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… introduced new CPO designs in 2025, with production and commercial shipments set to begin this year. Foxconn, a key Nvidia supplier, recently announced it will start shipping a CPO switch tray—a total solution that integrates the CPO module into a system—in the third quarter of this year.
The CPO market is projected to exceed USD 20 billion by 2036, a compound annual growth rate (CAGR) of 37% from 2026 to 2036, according to market research company IDTechEx. Bank of America Research estimates total CPO revenue at just USD 100 million this year, but projects it will surge to USD 15 billion by 2030.
Although increasing adoption of CPOs is expected to gradually reduce the use of external pluggable optical transceivers, most industry executives believe the two optical solutions will coexist for a long time due to the costs and difficulty of aftersales maintenance.
"I know many people worry about the disappearance of transceivers, but don't forget that one of the perks for the pluggable module is easy aftersales maintenance," said an executive with a maker of optical transceiver modules. "With the CPO approach, if an optical engine has a problem, then the entire CPO has a problem and it is not feasible to fix it."
The optical transformation, which is just at its nascent stage, has brought massive opportunities but also numerous challenges.
"Electronic materials have fundamentally different characteristics from optical materials and components, making integration and testing especially complex," said Collins Sun, technical director at WinWay Technology, a key Nvidia chip testing solution provider. "The integration, design, manufacturing, and testing of CPO systems remain highly complex, with no single company able to solve all the challenges alone, making close collaboration across the technology supply chain essential."
This article first appeared on <a href="https://asia.nikkei.com/business/technology/tech-asia/ai-demand-strains-supplies-of-lasers-fiber-and-other-optical-tech">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.kr-asia.com/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.
Note: JPY figures are converted to USD at rates of JPY 159.31 = USD 1 based on estimates as of May 29, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

