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… for Labor Education &amp; Research criticized Grab for profiting off an already financially disadvantaged workforce.
"It knows that riders are cash-strapped and that the nature of work requires constant financial maintenance. It's betting on the future labor of a rider, who bears the real risk and repeating crises of debt, stress, and dependency," she told Nikkei Asia.
Cheryll Soriano, a professor at De La Salle University and principal investigator of Resilient Platform Work Philippines, added: "Platforms promote loans through push notifications based on tenure and driving data. We have evidence from workers who were pushed loan invitations while still completing a previous loan cycle," she told Nikkei Asia.
She also said that it's hard for riders to grasp the gravity of the interest when they mostly only see the daily deductions.
Lawyers approached by Nikkei Asia said a court could force Grab to lower its interest rates.
Soriano said that a platform like Grab can "incentivize workers to take the longest payment period with higher interest rates."
Grab denied this, saying, "At no point are partners incentivized, nudged, or algorithmically steered toward higher-interest products or longer tenure options."
Grab holds monthly raffles and offers rewards for its riders who take loans with certain terms. To enter Grab's recent Christmas raffle, a rider had to have taken out a loan with the maximum repayment period.
One rider demonstrated that for a chance to win prizes, it was necessary to take out a PHP 13,000 (USD 218.8) loan that must be repaid through daily deductions of PHP 62.07 (USD 1) over 360 days, totaling PHP 22,343 (USD 376.1). The rider would pay almost double the principal amount with an effective annual interest rate of 234%.
Riders face a critical decision if they fall ill or if one of the on average 20 annual typhoons in the country hits their area: stay at home or risk the consequences of working just to keep deductions from piling up.
The motorcycle taxi association leader urges platforms to "have a heart. We can't stop force majeure and the apps should understand and suspend deductions."
Grab asserts it follows a "standard calamity response [which] can include offering loan payment holidays to driver-partners with existing loans." Riders told Nikkei they have seldom experienced this. The Philippines experienced 23 tropical cyclones in 2025. Grab did not provide the number of loan repayment holidays it gave during the year.
This article first appeared on <a href="https://asia.nikkei.com/spotlight/asean-money/grab-charges-philippine-bike-riders-over-230-interest-for-in-app-loans">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: PHP figures are converted to USD at rates of PHP 59.4 = USD 1 based on estimates as of March 10, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

