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Following the rollout of AI Compute Service in Hong Kong (China), Thailand, Indonesia, and Singapore in 2025, Huawei Cloud MaaS (Model-as-a-Service) is now available, leveraging Huawei’s in-house acceleration engine to support mainstream models and provide customers with stable and high-quality token services.

Huawei Cloud continues to strengthen its collaboration with high-quality open-source models in the industry. Six models from three categories—GLM, DeepSeek, and Qwen—are the first to be supported by MaaS. These models are designed for two major application scenarios: intelligent Q&A and AI coding. They offer one-click access and out-of-the-box model hosting services, covering the entire lifecycle of model management from deployment to inference, fine-tuning, and evaluation. With elastic compute and pay-per-use billing, enterprises and developers can quickly integrate AI capabilities into their service systems without having to worry about the underlying infrastructure. This makes AI accessible to everyone.

Notably, this release includes support for the latest GLM-5 model. GLM-5 has attained state-of-the-art (SOTA) performance in coding and agent capabilities, making it an ideal general-purpose agent foundation for complex system engineering and long-text agent tasks in enterprise environments.

Huawei Cloud’s long-term strategic investment in AI has resulted in a comprehensive suite of AI solutions, including CloudMatrix AI Infra, MaaS, ModelArts (a model training and inference platform), CodeArts (a coding agent), AgentArts (an agent platform), and DataArts (a data agent).

CodeArts and AgentArts will be launched outside the Chinese mainland in the second half of 2026.

Huawei Cloud has established an optimized cloud infrastructure network in the Asia Pacific region. This network comprises five Regions and 18 availability zones (AZs) located in Singapore, Thailand, Hong Kong (China), Indonesia, and the Philippines, ensuring a 50 ms access latency. Additionally, in Malaysia, Huawei Cloud and partners have jointly built a local cloud.

Huawei Cloud AI Compute Service have helped many Asia Pacific customers elevate their cloud journey from simply migrating to the cloud to using AI well. They have benefited from improved productivity and better adaptation to changing environments.

iFLYTEK, a leading intelligent voice and AI company, selected Singapore as the first destination for its global expansion strategy in 2023, naturally extending its collaboration with Huawei Cloud from China to a global scale. Huawei Cloud AI Compute Service helped iFLYTEK quickly deploy their large language model training resources within two weeks. The training remained stable for 60 days without interruption, ensuring zero faults during the release of major versions.

In Vietnam, Green and Smart Mobility (GSM), an emerging green mobility platform, migrated its core operations platform to Huawei Cloud to reduce costs, enhance efficiency, and achieve multi-cloud flexibility. GSM has developed a comprehensive fleet management platform using AI and IoT. By utilizing Huawei Cloud IoTDA and ModelArts AI technologies, GSM analyzes violations and generates risk alerts to ensure driver and passenger safety, thereby fulfilling its mission of promoting green and safe transportation.

Huawei Cloud will continue to invest in AI innovation and provide a secure, stable, and intelligent cloud foundation to help enterprises in Asia Pacific achieve sustainable business growth in the AI era.



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About Huawei

Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We have 207,000 employees and we operate in more than 170 countries and regions, serving more than three billion people around the world.

Our vision and mission is to bring digital to every person, home and organisation for a fully connected, intelligent world. To this end, we will work towards ubiquitous connectivity and inclusive network access, laying the foundation for an intelligent world; providing diversified computing power where you need it, when you need it, to bring cloud and intelligence to all four corners of the earth; build digital platforms to help all industries and organisations become more agile, efficient, and dynamic; and redefine user experience with AI, making it smarter and more personalised for people in all aspects of their life, whether they’re at home, on the go, in the office, having fun, or working out. For more information, please visit Huawei online at www.huawei.com

Decoupling the Battery from the Price Tag

For decades, the battery has been the most expensive single component of an electric car. It is also the component most likely to depreciate. XEV’s innovative business model fundamentally alters this equation by separating the vehicle (hardware) from the battery (service).

Customers purchase the car but lease the energy capacity. This strategy significantly lowers the initial purchase price. It makes premium urban mobility accessible to a broader demographic. This ranges from young professionals seeking their first vehicle to fleet operators managing tight margins.

“We are not just manufacturing cars. We are redefining vehicle ownership,” says the XEV leadership team. “Our goal is to make car production as flexible as smartphone manufacturing. We give users exactly what they need for city living without the financial weight of traditional ownership.”