AI demand strains supplies of lasers, fiber, and other optical tech

China

<a href="/company/bytedance">ByteDance's</a> Volcano Engine has raised its full-year model-as-a-service (MaaS) revenue target to RMB 15 billion (USD 2.2 billion) after Seedance 2.0 became a major contributor to growth.
According to 36Kr, the latest revision was made in April and followed a series of upward adjustments made almost every month. At the end of 2025, the target was reportedly RMB 10 billion (USD 1.5 billion).
Volcano Engine’s full-year MaaS revenue in 2025 was around RMB 1.5 billion (USD 221 million), meaning its latest 2026 target is about ten times last year’s actual revenue. Much of that growth can be traced to the rapid adoption of Seedance 2.0, the video model now generating more than RMB 1 billion (USD 147.3 million) in monthly revenue.
A person close to Volcano Engine said its average daily token consumption has continued to grow by nearly 40% month-on-month.
That points to a clearer commercial pattern: strong <a href="/industry/ai">artificial intelligence</a> models can now drive higher token consumption and convert more users into paying customers.
<h3>Seedance 2.0 becomes the growth driver</h3>
Competition for token usage has split into two main fronts: coding and video generation. In conventional text chat, companies have pushed model prices close to the floor. Coding and video generation still retain some pricing power, and ByteDance is benefiting from the latter through Seedance 2.0.
After ByteDance released Seedance 2.0 on February 10, the model quickly gained traction globally. It led the Artificial Analysis Video Arena rankings with an Elo score of 1,269 and surpassed leading alternatives, including Google’s Veo 3 and OpenAI’s Sora 2, across several metrics.
Its popularity also created shortages. During the Lunar New Year period, users at one point faced long queues, with videos just over ten seconds long taking as long as ten hours to generate. ByteDance later introduced measures including whitelists, giving customers with annual contracts stable access to the full-capability version of Seedance 2.0. That marked the beginning of the model’s commercialization.
Several sources from major tech companies told 36Kr that Seedance 2.0 alone can generate more than RMB 1 billion in monthly revenue for Volcano Engine, and that the figure is still rising. They expect Volcano Engine to continue raising its MaaS revenue target.
Seedance 2.0 has validated a simple point: when a model’s capabilities are clearly differentiated, paying customers tend to follow. Seedance’s penetration rate in the short drama industry has reportedly reached about 95%. “If you work in short dramas, it is hard not to be a Seedance user,” one video agent practitioner told 36Kr.
Seedance 2.0 currently ranks second globally by market share, behind only Google’s Veo. This year, its goal is to expand further overseas and become the world’s largest video model by market share. If that effort succeeds, Volcano Engine’s MaaS revenue is likely to keep rising.
whereRelatedArticle
<h3>ByteDance lags in AI coding</h3>
Not every model sold by Volcano Engine is performing as strongly.
Coding has not brought Volcano Engine much incremental revenue. The reason is straightforward: ByteDance Seed’s coding capabilities are not yet strong enough.
In coding, more than one person familiar with the matter told 36Kr that Zhipu AI, also known as Z.ai, may be the biggest winner.
In 2024, Zhipu bet on a training path similar to Anthropic’s, focusing on model intelligence and coding capabilities. Two years of accumulated work gave Zhipu an opportunity to take a leading position.
Zhipu CEO Zhang Peng disclosed on an earnings call that GLM’s API call prices increased by about 83% in aggregate in the first quarter of 2026. Despite several price adjustments, API call volume still grew 400%. The cached-hit token price for Zhipu’s GLM-5.1 is now close to the level of Claude Sonnet 4.6, marking the first time a Chinese-built large model has matched leading overseas providers on price in a core use case. Behind that pricing is GLM-5.1’s leading domestic position in coding capability.
Compared with video models, coding is already a more crowded revenue track.
At the end of 2025, API service provider OpenRouter proposed that early users who adopt an AI model in its first month after launch often show higher retention than those who arrive later. When users find an effective model, they tend to build loyalty around it and embed it deeply into their workflows.
As a result, Moonshot AI, MiniMax, cloud services from major companies such as ByteDance, <a href="/company/alibaba">Alibaba</a>, and <a href="/company/tencent">Tencent</a>, and even telecom operators have been rolling out coding plans and increasing sales efforts. Their aim is to attract users with relatively low prices, bring them into their ecosystems, generate large volumes of token consumption, and then find ways to improve margins.
36Kr has learned that Alibaba Cloud has set up several new MaaS sales teams since last year. These teams can work with its existing direct sales teams on deals. Their main task is to identify use cases, push enterprise customers to adopt agent capabilities, and increase token consumption.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3836973710423429">article</a> was written by Deng Yongyi for 36Kr.
Note: RMB figures are converted to USD at rates of RMB 6.79 = USD 1 based on estimates as of June 4, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