Grab charges Philippine bike riders over 230% interest for in-app loans

Grab

Southeast Asia

Fintech

Lending

Philippines

<a href="/company/catl">Contemporary Amperex Technology</a>, better known as CATL, saw its shares climb after posting 2025 profit ahead of expectations, offering investors a fresh sign that growth in energy storage and overseas markets is helping the Chinese battery maker cushion a weaker <a href="/industry/ev">electric vehicle</a> backdrop.
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Net income rose 42.3% year-on-year to RMB 72.2 billion (USD 10.4 billion), while revenue increased 17% to RMB 423.7 billion (USD 61.2 billion), according to the company’s disclosure. CATL also reported lithium battery sales of 661 gigawatt-hours, up 39% from a year earlier.
The results suggest CATL is navigating the industry slowdown better than many battery peers, even if the recovery still rests mainly on its EV battery business. Revenue from EV batteries rose 25.1% to RMB 316.5 billion (USD 45.8 billion) and accounted for nearly three-quarters of group revenue, while energy storage battery revenue grew 9% to RMB 62.4 billion (USD 9 billion).
That puts CATL in a stronger position as battery makers look for growth beyond China’s crowded EV market. Energy storage has become a key part of that shift, helped by renewable power buildout and rising electricity demand from data centers, though CATL’s own revenue mix still shows a company far more battery-led than its broader positioning implies.
Overseas expansion remains central to CATL’s narrative. Revenue from international markets rose 17.5% to RMB 129.6 billion (USD 18.7 billion) in 2025, accounting for 30.6% of total sales. The company’s overseas gross margin also remained above its domestic margin, indicating that international growth is supporting profit as well as scale.
Margins improved at the group level, though not because CATL suddenly made more on every core battery sold. Gross margin rose to 26.27% from 24.44%, but the annual report said the main lift came from battery materials, recycling and other businesses. Gross margin in EV batteries and energy storage batteries was broadly flat.
CATL is also trying to hold its lead through technology and infrastructure. The company highlighted sodium-ion batteries, battery swapping, electric vessels and zero-carbon industrial projects as future growth areas, while R&amp;D expenses rose 19% year-on-year to RMB 22.1 billion (USD 3.2 billion). Global production capacity reached 772 GWh, with another 321 GWh under construction.
That spending reflects a broader ambition. CATL wants investors to look beyond cells and packs toward battery swapping, energy infrastructure and other operating platforms. The company said it had built more than 1,000 Choco-Swap stations for passenger vehicles across 45 cities, over 300 heavy truck battery swapping stations across 26 provinces, and deployed close to 1,000 electric vessels globally, while also highlighting progress in eVTOL (electric vertical takeoff and landing) vehicles and zero-carbon industrial parks.
The direction is clear enough, but the financial evidence is thinner. Without more granular disclosure, those newer businesses are easier to treat as growth options than as proof that CATL has already built a meaningfully broader earnings model.