3 Minutes to Full Power: Solving the Charging Crisis

Range anxiety remains a critical hurdle for European EVs. This is particularly true for drivers without private home charging infrastructure. XEV addresses this with its proprietary battery swapping network.

The XEV YOYO and the upcoming XEV XPRESSION are engineered with a modular battery system. Instead of waiting hours at a charging point, drivers pull into a dedicated station. They complete a fully automated battery replacement in approximately three minutes.

This “SWAPPING” technology does more than save time. It improves operational efficiency for commercial users and ensures the vehicle is immune to battery degradation. Since the driver does not own the battery, they never have to worry about the cell’s lifespan affecting the car’s resale value. This creates a “Zero Usage Anxiety” experience for the owner.

Data-Driven Customization: The End of “One Size Fits All”

The XEV lineup is purpose-built for the narrow streets and high congestion of European cities. With a compact footprint of roughly 2.5 meters, the YOYO navigates historic city centers with ease. However, small size does not mean limited options.

Unlike legacy automakers that push stock inventory, XEV utilizes a data-driven C2M model. Users configure their vehicles via an online platform. They select distinct exterior colors, interior materials, wheel designs, and specific features. This user input triggers a flexible production process that creates a customizable car tailored to specific tastes. XEV uses the massive data generated from these customization choices to refine future designs and forecast market trends with precision.

Commercial Application: Powering the Last-Mile Economy

The flexibility of the XEV platform extends well beyond personal commuting. It is designed to serve the booming last-mile economy. The platform supports last-mile delivery vehicles and shared mobility fleets.

XEV provides specialized enclosed cargo options for logistics companies. The vehicle can even be customized for small business applications, such as mobile coffee carts or retail trucks. For small business owners, the vehicle serves as a mobile asset that can be configured for specific trades, effectively lowering the barrier to entry for entrepreneurs.

XEV has already initiated pilot projects with major European logistics firms to prove the model’s viability for high-frequency urban commuting and commercial delivery. For car-sharing services, the high utilization rates and low maintenance needs of the YOYO make it an ideal asset for time-based rental fleets. The modular design further supports this eco-friendly lifecycle by facilitating easy repair and part upgrades. This extends the product lifespan and reduces waste compared to traditional vehicles that are often scrapped when a single major system fails.

A Strategic Supply Chain for a New Era

XEV achieves this level of flexibility through a strategic manufacturing model. The company adopts a capital-light approach that relies on deep collaboration with mature Asian automotive supply chains. This ensures rigorous quality control and cost efficiency without the bloating of traditional manufacturing.

Simultaneously, XEV is committed to European localization. The company is currently establishing assembly hubs and battery swapping networks across Europe to better serve local demand. This dual approach allows XEV to combine global manufacturing power with local market responsiveness. It ensures that while the technology is global, the support and infrastructure are local.

Availability

Sales and deliveries of the XEV YOYO have commenced in selected European markets, including Italy and Germany. The company continues to expand its infrastructure to support the growing network of users who demand a smarter and cleaner way to move through their cities.

For more information on the YOYO and the battery-swapping network, visit https://www.xev-global.com/yoyo or explore the upcoming XPRESSION model at https://www.xev-global.com/xpression.
Hashtag: #XEV

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About XEV

XEV is an innovative electric vehicle company committed to transforming the way cars are designed, built, and owned. Through its direct-to-consumer (DTC) online customization platform and a flexible production system, XEV integrates personalized user demand with modular smart manufacturing. The company’s mission is to make electric vehicles accessible and lifestyle-aligned for everyone. It drives the transition toward sustainable and personalized mobility. XEV positions itself not just as a manufacturer but as a global leader in urban electric mobility solutions.

The company, which appears to have been incorporated in Singapore in March 2026 as SEOEXPERT PTE. LTD., is presenting itself as a performance-driven agency focused on SEO, paid advertising and social media marketing. Its public-facing claims centre on AI-assisted content publishing, competitor monitoring, campaign optimisation and lead qualification, alongside a “no long-term contracts” offer and a promise to be judged on outcomes rather than retainers alone. That message lands at a time when many smaller businesses are under pressure to justify every marketing dollar and are increasingly wary of vague promises around rankings and traffic.