ByteDance raises Volcano Engine’s MaaS revenue target on Seedance 2.0 growth

East Asia

Artificial Intelligence

Deep Tech

Foundation and Large Models

AI Infrastructure

<a href="/company/kuaishou">Kuaishou’s</a> Kling AI is seeking its first funding round since its spinoff, according to IPO Zaozhidao, in a deal that would give the video generation business a pre-money valuation of USD 18 billion.
The round is also being viewed as a pre-IPO financing, according to the same source. Internal plans call for Kling to file a Hong Kong listing application in early 2027.
Kuaishou closed at HKD 48.98 (USD 6.2) a share on June 2, giving it a market capitalization of HKD 212.4 billion (USD 27.1 billion). Based on an approximate USD-HKD conversion, Kling AI’s USD 18 billion pre-money valuation is equal to roughly 66% of Kuaishou’s market value. That implies private investors are pricing the <a href="/industry/ai">artificial intelligence</a> business on stronger growth expectations than those typically applied to short video platforms.
<h3>Revenue growth supports Kling AI’s valuation</h3>
Kuaishou’s first-quarter 2026 results showed that Kling AI generated more than RMB 650 million (USD 95.8 million) in revenue during the period, up more than 300% year-on-year.
In March, Kling’s annualized revenue run rate, or ARR, was close to USD 500 million, four times the level recorded a year earlier. Kuaishou raised its full-year 2026 ARR guidance for Kling from USD 300 million to USD 500 million, citing rapid business growth.
Kuaishou chairman and CEO Cheng Yixiao said during the company’s earnings call that Kling’s growth is being driven by both enterprise API usage and consumer subscriptions. During the quarter, the number of paying users and the average monthly payment per user increased, while retention among enterprise and consumer users remained healthy. Cheng said this reflected Kling’s product stickiness among creative professionals.
In the first quarter of 2026, Kling strengthened its position in AI video generation through model iteration, product upgrades, and deeper penetration of professional use cases.
Kling launched its 3.0 series models in February. The models are built on an all-in-one product architecture and support multimodal input and output across text, images, audio, and video.
Kling also introduced a team-oriented pricing plan that supports real-time collaboration among as many as 15 members, allowing creators to manage team-based content production workflows more efficiently.
<h3>Professional use cases drive Kling AI adoption</h3>
According to Cheng, Kling AI is mainly used across three professional scenarios: advertising and marketing; film, television, and short drama; and gaming.
In advertising and marketing, Kling supports the full visual creation workflow, helping teams with creative visualization while maintaining consistency and stability for people and products across scenarios.
In film, television, and short drama, Kling can be used for script breakdowns, character and scene concept design, assisted storyboarding, and final video production. The platform can automate parts of the production process and may help reduce production timelines and costs.
In game production, Kling can support project planning, dynamic previews, visual effects, and narrative animation generation.
Kling 3.0 is currently ranked among the top Chinese text-to-video models. The latest <a href="https://artificialanalysis.ai/video/leaderboard/text-to-video">Artificial Analysis rankings</a> place Kling 3.0 fourth globally, behind <a href="/company/bytedance">ByteDance</a>’s Seedance 2.0, <a href="/company/alibaba">Alibaba</a>’s HappyHorse-1.0, and Kunlun’s SkyReels V4.
This <a href="https://xueqiu.com/2854806290/392673850">article</a> was adapted based on a feature originally written by SY and published on IPO Zaozhidao. KrASIA is authorized to translate, adapt, and publish its contents.
Note: HKD, RMB figures are converted to USD at rates of HKD 7.84 = USD 1 and RMB 6.79 = USD 1 based on estimates as of June 4, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Kuaishou’s Kling AI seeks fresh funding ahead of planned 2027 IPO