The balance sheet, however, gives it time to keep building. Monetary funds rose to RMB 333.5 billion (USD 48.2 billion) at the end of 2025 from RMB 303.5 billion (USD 43.9 billion) a year earlier, while net assets attributable to shareholders increased 36.5% to RMB 337.1 billion (USD 48.7 billion). Fourth-quarter net profit attributable to shareholders also rose to RMB 23.2 billion (USD 3.4 billion) from RMB 14 billion (USD 2 billion) in the first quarter, suggesting earnings strengthened through the year.
CATL’s business is broadening, but the financial engine is still familiar. 2025 was a strong year. It just was not yet proof that the company’s newer platforms matter as much as its core battery business.
Note: RMB figures are converted to USD at rates of RMB 6.92 = USD 1 based on estimates as of March 10, 2026, unless otherwise stated. USD conversions are presented for ease of reference and may not fully match prevailing exchange rates.

CATL’s business is broadening, but EV batteries still drive profit

East Asia

China

Deep Tech

Batteries

Energy

… Series B1 funding from Hefei Luzhou Industry Fund. The company develops AI-driven systems for transportation management and smart mobility. Prior to this investment, Sinoits had received backing from investors including Qualcomm Ventures, Glory Ventures, Seashell Capital, Soaring Capital, Highsea Capital, and CCCC Capital, as well as support from Nanjing Communications Group to build regional smart transportation ecosystems. —<a href="https://36kr.com/p/3706859579486597">36Kr</a></li>
<li aria-level="1"><a href="https://www.lemanbio.com/en">Leman Biotech</a>, a cell therapy developer, has raised nearly RMB 200 million (USD 28 million) in a new round jointly led by Yuecai Zhongyin Private Equity and XtalPi. Other participants include Kuangshi Zhixing, Mony Valley, Tailong VC, Zhongshan Investment Holdings, and individual investors, with existing shareholder Fuho Capital increasing its stake. The company is advancing low-dose metabolism-enhanced CAR-T cell therapies and operates two proprietary platforms that combine AI and metabolic reprogramming technologies to develop cell therapy treatments. Proceeds will support clinical trials, automated manufacturing process development, and the clinical translation of therapies targeting solid tumors. —<a href="https://36kr.com/p/3707151883382917">36Kr</a></li>
</ul>
whereRelatedArticle
<h3>Aonic, Dyna.Ai, Spirit AI, and others made recent headlines:</h3>
<ul>
<li aria-level="1">Aonic, a Malaysia-based drone technology company, raised USD 10 million in a Series A funding round led by Kairous Capital, with backing from Jelawang Capital.</li>
<li aria-level="1">Dyna.Ai, a Singapore-based developer of agentic AI systems, has closed a Series A round led by Lion X Ventures, raising an undisclosed eight-figure USD sum. The round included participation from tech company Adata, an unnamed South Korean financial institution, and several finance industry veterans.</li>
<li aria-level="1"><a href="https://www.spirit-ai.com/en/">Spirit AI</a>, one of China’s embodied intelligence companies, secured nearly RMB 2 billion (USD 280 million) across two consecutive rounds. Investors include Yunfeng Capital, HongShan, Chaos Investment, and industrial and state-backed funds such as Synstellation Capital, TCL Capital, Mornway Capital, Chongqing Industrial Parent Fund, and Hangzhou Finance and Investment Group. Existing backers Shunwei Capital and Prosperity7 also participated.</li>
</ul>
If there are any news or updates you'd like us to feature, get in touch with us at: <a href="mailto:hello@kr-asia.com">hello@kr-asia.com</a>.

