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The assessment evaluated multiple leading AI computing resource management platform providers in China and noted Phancy’s industry-leading technological maturity across heterogeneous accelerator compatibility and adaptation, large-scale cluster operations, and delivery in hybrid cloud environments. Drawing on its accumulated capabilities in heterogeneous computing resource management, fine-grained GPU virtualization and agent-oriented computing services, Phancy received full scores and outperformed the industry benchmark in four out of six evaluated dimensions[1].

According to the IDC report, as AI moves into large-scale deployment, the growing adoption of AI agents is reshaping cloud infrastructure. In the meantime, AI infrastructure is evolving beyond basic computing capacity to become a core part of the enterprise technology stack, supporting digital and intelligent transformation.

Dr. Dai Wenyuan, Founder and Chief Executive Officer of Phancy, said: “The AI industry is moving beyond the ‘model race’ and entering a new phase of large-scale deployment. For enterprises, the real challenge is no longer whether they can access large language models, but about how to translate agentic AI capabilities into sustained productivity while keeping costs under control and operations stable. IDC’s assessment reflects the growing importance of unified management, flexible scheduling and fine-grained operations for heterogeneous computing resources. Phancy will continue to advance its capabilities in heterogeneous computing resource scheduling and agent infrastructure, helping more enterprises unlock the value of AI with greater efficiency, cost-effectiveness and reliability.”

Five Core Capabilities Behind Phancy’s Vendor-Neutral Unified Management Platform

At the core of Phancy’s offering is vendor-neutral unified management software that supports large-scale training and high-concurrency inference for mainstream models across chips from over ten leading vendors[2]. Its core technological capabilities include:

• Code-compatible multi-chip virtualization: Phancy supports the partitioning of a single AI accelerator across multiple workloads, enabling mainstream frameworks and inference engines, including PyTorch, TensorFlow, vLLM and SGLang, to run without changes to application code. Resource quotas help maintain stability when multiple workloads run concurrently.
• Three-tier resource pools and intelligent workload scheduling: Phancy’s platform provides three types of resource pools: dedicated, shared and overcommitted pool. Resources can be intelligently scheduled based on four dimensions (workload priority, hardware topology, real-time load and resource requirements), enabling large-scale training and high-concurrency inference workloads to run on the same infrastructure.
• AI gateway and dual-track metering: The AI gateway provides unified management of model routing, API calls and audit activities. Usage is measured through both accelerator hours and token consumption, helping enterprises track costs and resource utilization from the perspectives of both resource consumption and model usage.
• Agent-oriented computing services: Phancy’s platform turns heterogeneous computing resources into standardized services that AI agents can call on demand. These services support partitioning, reuse and elastic scaling. Combined with intelligent routing through the AI gateway, this accommodates the frequent calls and fluctuating workloads associated with AI agents, while token quotas and circuit-breaking mechanisms also help enterprises manage usage risks and costs when predefined limits are exceeded.
• Operations and maintenance for heterogeneous computing resources: Phancy’s platform provides end-to-end observability spanning nodes, accelerators, workloads and model services. It supports fault isolation, workload rescheduling and private deployment in environments without public internet access, helping enterprises improve operational efficiency across complex heterogeneous computing environments.

The report highlighted a use case in which a Chinese policy bank significant improved resource utilization by using Phancy’s three-tier resource pool architecture to manage computing resources across three data centers in two locations, while also enabling a smooth business migration.

Looking ahead, Phancy will continue to advance its AI computing resource management platform as AI infrastructure shifts from traditional “cloud + AI” architectures toward greater cloud-native, agent-oriented integration. The Group will continue to help enterprises manage computing resources more efficiently, deploy AI across a wider range of production environments, and turn AI into sustainable business productivity at scale.

Hashtag: #Phancy

The issuer is solely responsible for the content of this announcement.

About Phancy Group

Phancy Group (6682.HK) is a leading full-stack AI cloud services platform, providing comprehensive solutions for the AI 2.0 era. Our offerings include SageAIOS, HAMi vGPU and ModelHub XC, delivering efficient and scalable AI infrastructure with end-to-end capabilities. We provide a complete solution from heterogeneous compute resource management and optimization to the deployment of intelligent agent models. These solutions empower digital transformation across a wide range of industries, supporting our vision of building a large-scale and efficient “Token Factory.”

Guided by the mission of “AI for Everyone” and positioned as the “Navigator of AI,” Phancy Group is committed to becoming a global leader in Artificial General Intelligence.

The Asian Technology Excellence Awards recognise groundbreaking technological projects and innovations across Asia. Presented by Asian Business Review, the programme selects one winner per technology category and industry in each market, with entries judged on uniqueness and innovation, effectiveness and impact, and dynamism.

For ANGEL, the KFC Indonesia project demonstrates a capability that matters across the food and beverage sector. The company begins with on-site water quality testing and assessment, then designs the configuration around actual inlet conditions. That approach is backed by a commercial portfolio that includes microfiltration and UV sterilization, and by local delivery and service teams. It is this combination—not a standard product alone—that allows ANGEL to serve restaurant chains operating across diverse markets.