Venture Capital

Hong Kong

CRP Robot Technology, a Chengdu-registered <a href="/industry/robotics">robotics</a> firm, filed an updated prospectus with the Hong Kong Stock Exchange on May 31 as it seeks a main board listing. Guotai Haitong Securities is the sole sponsor.
The filing keeps CRP on track in its bid to become China’s first listed company focused on deploying embodied intelligence in industrial settings.
<h3>From controllers to complete robots</h3>
Founded in 2012, CRP has built a self-developed product portfolio across three categories: industrial robots, collaborative robots, and embodied robots.
According to Frost &amp; Sullivan data cited in CRP’s prospectus, the company ranked first among Chinese welding robot manufacturers by revenue in 2025. From 2023–2025, it sold products to customers in 40 countries and regions outside China, including Germany and Japan, and formed partnerships with more than 80 localized professional integrators overseas.
CRP focused on foundational robotics technology from its early years. Before 2018, it mainly supplied industrial robot controllers and complete electrical systems. In 2018, it expanded from key components into complete robot products, launching its first full robot that year. It launched its first embodied robot in 2022.
As of May 25, CRP’s industrial robot portfolio included more than 70 models across sectors such as metal and machinery processing, automotive and components, electronics, new energy, consumer goods, and healthcare. Its robots are used in major industrial scenarios, including welding, grinding, handling, cutting, and adhesive dispensing. Its embodied robot products address specific applications, including transmission tower welding, photovoltaic panel installation, grain sampling, wood panel handling, and airport baggage handling.
<h3>Industrial robots move closer to deployment</h3>
CRP released Lingshuo, an industrial wheeled humanoid robot, and Lingxun, a hybrid robot, in August 2025. The systems integrate environmental perception, autonomous decision-making, and precision execution, allowing them to interpret tasks, adapt to changing conditions, and work with existing industrial equipment. They are designed for advanced manufacturing environments.
In March this year, CRP publicly demonstrated RHM-T1W, its second-generation wheeled humanoid robot. The model combines a wheeled chassis with a humanoid upper body and supports autonomous obstacle avoidance, route planning, slope driving, and sub-millimeter motion control. It can bend, turn, grasp, and perform other complex movements, making it suited to demanding industrial scenarios such as inspection, handling, and assisted operations.
Its self-developed robot intelligence system uses a two-layer architecture. The lower layer is based on a 3D vision foundation model that helps the robot interpret complex industrial environments. The upper layer draws on knowledge bases covering more than 70 industries and over 2,000 process workflows. Combined with tactile feedback technology, it is designed to improve performance on specialized tasks.
Through a full-chain architecture spanning perception, decision-making, execution, and iteration, CRP aims to make robots more capable in industrial settings. Its expansion into embodied robotics builds on existing capabilities in motion control, robot bodies, multisensor fusion, industrial scene understanding, and software algorithms.
Industrial settings are widely viewed as one of the earliest markets where embodied robots can be commercialized. Compared with households, industrial environments usually have more standardized tasks, more accessible data, clearer commercial value, and stronger customer willingness to pay. CRP’s accumulated process data, scenario experience, and customer relationships in industrial robotics could therefore support the commercialization of its embodied robots.
CRP’s product portfolio reflects more than a decade of technical development. As of May 25, the company held 326 patents and 44 software copyrights, forming an intellectual property system across hardware, software, and algorithms.
This full-stack capability is important in industrial robotics because robots are not standalone hardware products. They are integrated systems comprising control systems, software algorithms, mechanical bodies, and industrial process know-how. Companies that control the underlying control layer have more flexibility in product iteration, cost optimization, and scenario expansion. In welding, where motion precision and process knowledge are critical, that control can be especially valuable.
<h3>Growth accelerates ahead of IPO</h3>
CRP recorded revenue of RMB 222 million (USD 32.7 million), RMB 234 million (USD 34.5 million), and RMB 324 million (USD 47.7 million) in 2023, 2024, and 2025, respectively. Revenue grew 38.5% year-on-year in 2025, accelerating from the previous year.
By revenue mix, CRP’s collaborative robot revenue grew nearly fourfold year-on-year in 2025, while revenue from embodied robots increased more than 2.4 times. The shift suggests the company is extending beyond traditional industrial robots into higher-value product categories.
CRP’s gross margin rose from 27.1% in 2023 to 33% in 2025. It also turned operating cash flow positive in 2025, reaching RMB 28.3 million (USD 4.2 million), indicating improvement in cash generation.
Since its establishment, CRP has completed several funding rounds. Its investors include Northern Light Venture Capital, Richen Capital, Shuanghuan Company, TTGG (Silicon Paradise), Eastern Bell Capital, Qixin Capital, Grand Yangtze Capital, HT Capital, and the Shanghai Electric Apparatus Research Institute (SEARI).
In its prospectus, CRP said the net proceeds from the IPO will mainly be used to strengthen R&amp;D capabilities, deepen partnerships with existing customers, build its brand in China, expand overseas, enhance manufacturing capabilities, and provide general working capital and operational flexibility.
This <a href="https://xueqiu.com/2854806290/392453885">article</a> was adapted based on a feature originally written by and published on IPO Zaozhidao. KrASIA is authorized to translate, adapt, and publish its contents.
Note: RMB figures are converted to USD at rates of RMB 6.79 = USD 1 based on estimates as of June 4, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