Deals in brief: Gobi Partners backs Cortical Labs, TVS invests in Vietnam’s Dat Bike, 11 China deals, and more

Venture Capital

Private Equity

Investment

Merger &amp; Acquisition

Singapore

Vietnam

Indonesia

Oceania

… Children's tableware costs nearly RMB 400 (USD 56.0) per set. Ovens priced at RMB 50,000 (USD 7,000) are used primarily to prepare lamb ribs.
One investor noted that Xibei's lamb spine contains about 30% meat, compared with an industry norm closer to 10%. The cost difference can exceed fivefold.
“Consumers may not need that much meat,” the investor said. “Even if it's better, if it's too expensive, it may not be what I want.”
The same tension applies to frozen broccoli, sourced at RMB 8 (USD 1.1) per jin, or about 600 grams.
“Many of the frozen ingredients from the central kitchen are processed using very advanced rapid freezing equipment,” said Li Ni (pseudonym), a former Xibei store manager. “They actually move quickly through inventory.”
A similar example comes from a well-known seafood buffet eatery in Dalian that invested heavily in liquid nitrogen freezing technology. The restaurant promoted the idea that nitrogen-frozen crabs could taste even better than live ones, but few diners were convinced. One consumer who visited the restaurant told 36Kr that locals overwhelmingly chose live river crabs instead. For most diners, seafood simply needs to be alive and fresh, just as many consumers today expect restaurant food to be freshly prepared and reasonably priced.
When consumption was broadly upgrading, higher costs were easier to justify. In the current environment, they risk becoming misaligned with demand.
“Sometimes we wondered whether the boss focused more on what he wanted to sell than on what customers wanted,” Weng Yang said.
Li Ni said Jia had long insisted on paying above-market wages. “If the market pays a server RMB 5,000 (USD 700) a month, we would recruit at RMB 5,500 (USD 770) or RMB 6,000 (USD 840),” he said. After recent adjustments, each store is expected to employ about ten ambassador-style roles earning more than RMB 10,000 (USD 1,400) per month, pushing labor costs toward 35% of revenue. That figure is comparable to Haidilao's 33.8%.
Ultimately, the virtuous cycle of well-paid staff, better service, and satisfied customers breaks down when traffic falls.
Jia once argued that being expensive is not the problem, being expensive without delivering value is. Yet in today’s consumer environment, Xibei’s pricing has arguably become the main source of customer dissatisfaction.
<h3>Jia Guolong’s sweeping bets</h3>
For Jia, learning to make things cheaper has never been a natural instinct.
Before returning to the core business in early 2025, Jia spent roughly a decade experimenting with new formats. His ambition was sweeping, for every city in the world, every street, to have a Xibei outlet.
A 300-square-meter Xibei Youmian Village store could not support that vision, so Jia began experimenting with smaller formats and new brands.
Zhou Luo (pseudonym), a former Xibei employee who worked on the Jia Guolong Kung Fu Cuisine project, said the company spared little expense. “We spent more than RMB 100 million (USD 14 million) in a single year,” he said. “There were more than 300 R&amp;D consultants. Our only task was to map the country and find the best dishes, then pay high prices to buy the recipes and turn them into standardized operating manuals.”
“A single mapo tofu recipe could cost tens of thousands of RMB,” Zhou Luo said. “And that wasn’t the end of it. One chef said his version was the best, another said theirs was the best, so we bought both to compare.”
After acquiring the recipes, Xibei began building factories to mass produce the dishes. “We manufactured a large number of products,” Zhou Luo said. “At the time, in the consumer-facing pre-prepared meal market, Jia Guolong Kung Fu Cuisine was among the most advanced.”
Despite high expectations, the ventures struggled. Fast food and casual dining concepts followed similar trajectories: ambitious launches followed by abrupt closures.
In total, the company spent more than RMB 1 billion (USD 140 million) on new ventures.
“One reason many projects failed is that the founder’s will is extremely strong,” Zhou Luo said. “Senior managers execute forcefully, and while Xibei may be a large company, sales cannot always support the costs when spending becomes excessive.”
<h3>The path ahead</h3>
Investors said some progress is visible: fewer side ventures, greater founder oversight, and a stated willingness to prioritize customer preferences. Yet doubts remain over whether Jia can fully recalibrate the company's strategy.
Some argue Xibei must lower prices. Others counter that, given its current margins, deeper price cuts could accelerate financial decline.
The challenge may not be competing on price alone, but delivering stronger value within an RMB 80–100 (USD 11.2–14.0) average ticket range.
If Xibei moves upmarket, it must rebuild consumer trust. If it moves downmarket, it must dismantle years of operational buildup around premium inputs.
“From zero to one, Xibei was built by energetic, capable people alongside Jia,” Zhou Luo said. Many of those early standouts have since moved on.
In 2022, an IPO by 2026 once seemed plausible. That ambition has faded.
Even if Xibei survives the current moment, Jia may first need to change himself.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3711330673242249">article</a> was written by Ren Cairu, Li Xiaoxia, and Xiao Sijia for 36Kr.