Sustainability is built into that model in practical ways. ANGEL integrates with existing pre-filtration systems, reducing the need for equipment replacement, water supply modifications and installation waste. Treatment is selected according to actual water quality, so sites receive the configuration they need. The modular design also limits maintenance complexity and supports long-term operating efficiency. For KFC Indonesia, this meant upgrading water quality without interrupting daily operations, while keeping existing infrastructure in service.

The deployment itself follows the same logic. Restaurants with more complex water conditions receive the C11 Microfiltration System together with UV sterilization, while sites with relatively stable inlet water can use UV sterilization alone. This scenario-based approach helps KFC Indonesia maintain consistent water quality across different cities and islands, and reflects how ANGEL works with food and beverage customers more broadly.

Accepting the award, ANGEL’s Assistant Vice President Annie Guo said, “This award recognizes the work of our teams and local partners in turning technology into practical value for customers. It reinforces our approach to international growth: understand local needs, deliver the right solution, and support it properly over time. For ANGEL, the responsibility continues after installation.”

The KFC project reflects ANGEL’s broader commercial strategy. For its global food and beverage business, the project shows that water purification can move beyond a functional utility to become a strategic asset for operators. ANGEL has built a commercial portfolio spanning microfiltration, ultrafiltration, and reverse osmosis, enabling tailored solutions for local conditions and customer needs. In markets where complex water conditions could otherwise constrain expansion, these capabilities support safer operations, greater resource efficiency, and more sustainable growth.

Hashtag: #ANGELGroup

The issuer is solely responsible for the content of this announcement.

About ANGEL

Founded in 1987, ANGEL has become a global leader in water purification. For nearly four decades, the company has dedicated itself to improving drinking water quality through innovation, delivering safe, healthy, and stylish water solutions. ANGEL has earned 11 internationally recognized certifications, including NSF, UL, TUV, SGS, CSA, and HALAL, ensuring compliance with high standards of quality, safety, and environmental responsibility.

The company said an initial fleet of all-electric Jaguar I-PACE vehicles will arrive in Singapore over the coming months, with preparations beginning before a phased testing programme in 2027. Trained autonomous specialists will initially drive the vehicles manually while Waymo maps roads and adapts its self-driving system to local conditions.

The programme will expose the Waymo Driver to Singapore’s road geometry, dense traffic environment and monsoon weather patterns before the company seeks to move towards autonomous operation. Commercial rides are scheduled to be offered through the Waymo app in 2028, subject to regulatory approvals.

Initial operations are expected to focus on western Singapore, including the Labrador and HarbourFront area, before any broader passenger rollout is considered locally.

Singapore’s Land Transport Authority said Waymo would become the country’s newest autonomous vehicle operator, joining ComfortDelGro and Grab. The authority said it would work closely with the company to ensure deployments meet safety and regulatory requirements and help build public confidence in autonomous vehicles.

Waymo is entering a market where autonomous transport is already moving from trials towards limited passenger services. Public rides on autonomous shuttle services began in Punggol in April, while operators including Grab, WeRide, ComfortDelGro and Pony. ai are expanding deployments and testing additional routes.

Waymo’s arrival therefore adds a major US developer to a field that already includes regional and China-based autonomous driving companies. Singapore has sought to attract multiple operators as it develops a competitive autonomous mobility sector and evaluates how driverless vehicles could supplement existing public transport.

Transport Minister Jeffrey Siow said Waymo would bring technology and operational expertise while supporting Singapore’s goal of creating additional transport options. Authorities have also stressed that autonomous vehicle deployment will not be allowed to move faster than measures to retrain and support drivers whose jobs could be affected.

The government announced a manpower transition package in July aimed at helping drivers acquire new skills and, where appropriate, move into jobs created by the autonomous vehicle sector. The issue has become more prominent as testing expands from controlled trials towards services carrying members of the public.

Singapore’s regulatory framework requires autonomous vehicles to clear technical and operational assessments before carrying passengers and progressing towards driverless operation. The Land Transport Authority assesses performance on authorised routes, including whether vehicles can cover sufficient distance without intervention and handle a range of traffic situations within their approved operating areas.

The Ministry of Transport also opened a public consultation this year on a broader legislative framework covering autonomous vehicles, including responsibility, licensing, insurance, liability and enforcement. Existing rules already require authorisation for autonomous vehicle trials and use on public roads.

Waymo said its Singapore expansion would follow the phased approach it has used elsewhere. The company has completed more than 20 million fully autonomous passenger rides and more than 300 million autonomous kilometres, according to company figures, giving it one of the largest operating datasets among commercial robotaxi developers.

Its overseas push is gathering pace. Waymo is preparing for commercial autonomous services in Tokyo and has also announced plans involving London and Munich, as it seeks to extend technology developed largely on US roads to markets with different driving environments, regulations and weather conditions.

Singapore offers a compact but demanding testing ground. Heavy rainfall, complex urban traffic, motorcycles, cyclists and dense interactions around public transport infrastructure create operating conditions that differ from many of Waymo’s established US service areas.