CRP advances Hong Kong IPO plan as it expands in industrial robotics

Robotics

Embodied Intelligence

… milestone in the development of Qatar’s financial sector.
Salwa REIT aims to provide investors with a more convenient and efficient way to participate in Qatar’s real estate market. It is also expected to broaden real estate investment channels and improve capital market depth and liquidity.
<h3>Qatar Chamber hosts entrepreneurship leadership forum</h3>
Qatar Chamber, in partnership with the Qatar chapter of the Entrepreneurs’ Organization and the Young Entrepreneurs Club, hosted a dialogue forum in Doha focused on entrepreneurship in times of uncertainty, according to <a href="https://thepeninsulaqatar.com/article/26/05/2026/qc-holds-forum-on-entrepreneurial-leadership-in-times-of-risk">The Peninsula</a>.
The forum was held under the theme “Head. Heart. Guts.” focused on entrepreneurial leadership amid risks and challenges, exploring decision-making in a rapidly changing business environment and the practical issues startups face during economic and technological transformation.
This <a href="https://mp.weixin.qq.com/s/DFTjpjS0AzWqRwATiMI4Tg">article</a> was adapted based on a feature originally written and published by Al Shasia. KrASIA is authorized to translate, adapt, and publish its contents.
Note: QAR, RMB, SAR figures are converted to USD at rates of QAR 3.64 = USD 1 and RMB 6.79 = USD 1 and SAR 3.75 = USD 1 based on estimates as of June 4, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Middle East weekly: Invest Qatar concludes China roadshow, Core42 secures HSBC financing, Salwa REIT Fund launches, and more

Saudi Arabia

Qatar

Middle East

… child, and that is something no commercial company can bear. A wheeled version, by contrast, can remain stable and stationary after losing power and will not topple. In terms of safety, stability, deployment speed, and cost control, it is better suited to large-scale commercial use,” Li told 36Kr.
The core of role-based deployment is stability, safety, and deliverability. At this stage, Keenon sees those as the key advantages of wheeled humanoid robots.
Role-based deployment, collaboration between specialized and general-purpose robots, a layered product matrix, and a wheeled-first approach form the core of Keenon’s embodied intelligence strategy. But a clear strategy is only the beginning. To achieve scaled deployment, companies must compete on more than technical specifications and stage performance.
<h3>Commercialization is the test</h3>
Technical parameters and lifelike movement may attract attention, but they do not automatically create long-term differentiation. In robotics, the more durable advantage may be end-to-end commercialization: the ability to deploy, mass produce, support, and profit from machines in real environments.
Over 16 years, Keenon has used commercial deployments to build what it sees as comprehensive industrialization capability. That includes scenario adaptation, engineering-led mass production, global delivery, cost control, and customer trust. These capabilities can determine whether a robotics company can move through industry cycles.
The first barrier is scenarios and data. Scenario data is the foundation of technological iteration.
Keenon said it has placed more than 100,000 units into real roles worldwide, accumulating long-term operational data on obstacle avoidance, interaction, and practical use. Because this field data is tied to actual roles, it can support algorithm iteration, improve device stability, shorten the path from prototype to scaled deployment, and create a scenario-data advantage that is difficult for newer entrants to replicate.
Data shapes the product ceiling. Engineering-led mass production sets the deployment floor. The industry’s common pain point is that prototypes are easier to build than stable volume production. Short-term R&amp;D can produce a strong prototype, but supporting millions of stable operations and standardized global delivery requires long-term engineering accumulation. Capital can accelerate this process, but it cannot replace it.
Keenon’s approach is to build its own R&amp;D, production, and supply chain capabilities. From core components to whole-machine integration, and from reliability optimization to cost control, the company says its systems have been tested through more than a decade of engineering work and the real-world validation of more than 100,000 shipments.
Keenon’s overseas work, global footprint, and customer relationships have also created a time-based barrier. The company says its business covers more than 70 countries. Through its channels and after-sales systems, it can use field experience and customer feedback to iterate products. This gives its humanoid robots a platform for proof-of-concept validation and scaled deployment, with advantages in deployment efficiency and tolerance for error.
Across these efforts, Keenon’s guiding idea is that robotics must be anchored in deployment value. Product definition and technology iteration revolve around reliability, safety, and commercial returns. The company is not trying to build conceptual props. It is trying to deliver productivity tools that can take on real roles, run stably, and offer strong cost performance.
Industry trends point in a similar direction. Some humanoid robot makers have begun expanding into nonhumanoid product lines to close commercialization gaps and build a healthier cycle through mature deployment scenarios.
In 2026, the humanoid robot market is moving from concept-driven enthusiasm toward a more demanding phase of commercialization. Mass production does not equal commercialization. Shipments do not equal deployed value. Advanced form does not equal customer recognition. The market’s core demand remains unchanged: machines that solve real problems, replace repetitive work, and generate returns.
Keenon has already validated a development path for embodied intelligence. It is not confined to a single scenario, held hostage by product form, or trapped in between capital-backed factions. Instead, its strategy is to anchor itself in customers’ real needs, focus on commercial deployment, and dig deep into role-based value.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3825951391240838">article</a> was written by Xiao Xi for 36Kr.