Can Jia Guolong save Xibei by stepping back?

Consumer Economy

Asian stocks were hit hard on March 9 as the US and Israel's war on Iran drove up oil prices and worries swirled over the economic fallout from the conflict amid signs tensions are broadening across the Middle East.
South Korea and Japan led falls in the region.
The KOSPI had dropped almost 9% at one point, triggering the Korea Exchange to issue a circuit breaker on trading, before ending the day down 6%. KOSPI heavyweights SK Hynix and Samsung Electronics declined nearly 10% and 8%, respectively.
Japan's benchmark Nikkei Stock Average tumbled as much as 4,200 points, or 7.6%, to hit a two-month intraday low. The blue chip gauge trimmed some of its losses but ended the day down 2,892.12 points, or 5%, at 52,728.72. In terms of the absolute point drop, that marked the third biggest fall in the index's history. The broader Topix also declined close to 4%.
Both countries' stock markets were trading at historic highs before the Iran war erupted. Compared to their February all-time closing highs, South Korean equities have fallen 17% while Japan's are down 10%.
Other Asian stock markets were also under pressure. Vietnam's VN Index was down over 6% while Taiwan's TAIEX and the Philippines' PSEi were lower by around 5%. Australia's equity benchmark and Thailand's SET Index were down by around 3%, and India's BSE Sensex, Singapore's STI, and Hong Kong's Hang Seng Index were lower by about 2%.
The steep selloff came on the back of higher oil prices. US benchmark West Texas Intermediate crude breached USD 110 per barrel, touching its highest level since July 2022. The price of Brent crude, the international benchmark, has also surged, with futures up nearly 20% to over USD 100 per barrel.
Energy prices are continuing to climb as the Iran conflict shows few signs of easing. Vital desalination plants in Iran and Bahrain have reportedly been attacked in what many analysts call a serious escalation that could have a major impact on civilian life and could make it even harder for the region to sustain oil and gas production on which the rest of the world depends.
Countries like South Korea and Japan, who heavily rely on energy imports, are likely to be significantly affected. Oil shipments from the Persian Gulf are currently suspended due to fears that tankers could come under attack from Iran, which occupies the entire northern coast of the key Strait of Hormuz.
In a report on March 5, Kpler's director of oil and tanker research, Andon Pavlov, pointed out that the closure of the Strait of Hormuz "represents one of the most significant crude oil supply disruptions in modern history" as roughly 16 million barrels per day of petroleum products have stopped flowing through.
"Asia faces a combined reduction in refining throughput of close to three [million barrels per day]" and countries with the highest exposure include South Korea, Thailand and India, he noted.
Japan also imports 95% of its oil from the Middle East, with the UAE and Saudi Arabia its two biggest suppliers.
In the Tokyo market, shares declined across the board, including electronics makers, retailers, tech stocks, and energy-related companies. The risk-off sentiment pushed investors to take profits on tech stocks, which have been enjoying a rally on the back of the <a href="/industry/ai">artificial intelligence</a> boom.
Shares in oil company Idemitsu Kosan declined almost 3%. In a sign of the broadening repercussions of the war on the Japanese economy, Idemitsu has notified business partners that it may stop domestic ethylene production if the Strait of Hormuz blockage continues to prevent raw material imports. Without ethylene, plastics cannot be churned out, which in turn could hamper production of autos and electronic appliances.
Goldman Sachs strategists warned in a note that there is "the risk of a major correction in the Japanese equities market given the relatively benign market conditions since last April's Liberation Day-related volatility," referring to trade tariffs announced in early April by US President Donald Trump.
Since April 2025, Japanese equities have had no major correction, which is "extremely unusual in historical terms," the investment bank wrote in a note on March 9. "This changed last week however, and we think that these elevated levels of volatility could continue from here until the geopolitical situation in the region becomes clearer."
The Iran conflict is continuing to unnerve investors. Along with the intensifying attacks, Iran over the weekend chose Mojtaba Khamenei to succeed his father Ayatollah Ali Khamenei, who was killed in the strikes. Mojtaba is known for having close ties to the country's hardline Islamic Revolutionary Guards Corps.
<a title="" href="https://asia.nikkei.com/business/markets/currencies/asian-currencies-weaken-as-iran-conflict-intensifies2" target="_blank" rel="noopener">Currencies were also trading weaker</a> against the dollar on March 9 as investors rushed toward safe-haven assets like the greenback. The Japanese yen depreciated about 0.6% into the range of JPY 158 per USD 1. The Korean won has also fallen near the KRW 1,500 per USD 1 mark.
"Global markets are firmly in risk-off mode," according to Lloyd Chan, senior currency analyst at MUFG Global Markets Research in Singapore. "Net oil-importing economies in Asia are particularly exposed, with currencies and equity markets likely to face downward pressure."
"Based on net oil trade balances and dependence on Middle Eastern oil supply, Thailand, [South] Korea, and the Philippines appear especially vulnerable to oil price shocks and potential supply disruptions," he added.
This article first appeared on <a href="https://asia.nikkei.com/business/markets/asia-stocks-dive-as-crude-oil-spikes-on-iran-crisis">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>.