The broader backdrop helps explain why such positioning may resonate. Singapore’s digital economy accounted for 18.6 per cent of gross domestic product in 2024, up from 14.9 per cent in 2019, according to the Infocomm Media Development Authority, while SME adoption of AI more than tripled in one year to 14.5 per cent in 2024. That expansion has widened the addressable market for agencies promising to help firms compete online, but it has also sharpened scrutiny of whether AI-branded services genuinely improve sales, lead quality and discoverability or merely repackage familiar tactics with new language.

SEOExpert is entering a field where established players already market many of the same ideas. Rival agencies in Singapore promote AI-assisted SEO, performance pricing, flexible contracts and proof-of-results case studies, while independent directories and agency marketplaces show a busy, fragmented sector serving everything from small retailers to larger regional brands. That means the newcomer is not inventing a category so much as trying to sharpen a proposition around trust, transparency and speed of execution. The challenge will be whether it can demonstrate that its systems produce durable gains rather than short bursts of visibility.

For SMEs, the appeal of a results-linked arrangement is obvious. Search marketing has long suffered from an information imbalance: agencies control the technical work, clients often lack the tools to assess quality, and outcomes can depend on shifting search algorithms, website health, content quality and competition in a given niche. In that environment, a promise that reduces fixed commitment can sound attractive, particularly for businesses that have previously paid monthly retainers without a clear link to revenue. Yet such offers also deserve careful reading. “Results” can mean rankings, clicks, leads or sales, and those metrics do not carry equal commercial value. A company can rise in search results without converting more customers.

The AI element also cuts both ways. Automation can help agencies monitor competitors, scale content operations and identify technical issues faster, which may lower delivery costs and shorten turnaround times. At the same time, search platforms and clients alike are becoming more alert to thin, repetitive or mechanically generated material. That raises the bar for agencies claiming proprietary tools. The real test is not whether software is involved, but whether the work improves relevance, authority and user experience in a way that survives algorithm changes and stricter expectations from search engines and AI-driven discovery platforms.

Another factor is credibility. Public records indicate the company is newly formed, which is not unusual for a startup agency but does mean prospective clients will have limited operating history to assess. Its website advertises more than 100 brands served and showcases commercial claims around measurable growth, though such statements are difficult to independently verify from public information alone. For buyers in Singapore’s SME segment, that typically shifts due diligence towards contract terms, reporting standards, client references, attribution methods and whether performance targets are clearly defined before money changes hands.

The early-April figures reinforce a broader pattern already visible through the first quarter. South Korea, one of the world’s most closely watched export economies because of its central role in memory chips, displays and consumer electronics, has been benefiting from a steep recovery in semiconductor sales after a prolonged industry downturn. Reuters reported at the end of February that the country’s chip exports had jumped 160.9 per cent in that month alone, passing $20 billion for a third straight month as AI investment and stronger memory prices lifted demand.

Semiconductors were again the main engine in the latest 10-day release. Chip exports surged 152 per cent from a year earlier, underscoring how heavily South Korea’s trade performance is now tied to data-centre investment, high-bandwidth memory demand and the wider AI build-out led by large technology firms. That strength has helped offset a less even backdrop in other parts of the economy, where investment, household demand and external policy risks remain more mixed.

The export rebound matters well beyond monthly trade headlines. South Korea’s central bank raised its 2026 growth forecast to 2.0 per cent in February and signalled that a chip-led upswing was giving policymakers more room to hold interest rates steady while watching inflation and financial stability risks. Reuters also reported this month that central bank officials see strong semiconductor exports and an extra budget as factors easing downward pressure on growth, even as won weakness and higher energy costs complicate the inflation outlook.

Factory data has pointed in the same direction. A Reuters report on S&P Global survey findings showed South Korea’s manufacturing activity expanded in January at the fastest pace in nearly a year and a half, helped by stronger export orders from China, North America and Europe. Manufacturers reported improving optimism as orders strengthened in sectors such as autos and semiconductors, indicating that the recovery is not only statistical but also visible in production and order books.

Still, the trade picture is not free of risk. South Korea remains highly exposed to swings in global demand, to US trade policy and to supply disruptions linked to tensions in the Middle East. Reuters polling before the March trade data showed imports rising sharply as higher oil prices pushed up the energy bill, even while exports surged on semiconductor strength. That combination can support headline trade values, but it also leaves the economy vulnerable to a renewed squeeze from commodity inflation and currency volatility.