Keenon Robotics prioritizes function over form in its robot lineup

… is to go deeper into Thailand rather than to expand internationally," he said. "We know the Thai market quite well. We will try to optimize our technology and we will localize as we understand each community."
However, Thailand's economic growth has been relatively weak, hurt by high <a title="" href="https://asia.nikkei.com/spotlight/asean-money/thailand-s-household-debt-crisis-acts-as-brake-on-anemic-growth" target="_blank" rel="noopener">household debt</a> and rising fuel prices brought on by the US-Iran war.
While acknowledging "macroeconomic challenges," Yod said he sees opportunities.
According to Momentum Works' research, Thailand's food delivery growth rate was the highest in the region, expanding 22% in 2025, outpacing Malaysia and Vietnam, both at 19%.
"Food delivery actually continued to grow at a fast pace even though the economy still has some challenges," Yod said, adding that the weak economy encouraged people to eat at home, and food delivery—which tends to be less expensive than dining out in Thailand due to promotion deals—is a solution. "Food delivery remains very frequent and a very economical way to enjoy food compared to dining out."
In the final quarter of 2025, Thailand introduced the "Khon La Khrueng" (half-half) <a title="" href="https://asia.nikkei.com/politics/turbulent-thailand/new-thai-pm-plans-revival-of-shopping-stimulus-to-boost-economy" target="_blank" rel="noopener">shopping subsidy program</a>, in which the government covers 50% of consumers' spending for food and daily necessities to spur spending. Line Man joined the project, enabling its users to order food at subsidized prices.
The second phase of the shopping subsidy starts in June, and Yod said Line Man will join again. "We joined the Khon La Khrueng program last year, and we expect to do the same this year," he said, adding that the company expects its revenue to grow "at least 20%" in 2026.
According to the company, its revenue for 2024, the latest year for which figures have been disclosed, was THB 16.7 billion (USD 512.3 million), up 44% from 2023. But it remained unprofitable with a net loss of THB 356 million (USD 10.9 million) that year.
Yod acknowledged that food delivery operators are engaged in an intense price war and that the competition will persist.
"I think we will always be in a price war," he said. "Online food delivery platforms will continue to offer discounts … to give the best prices to users." He added that this kind of "fair competition" can be expected in a growing market.
Kedsuda Inchai, a 38-year-old office worker in Bangkok, told Nikkei Asia she uses Line Man "because it has a lot of food options and its delivery price is quite cheap."
Analysts say that although Thailand's food delivery sector is growing rapidly, profit margins can be expected to remain slim due to intense competition.
"Grab uses promotions to offer discounts on food, while Line Man cuts the delivery price," said Passakorn Wangwiwatcharoen, an analyst at Asia Plus Securities. "Both strategies squeeze profit margins."
Passakorn added that cut-rate strategies are not sustainable.
Yuto Ikeuchi, a Bangkok-based consultant at Mitsubishi UFJ Research and Consulting, pointed out that Thailand's food delivery operators are currently facing higher consumer prices and delivery costs that could affect demand and squeeze their margins.
"In addition, major players in the sector have been investing heavily in advertising and infrastructure to build their platforms," he said, adding that "when these investments will begin to pay off remains a key concern for investors."
This article first appeared on <a href="https://asia.nikkei.com/spotlight/asean-money/thailand-s-line-man-pushes-beyond-food-delivery-eyes-2027-ipo">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.kr-asia.com/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.
Note: THB figures are converted to USD at rates of THB 32.60 = USD 1 based on estimates as of May 29, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Thailand's Line Man pushes beyond food delivery, eyes 2027 IPO