Asia stocks dive as crude oil spikes on Iran crisis

Malaysia

Myanmar

Thailand

Cambodia

Japan

South Korea

Hong Kong

India

… needed specifically for AI server deployments. However, we estimate that a single Nvidia GB200 server rack requires around 120 NOR flash chips, roughly equivalent to the amount used in some 120 personal computers. That gives you a sense of the scale and the enormous appetite for memory driven by AI," Winbond's Chen said.
An executive with an optical module supplier serving Nvidia and Amazon Web Services said supply crunch concerns are growing. "Not just the large chips but also some small chips related to AI are in short supply, and we are very worried about it, as it will affect the smoothness of our shipment to end customers," the executive said. "Those small, overlooked chips and components not only are in constrained supply, but also much more expensive now."
Nanya Technology, the world's fifth-ranked DRAM memory chipmaker, said it would more than double its capital spending for 2026, after nearly three years of a severe market downturn.
President Lee Pei-Ing said there are supply gaps in almost every type of DRAM and in all types of markets.
"Some more urgent ones are from consumer electronics and automotive solutions," Lee said. "We see overall market demand as strong across every region worldwide, particularly from the US and China, as well as in Japan and South Korea."
Joseph Tung, CFO of ASE, said that demand currently far exceeds supply, creating a favorable pricing environment. He added that the company's leading-edge chip packaging business is expected to double in 2026, while its mainstream packaging segment, some of which supports chips used in building out the AI ecosystem, is also experiencing solid growth.
While many component makers in the AI space are racing to expand capacity, they also warn there is still some uncertainty.
Ping Cheng, chairman and CEO of Delta Electronics, the world's biggest maker of power supply solutions, said the company plans to spend more than TWD 46.1 billion (USD 1.5 billion) in 2026 capex, its highest level ever, and is scouting locations to build new plants.
Cheng said Delta always builds facilities two to three years in advance to prepare for visible future demand. "But in the past two years, the demand for AI came so sudden and ferocious that it occupied many of our prepared new capacities ahead of our plans. We have to look for locations now to build more plants for the 2028 demand and beyond," he said last week at an investors conference.
"The growing momentum for data center buildup is likely to continue this year, but the market is also moving very dynamically," he added. "The AI data center buildup could still face many challenges, and there's a shortage of construction crews as well as issues surrounding water and power supplies in many places. Those can all be issues that hinder the speed of massive construction."
This article first appeared on <a href="https://asia.nikkei.com/business/technology/tech-asia/chip-price-hikes-spread-as-asia-s-chipmakers-plan-record-136bn-spending">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>.

