated development framework beyond monocolonal antibody net biotic antibody to include symmetric is, prices and bodies and also high construction programs. [indiscernible] the most challenging molecule format for [indiscernible] from cell transaction to toxic cloud at production at later at 4.5 months, significantly shortening the development time line for AI-driven programs. AIDD is really moving entirely fast with [indiscernible] extensive experience, competitive hotel line system and integrated discovery and CMC platform, we believe provides well positioned for AIDD program, and we will continuously capture these strategic opportunity.

Ray Chen : Yes. Thanks, Allen. So maybe for your question regarding our capital allocation and CapEx plans. So we will keep investing into match these growth market just to chase it. So expanding capacity, automation and the technology platforms to support a robust growth of both of SG and the CDMO business. So our approach to impact allocation stay very disciplined out and with a very -- every investment calibrated tightly to customer demand and expect it to return. So let's use some numbers. So during the first half of [indiscernible], the group incurred capital expenditure of USD 484 million. And based on accounting basis of momentum and the project execution progress. We expect full year '26 CapEx to remain at a healthy and a battle with total CapEx approximately USD 130 million. And importantly, the company continues to maintain a robust balance sheet and a healthy liquidity structure. We currently hold approximately USD 830 million in cash and cash current. And in addition, our discipline the management of capital expenditure, operating costs and the return on invested capital, ROIC has driven a significant year-over-year improvement in both working capital and free cash flow during the first half of '26. So given our substantial cash position, our continued ability to generate operating cash flow and a high-quality and [indiscernible] credit standing, we are confident that we have a surmise financial resources to support our ongoing expansion initiatives. And [indiscernible] do not build growth and investment as competing priorities. Our objective is to continue investing aggressively in the highest return opportunities while maintaining discipline and capital application and creating long-term shareholder value. So going forward, we will keep advancing our growth strategy. with the same financial discipline and that code. So important to say we have result from a position of increasing profitability, including return on capital and growing financial strength. So to directly address your second question, we have a sufficient for the grittier.So we see no need for [indiscernible] financial.

Operator : Next, we have Laurence Tam from Morgan Stanley.

Laurence Tam : Thank you. First of all, congrats to management on these fantastic results. I have two questions. The first one is that within the AIDD customer base, we have noticed that large AI model companies are gradually becoming a new source of revenue growth. Could you help us better understand the profile of these customers and how their needs differ from those of traditional pharma and biotech companies? That's my first question.

Ray Chen : Thank you, Laurence. This is Ray from Genscript Life Science Group again as it's a really, really interesting question, we're learning as well along the way. This is one of the most important shifts that we're seeing in our customer base, and it's worth being and precise about what we have learned and how differently and these customers behave. But let me start about the scale a traditional pharma program typically advance a handful of candidates through a small number of projects, but the A-rated customers operate on entirely different order of magnitude and their motors can generate hundreds, thousands of candidate sequences in a single iteration. And each of those needs rapid experimental validation that are long in the order size minibus. And second about speed, maybe it's truly different a traditional design test to learn cycle runs in months and -- and customers need continuous fast feedback loop. Because the model requires a steady stream of experimental data to retrain and improve, which is why the turnaround measures in base now and not weeks and high throughput expression automated platforms it's must to have for those customers. And third, it's about the molecule complexity and is different. The traditional pharma projects compensate heavily on well validated targets or formats, which I late customers, and they are pushing the boundaries they have more complex designs and because the models are policy designed to explore molecular space, the traditional discovery won't give temps. So here's the insight that matters most, we think of how we will further grow for late customers we're not just delivering a DNA construct of protein itself. We are delivering the data. The data is [indiscernible] and the express and functional activity, binding stability, developability data or feedback into the model development as input. This means we're not just selling one project or are deliverable. We're becoming part of the customers' AI development infrastructure, which is truly fascinated and that's what's driving the real upside. So that the customer's lifetime value. The traditional engagement is often a one-off project. And with AI native relationship can expand the complete workflow in drug discovery, which can also further extend to the clinical and CMC like Allen just mentioned that with Probi. This is always one positive. So simply put [indiscernible] customers and the demand more scale, more speed, more molecules, more designs, more data earlier in the process than traditional programs ever did and the companies and the build for the high throughput, automated enter and single data quality data delivery are the ones positioned to capture the value. That's exactly the infrastructure we have been building for the past 2 decades and we've built a wrong way for success. So more importantly, that which is more exciting as well, the traditional pharma is evolving as well. They are adopting together along the way. So this is why we see the customer segment is a structural long-term growth driver rather than a short-term momentum. And thank you for allowing me to share what we have learned.