On-demand Services

Food Delivery

Consumer Economy

Thailand

Southeast Asia

… Mall.
whereRelatedArticle
Doubao is not the first product to try to complete the AI shopping loop. On May 11, Alibaba’s Qwen officially connected to Taobao and enabled AI-driven shopping features. In September 2025, ChatGPT also <a href="https://openai.com/index/buy-it-in-chatgpt/">launched Instant Checkout</a>, trying to guide users to place orders and complete payments directly within the AI chat interface. But in March, OpenAI canceled the feature.
Doubao and Qwen have an advantage because they are backed by Douyin Mall and Taobao, respectively, two mature e-commerce systems. Product catalogs, merchant ecosystems, payment, and fulfillment capabilities already exist. That makes AI shopping appear more viable in theory.
Even so, AI shopping faces two questions:
<ul>
<li aria-level="1">First, is AI shopping a real user need? During the Lunar New Year, Alibaba <a href="https://kr-asia.com/alibabas-latest-qwen-subsidies-are-a-bet-on-agentic-commerce">invested RMB 3 billion (USD 442.6 million) in “red packet” subsidies</a> to encourage users to order milk tea through its Qwen app, trying to cultivate the habit of using AI to make consumption decisions. But it remains unclear whether the campaign helped develop long-term user retention. Moreover, compared with ordering food delivery, shopping is a more complex consumption scenario that often relies on comparison and deliberation.</li>
<li aria-level="1">Second, will consumers trust product recommendations from AI? As AI search and recommendation capabilities become more important, some merchants have already started using GEO, or generative engine optimization, to influence how large models crawl and rank information. Once AI recommendations are shaped by paid placement and commercial interests, it remains to be seen whether consumers will view them as objective advice or as another advertising channel.</li>
</ul>
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3834544830721671">article</a> was written by Xiao Sijia, with contributions from Zhou Xinyu, for 36Kr.
Note: RMB figures are converted to USD at rates of RMB 6.78 = USD 1 based on estimates as of June 3, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Doubao prepares paid subscriptions as ByteDance seeks AI returns