Another uncertainty lies in concentration. The same chip boom that is lifting exports also raises dependence on a narrow cluster of products and companies. South Korea’s trade resilience is being powered largely by memory and advanced semiconductor demand, especially products linked to AI servers. Investment plans such as SK Hynix’s announcement in February of 21.6 trillion won in new facilities show confidence in long-term demand, but they also underline how central the semiconductor cycle has become to the country’s broader growth model.

For now, the momentum remains hard to ignore. Reuters polling ahead of the March data had already pointed to the fastest export growth in nearly five years, with shipments to the United States and China both showing strong gains alongside the semiconductor surge. Monday’s early-April figures suggest that pace has carried into the second quarter, strengthening the case that South Korea’s exporters are entering another period of outsized performance after a weak stretch in 2025.

That debate has sharpened after comments by Arun Subramaniyan, founder and chief executive of Articul8, who argued that India’s AI trajectory should not be framed as a choice between sovereign control and cultural depth, but as a need for both. His view comes at a time when the public and private sectors are moving from broad enthusiasm around generative AI to harder questions of ownership, trust, utility and scale.

The timing is notable. Under the IndiaAI Mission, the government has been expanding support for domestic compute, foundational models, datasets, skills and applications, while official messaging at the India AI Impact Summit in February cast sovereign AI as a strategic capability rather than a branding exercise. Government-backed efforts such as BharatGen have also been positioned as multilingual, multimodal systems designed around the country’s linguistic diversity and socio-cultural context. Together, those moves show that the argument for AI sovereignty in India is no longer limited to who owns the model or where the servers sit. It is increasingly about whether AI built for India can understand how people speak, work and make decisions across vastly different regions and sectors.

Subramaniyan’s intervention adds another layer to that discussion. He has suggested that sovereignty on its own can become too narrow if it is treated only as a matter of defence, infrastructure or control. In his framing, heritage matters because AI systems that ignore local language, history and context risk becoming technically impressive but socially shallow. That point has growing resonance as global concern rises over English-heavy training data, cultural blind spots and the danger that smaller languages may become underrepresented in the next generation of digital tools.

For India, the heritage argument carries practical as well as symbolic importance. A country with hundreds of languages, wide variations in literacy and deep differences in economic activity cannot rely on AI products optimised only for Western datasets or metropolitan users. Voice interfaces, translation layers, domain-specific copilots and public-service tools all perform better when they are trained on the speech patterns, terminology and workflows of the people expected to use them. This is why multilingual model development has moved from a niche research issue to a core policy concern.

At the same time, the enterprise case is becoming clearer. Many companies have discovered that generic large language models can help with drafting, summarising and coding, but struggle when deployed in regulated or mission-critical environments without access to internal knowledge. The more valuable opportunity lies in turning proprietary documents, engineering manuals, transaction records, legal archives and operational know-how into structured intelligence that can support decisions. That is the commercial logic behind domain-specific AI, and it helps explain why firms such as Articul8 are pitching secure, enterprise-grade systems built around private data rather than public internet corpora alone.

This shift also reflects a broader global pattern. Corporate surveys and advisory research have shown that many organisations remain stuck between pilot projects and real productivity gains, largely because governance, data quality and workflow integration have lagged behind excitement over model capabilities. In practice, companies tend to get stronger returns when AI is tied to specific functions and high-value use cases rather than treated as a general-purpose novelty. For banks, manufacturers, energy groups and healthcare providers, that often means models that can work inside tightly controlled environments and understand sector language with precision.

India’s opportunity may lie in combining these two strands. One is sovereign capability: domestic compute, public datasets, local model development and policy oversight. The other is heritage depth: linguistic coverage, cultural nuance and knowledge systems that reflect the country’s own realities. The third, emerging alongside them, is institutional depth inside enterprises, where AI can turn decades of accumulated expertise into a working asset instead of leaving it trapped in silos.

There are, however, risks in the current moment. A strong sovereign AI narrative can drift into protectionism or technological duplication if it becomes a race to mimic every frontier model at any cost. Heritage-focused rhetoric can also become vague if it is not matched by usable datasets, benchmark standards and transparent governance. Enterprises face a different danger: spending heavily on AI assistants that are poorly connected to business processes, weak on accuracy and difficult to audit.