Chip price hikes spread as Asia's chipmakers plan record spending

Semiconductors

A surge in demand for data infrastructure during the <a href="/industry/ai">artificial intelligence</a> boom is pushing Shenzhen-based Xunce Technology into the spotlight.
Often described by analysts as China's equivalent to Palantir, the company said its revenue nearly doubled in 2025, surpassing earlier expectations and highlighting how the race around large language models is shifting toward a new battleground: data infrastructure.
Xunce released a profit forecast on March 6, projecting full-year 2025 revenue of about RMB 1.283 billion (USD 179.6 million), up 102.95% year-on-year. Adjusted net loss is expected to narrow to roughly RMB 55 million (USD 7.7 million), compared with RMB 82 million (USD 11.5 million) in 2024.
The company attributed the remaining losses primarily to a period of rapid expansion and sustained R&amp;D spending. It is also extending its AI infrastructure beyond its initial domains into emerging areas such as <a href="/industry/robotics">robotics</a> data platforms and commercial aviation.
Xunce listed on the Hong Kong Stock Exchange on December 30, 2025. It positioned itself as the first publicly traded company built around a data agent architecture designed for large AI models.
Financial momentum accelerated sharply in the second half of the year. According to the company's earlier prospectus, Xunce generated RMB 198 million (USD 27.7 million) in revenue during the first half of 2025. That implies more than RMB 1 billion (USD 140 million) in revenue in the second half alone, representing a sequential increase of about 448%.
In its earnings notice, the company said the revenue growth reflects rising demand for data capabilities as AI models move from experimentation to real-world deployment. With its AI data agent platform at the core, Xunce has built an end-to-end technology stack covering data acquisition, cleansing, standardization, real-time processing, and model optimization. The system is designed to process data with millisecond-level latency.
Leveraging that infrastructure, Xunce said its AI platforms and solutions are increasingly deployed across a wider range of industry scenarios, while existing customer partnerships deepen.
The same day it released the profit forecast, the company was also added to the Hong Kong Stock Connect program, effective March 9. Inclusion allows mainland Chinese investors to trade its shares through the cross-border channel, a development that often increases trading liquidity and investor visibility.
The move may also reflect growing confidence among capital market participants in Xunce's long-term prospects, while potentially supporting its valuation as access to cross-border investors expands.
<h3>Analysts draw parallels with Palantir</h3>
Over the past month, several domestic and international investment banks have initiated coverage of Xunce, broadly assigning “buy” or “overweight” ratings.
Deutsche Bank, for example, said the company's growth trajectory resembles the early strategy of Palantir. Rather than scaling through low-barrier applications, Xunce first commercialized its technology in sectors with complex data environments and high technical requirements.
Palantir began by working with military and government intelligence agencies before expanding into finance, healthcare, and manufacturing. Over time, it developed into one of the world's most prominent AI data platforms.
Xunce followed a similar path. It initially focused on the asset management industry, a sector known for highly complex datasets and strict requirements for accuracy and timeliness.
Successfully commercializing technology in such environments can create a durable competitive moat. The real-time data processing capabilities Xunce developed in asset management, including the ability to manage high concurrency, low latency, and strong data consistency, can transfer to other industries.
Deutsche Bank estimates that revenue from industries outside asset management could grow at a compound annual rate of 109% between 2024–2027. Telecommunications, urban governance, and manufacturing are expected to become key growth drivers.
The company's customer base has already expanded beyond asset management to include financial services, city management, manufacturing operations, and telecommunications. Clients include China's three state-owned telecommunications operators.
In 2024, industry application revenue from sectors outside asset management accounted for 61.3% of Xunce's total revenue, up from 34.1% in 2023 and 25.6% in 2022.
<h3>Modular architecture as a moat</h3>
Analysts at Guotai Haitong also highlighted the company's technological differentiation, particularly its modular product architecture.
The design gives Xunce's platform a high degree of flexibility. Individual modules can be combined to meet the needs of different industries or configured into customized solutions for specific clients.
According to the company's prospectus, Xunce had developed more than 300 modules as of June 30, 2025, spanning real-time data infrastructure and data analytics capabilities.
The number of modules increased from 152 at the end of 2022 to 318 at the end of 2024, and 332 by mid-2025.
The modular approach echoes Palantir's product strategy. Its core platforms, Foundry for commercial clients and Gotham for government users, are built around component-based architecture in which individual modules provide specific functions and can be assembled based on client requirements. Palantir's Apollo platform enables remote updates, centralized management, and compliant deployment of software across global customers operating in heterogeneous environments.
For Xunce, the growing module library could also increase revenue per user. Deutsche Bank estimates that average revenue per user could grow at a compound annual rate of 83% between 2024–2027 as clients adopt more modules and expand usage across deeper project deployments.
Taken together, analysts increasingly frame Xunce not as a traditional software company but as a foundational data infrastructure platform for the AI era. That perspective partly explains why Guotai Haitong assigned the company a target price of HKD 104.78 (USD 13.4), implying nearly 40% upside from its recent share price.
As competition around large AI models matures, the focus may gradually shift from algorithms to the data systems that power them. Companies capable of building those underlying rails may shape the next phase of the AI sector.
This <a href="https://xueqiu.com/2854806290/378525966">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.