Doubao

Wuxi-based Autolink Intelligence Tech updated its <a href="https://www1.hkexnews.hk/app/sehk/2026/108596/documents/sehk26052902439.pdf">prospectus</a> on May 29, as it continues to pursue a main board listing on the Hong Kong Stock Exchange. CICC and Guotai Haitong Securities are serving as joint sponsors.
Founded in 2014, Autolink’s portfolio now spans in-vehicle computing solutions and zonal controller solutions. The company has established partnerships with China’s five largest domestic-brand automakers, according to its prospectus. As of May 22, its products covered 45 brands under those automakers. By the same date, its cumulative number of vehicle model design wins, an industry term for being selected to supply technology for specific models, had increased to 164.
At the product level, Autolink said it became the first company in the world in 2021 to launch and mass produce an intelligent cockpit domain controller based on Qualcomm’s Snapdragon SA8155P platform. According to Frost &amp; Sullivan data cited in the prospectus, cumulative shipments of cockpit domain controllers based on Qualcomm’s SA8155P platform had exceeded 2.3 million units as of May 22, ranking first globally.
In cockpit-driving integration, Frost &amp; Sullivan data shows that Autolink’s AL-A1 series, built on Qualcomm’s SA8775P platform, was the world’s first single-chip cockpit-driving integrated product to debut and enter mass production. The product was installed in both the battery-powered and range-extended versions of BAIC’s Arcfox Alpha T5, which entered mass production in the third quarter of 2025. As of December 31, 2025, products based on the SA8775P platform had secured design wins for ten vehicle models. As these projects move from design wins to mass production, cockpit-driving integration could become an important source of revenue growth for Autolink.
<figure id="attachment_162419" aria-describedby="caption-attachment-162419" style="width: 1920px" class="wp-caption alignnone"><img loading="lazy" decoding="async" class="size-full wp-image-162419" src="https://console.kr-asia.com/wp-content/uploads/2026/06/Autolink-Intelligence-Tech-AL-A1-Auto-Shanghai-2025.jpg" alt="Photo of the AL-A1 integrated domain controller, on display at Auto Shanghai 2025." width="1920" height="1280" srcset="https://console.kr-asia.com/wp-content/uploads/2026/06/Autolink-Intelligence-Tech-AL-A1-Auto-Shanghai-2025.jpg 1920w, https://console.kr-asia.com/wp-content/uploads/2026/06/Autolink-Intelligence-Tech-AL-A1-Auto-Shanghai-2025-720x480.jpg 720w, https://console.kr-asia.com/wp-content/uploads/2026/06/Autolink-Intelligence-Tech-AL-A1-Auto-Shanghai-2025-1024x683.jpg 1024w, https://console.kr-asia.com/wp-content/uploads/2026/06/Autolink-Intelligence-Tech-AL-A1-Auto-Shanghai-2025-768x512.jpg 768w, https://console.kr-asia.com/wp-content/uploads/2026/06/Autolink-Intelligence-Tech-AL-A1-Auto-Shanghai-2025-1536x1024.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /><figcaption id="caption-attachment-162419" class="wp-caption-text">The AL-A1 integrated domain controller on display at Auto Shanghai 2025. Photo source: Autolink.</figcaption></figure>
For next-generation central computing products, Autolink released its Deep Fusion electronic and electrical architecture (EEA) in January. The architecture integrates a central computing platform, zonal controllers, and high-speed optical communication. It is designed to support advanced driving assistance, on-device large models, in-vehicle <a href="/industry/ai">artificial intelligence</a> agents, ultra-high-definition video perception, and full-scenario intelligent interactions.
As large model capabilities move from the cloud into vehicles, intelligent cockpits are evolving from collections of functions into in-vehicle AI interaction gateways. Autolink has positioned itself around this trend through two product paths, AI box and AI cockpit:
<ul>
<li aria-level="1">Its AI box connects independently with a vehicle’s existing cockpit and driving systems, adding on-device AI capabilities to current vehicle models. It is designed to help automakers meet demand for AI upgrades from existing users more quickly and with lower modification costs.</li>
<li aria-level="1">AI cockpit, by contrast, is aimed at mid- to high-end and premium models. It emphasizes the ability to run on-device large models and deliver low-latency responses for products built on newly developed vehicle architectures.</li>
</ul>
In in-vehicle optical communication, Autolink has begun joint R&amp;D and validation of in-vehicle optical communication modules with a leading domestic optical communication company. The work focuses on applying PCIe 4.0 optical communication technology to vehicle products. Although the initiative remains in an early incubation stage, it could give Autolink a differentiated position as automakers move toward the next generation of vehicle EEA.
Autolink’s early position in cockpit domain controllers and cockpit-driving products, along with its record of scaled mass production, suggests it has built platform-level capabilities. Its early work in AI products and optical communication also gives it a longer-term reserve for intelligent in-vehicle experiences and the communication systems that support them. The company is seeking to move deeper into higher-value vehicle architecture layers and become a long-term technology partner for automakers as they develop more intelligent vehicles.
A key reason Autolink has been able to expand its product portfolio is its in-house R&amp;D and platform-based architecture. As of December 31, 2025, the company had more than 500 R&amp;D employees, with experience across system architecture, middleware, functional algorithms, testing and validation models, and other areas of the automotive electronics value chain. This has given it full-stack in-house software and hardware capabilities:
<ul>
<li aria-level="1">On the software side, Autolink has development capabilities covering base software platforms, middleware, and upper-layer applications.</li>
<li aria-level="1">On the hardware side, it independently designs, integrates, and debugs domain controller hardware platforms, supporting faster adaptation for different customers’ projects.</li>
</ul>
Autolink said in its prospectus that it plans to use the net proceeds from its IPO mainly for R&amp;D of connected vehicle solutions, strengthening its international capabilities, expanding production capacity, working capital, and other general corporate purposes.
This <a href="https://xueqiu.com/2854806290/391899467">article</a> was adapted based on a feature originally written by Stone Jin and published on IPO Zaozhidao. KrASIA is authorized to translate, adapt, and publish its contents.

Autolink makes its Hong Kong IPO case with smart vehicle architecture