Laurence Tam : My second question is on Bestzyme time. Bestzyme has been extensively integrating AI technologies into its operations under the AI for science initiative. Could management provide more details on how AI is being applied at best in and impact it's having on the business.

Aixi Bai : Thank you, Laurence, for the question. This is Aixi from Bestzyme. So [indiscernible] de integrated into our state or R&D as beta. And the business impact comes down to 2 things. after R&D and a lower cost. So first, our trained and fine-tune models led us optimize inline performance across multiple dimensions. The enzyme molecules we are guiding to the format levels that our old method similar or reach. Second, our green much property optimization has doubled our positive pirate compared to 2024. In the Bestzyme, [indiscernible] project go in just round of wiring design with fewer than 150 new pits, which model improves our project success rate but also significant continued increases the number of products we delivered. For 2026, we expect to deliver fixed to parent project which is [indiscernible] in 2025. Third, we will shorten evade money situps, we will launch both is [indiscernible] and the broad flow agent perform. They are already cutting only time by 20% and on [indiscernible] then simply by using natural language. So it's much more accessible to the team. But our protein AI models help boost engine activity by our game-related models helping improve our production yields. So put together, they drove significant cost reduction. Over the past year or 2, we will see meaningful cost savings across more than 3 projects take our findings and high temporary analysts and examples both achieved better performance at a lower cost, with gross margins up by 7% and 6%, respectively, for the single products.

Operator : Next, we have Linhai Zhao from Goldman Sachs.

Linhai Zhao : Congrats on the great results for Life Science Group, in particular, I'm interested to get more color on the improved gross profit margin in the first half, it seems like the AID orders came with a higher margin compared to the traditional into protein orders? Can management share more colors on that? And given that? Can we get a better sense moving forward? How should we think about the long-term AIDD margins? And if the LED margins would likely to remain higher how should we think about the entry barriers into this field and the competitive mode of Genscript? And also Dr. Zhou also mentioned that increase in utilization to cope with the demand as we're expecting triple-digit growth in the second half and even beyond. What is the utilization rate that we are currently seeing? And how are we preparing for the increased capacity going forward? Especially for protein side. Well, I understand that the automation level is lower compared to the gene part?

Phil Zhou : Thank you, it is Phil. I will address your first question regarding the profitability of orders. And for the second part, the excitation has deferred to rate to answer Okay. So LED related orders carry structurally higher margin than traditional protein expression veritable extremely exactly wine because their durable not a long time. First, customers partially face a large scale, high woods, which significantly increased the pertain expression throughput per project and that the proportion of the fixed cost or our platform. Second, the only pay a premium for fees, rightly the turnaround isn't optional plan because the AI models depend on faster experimental feedback to keep iterating and seen at scale is exactly for automate it. [indiscernible] to deliver third and most important, the delicate in itself, it's a different customers on just buying protein. They are buying high-quality structures, experimental data at test are actually back into their models, okay? So it's a higher value service plan than [indiscernible] alone and they commence the pricing accordingly. Put together, these 3 factors are AIDD-related projects on roughly 20 points higher in gross margin than traditional pertain expression orders. And regarding your question on sustainability, we believe these different expense costs and group reasons one on the value we are pricing pod, really the speed at scale and modeled data as [indiscernible] just mentioned, becomes more variable and AI adoption in drug-refractory lease. And because of the cost of validation bottlenecks or grows more painful for customers at more scale. And second, as our platform utilization increases and automation investments majority, our own cost structure includes imperil, which means an defined margin premium even as the category growth and the competitive intensity increases. So that is a foundational and structural advantage tied to how they distribute [indiscernible]. And for the second one?

Ray Chen : Yes. Thank you for your question. I can talk with you for days about how we could scale the throughput is not only the genes, but also all the way to protein expression and the further downstream average for the validations. So our tool our infrastructure is built, as I mentioned, the module and the intelligent workflows and workstations and which allows us to scale very rapidly with confidence and the orders, the magnitude that we're getting no one else in the world could accept and deliver. That's what we're doing right now. And we have the competence to prove double and doubling our support capacities in the coming days and coming months and in a very exciting way. Thank you.

Phil Zhou : Thank you for your interest and the questions and the ongoing support for Genscript, we apologize for not being able to address all the questions due to timing limitations. So if you have additional questions, do not hesitate to reach out to our Investor Relations team, and we will see you on our next call. Thank you.

Operator : This concludes today's conference call. Thank you for participating. You may now disconnect.