China’s “Palantir equivalent” Xunce forecasts strong revenue growth amid AI data surge

Artificial Intelligence

AI Infrastructure

… global company. Under compliant conditions, it can lawfully collect and use local data wherever it operates.
Third, through world model-based simulation and generation, we can quickly reach a baseline capability for generalized scenarios.
Our global autonomous driving strategy combines strong model generalization, global deployment, and technological breakthroughs. It cannot rely solely on China data.
<h3>36Kr: If the foundation model empowers diverse agents, will there be bottlenecks in multimodal interaction or spatial perception?</h3>
LX: The underlying reuse capability should be strong. The VLA and foundation model are natively multimodal and not designed solely for autonomous driving. However, we are still exploring the extent of reuse. Our immediate focus is to fully deploy it in vehicles before advancing cockpit-driving integration further.
<h3>36Kr: Some argue human data is losing value. What's your view?</h3>
HX: The amount of data in the physical and human world is effectively infinite.
I used to think 100,000 or one million vehicles generating miles of data would be enough. Now I believe it's far from sufficient. Many assume that selling more cars automatically yields valuable data. That's incorrect. Collecting high-quality, valuable, large-scale data is extremely difficult, and that applies to cars and robots alike. We are far from solving that challenge.
<h3>36Kr: Is reinforcement learning a cure-all?</h3>
LX: Reinforcement learning is not a panacea. It requires a strong foundation model that can at least sample feasible solutions. Without that, reinforcement learning cannot improve performance.
However, it is highly efficient for targeted problem-solving and long-tail exploration. It is a powerful learning method, but not a universal solution.
<h3>36Kr: Why don't users perceive proportional improvements despite massive increases in computing power?</h3>
LX: It's not about headline numbers. The key is using computing power effectively. That's why we are transitioning from general-purpose processors to ASICs.
Look at <a href="/company/nvidia">Nvidia's</a> GPU and CUDA era. The issue is utilization, not simply scale. Large computing power also requires higher information density inputs and larger models. Otherwise, the compute sits idle. Simply increasing the numbers will not produce perceptible improvements for users.
<h3>36Kr Does the VLA approach directly output a trajectory, or generate multiple options for selection?</h3>
LX: The core question is whether you are building autonomous driving, or AI. We are building AI.
If you commit to that shift, you cannot carry over legacy heuristic rules. The key is scaling data, model size, and compute, and iterating rapidly. Over the past few years, AI development has shown that scaling and fast iteration can solve many problems.
<h3>36Kr: Is there a tradeoff among safety, scenario coverage, and efficiency?</h3>
LX: Anyone familiar with machine learning knows the PR curve. When performance plateaus, tradeoffs emerge among safety, efficiency, and coverage.
The main objective of autonomous driving is safety. But no one wants a system that is safe yet unbearably slow and inefficient. The solution is to improve fundamental capability. Only then can safety improve without sacrificing other dimensions.
What we mean by a “generational gap” is not just a single metric lead. It refers to shifting the entire approach and accelerating iteration itself. The goal is not only to move faster, but to continuously increase the pace of improvement by building a general underlying capability system. That is the real generational difference, not isolated metric gains.
KrASIA features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3707327485505672">article</a> was written by Xiao Man for 36Kr.

Xpeng reframes autonomous driving as AI deployment in the physical world

Xpeng Motors

Transportation

Autonomous Vehicles

Mobility

… before a stronger second half as the comparison base eases. They also pointed to renewed trade-in support as a constructive backdrop.
The risk is that this recovery thesis still depends on several developments occurring at once: steadier consumer demand, less aggressive competition in food delivery, and continued monetization of higher-margin advertising and services.
The cleanest way to read the quarter is that JD’s core retail business is stronger than the headline suggests, but the group is less profitable than that core would typically allow. Revenue diversification is progressing. Profit diversification has not yet followed. What to watch next is whether food delivery losses continue narrowing without another surge in subsidies, and whether retail margin gains remain intact as electronics demand recovers. That will determine whether 2025 marks an investment trough or the beginning of a longer period in which JD’s expansion plans continue to outpace its earnings.
Note: RMB figures are converted to USD at a rate of RMB 1 = USD 0.14 for reference, unless otherwise stated. Company disclosures may apply different exchange rates.

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