The company says its vehicles use lidar, radar and cameras to maintain a 360-degree view of their surroundings. The Singapore fleet will initially use Jaguar I-PACE sport utility vehicles, although Waymo has not disclosed how many vehicles will be deployed at launch or the eventual size of its commercial fleet.

Bae said South Korea was still trying to close the gap with leading AI powers while creating new markets, making its position different from countries or companies at the technological frontier. “We cannot afford to slow down AI right now,” he wrote on social media, describing the government’s approach as one of “speed responsibility” rather than speed control.

His remarks place Seoul firmly on the acceleration side of a widening debate over whether developers should moderate the pace of capable AI systems. Anthropic chief executive Dario Amodei has called for a slowdown in frontier model development to allow more time for safety work, while OpenAI chief executive Sam Altman and other technology leaders have voiced support for stronger precautions as capabilities advance.

Bae said South Korea should continue expanding research, industrial adoption and home-grown model development while strengthening protections against deepfakes, cyber threats and privacy violations. Faster progress, he said, required safety and trust measures to move at the same pace rather than follow after deployment.

The minister pointed to a broader technology agenda that includes sovereign foundation models, systems capable of processing vision and language, and models able to interact with physical environments. He said the country also needed to prepare for AI becoming deeply embedded across industries and everyday life.

The government has made domestic foundation-model development a central part of its ambition to place South Korea among the world’s top three AI powers. The Ministry of Science and ICT has been running a sovereign AI foundation model programme intended to improve domestic capabilities and reduce dependence on foreign technology.

Three teams led by Upstage, SK Telecom and LG AI Research advanced after the programme’s second-stage evaluation this year. The ministry has said models developed under the initiative were built with comparatively limited resources but were released as open source as part of an effort to expand the domestic AI ecosystem.

Bae indicated that further details on the next phase of the foundation-model programme would be announced after ongoing reviews. His comments also referenced government work on security-focused AI models and frontier systems, alongside an “AI for All” initiative intended to spread adoption across the economy.

The policy push is being developed alongside South Korea’s AI Basic Act, which establishes rules covering both the development of artificial intelligence and the creation of a framework for trust. The law’s stated purpose includes protecting rights and human dignity while supporting quality of life and national competitiveness.

That legal structure gives Seoul a basis for pursuing faster adoption without presenting safety as a separate objective. Bae said competitiveness and sustainability were linked, arguing that development speed and safeguards should advance together.

The global dispute has intensified as leading executives and policymakers weigh the economic benefits of faster AI deployment against concerns over misuse and loss of control. Amodei has proposed independent safety evaluators, coordination among major laboratories and greater international cooperation, while Nvidia chief executive Jensen Huang has argued against slowing technological progress and favours advancing safety alongside innovation.

European Commission President Ursula von der Leyen on Wednesday backed calls for greater caution and said frontier AI laboratories would be invited for talks on managing risks. Meta chief executive Mark Zuckerberg, by contrast, said AI companies already had strong incentives to build systems safely and did not require an industry-wide slowdown.

Bae’s intervention highlights the competitive pressures facing countries outside the United States and China, where most frontier AI investment and model development remains concentrated. South Korea has strong semiconductor and technology industries, but its government has acknowledged the need to strengthen domestic models, computing capacity and commercial adoption to narrow the gap.

Rahul Chari, PhonePe’s founder and chief product and technology officer, said the company is concentrating on AI deployments that produce measurable gains in operating, product or revenue metrics rather than adding the technology indiscriminately across its platform.

Chari told the Global Fintech Fest in Mumbai that the company’s approach starts with identifying operational bottlenecks where artificial intelligence can change outcomes. “Not everything that is an experience today gets genuinely better using AI,” he said. The emphasis, he added, is on a baseline shift in performance rather than the number of AI-labelled features. That approach is shaping investment across customer interactions, back-office workflows and engineering, while preserving conventional systems where automation offers little advantage.

The fintech processes close to 12 billion transactions a month and operates customer support with roughly 500 agents. Automation has increased the share of support cases handled without human intervention from about 90 per cent to 94 per cent, and PhonePe is targeting 96 per cent.

Chari said the remaining cases are harder because they often involve unusual circumstances, scattered information and the need for rapid responses. Large language models are being used to address those complex interactions, while human staff remain focused on cases that require judgement or escalation.

Fraud investigation is another area where automation has advanced. About 80 per cent of investigations can now be handled through automated systems, allowing specialist teams to concentrate on complicated incidents and new fraud patterns, according to the company’s account of its AI programme.

PhonePe is also extending artificial intelligence into consumer-facing services. It has been developing natural-language search that allows users to navigate the app, initiate tasks and reach relevant services using voice or text commands. The company is exploring broader conversational capabilities for personal finance, insurance and investment products.

Its search system, launched earlier this year using Microsoft Foundry, can interpret requests such as making a payment, recharging a FASTag or locating transaction information. PhonePe has said the interface is designed to reduce dependence on conventional menu navigation by directing users according to their stated intent.

Merchant products are another focus. PhonePe launched an AI-powered integration layer in May aimed at helping online businesses connect to its payment gateway through conversational instructions, reducing a process that can otherwise require developers to work through documentation and technical configuration.

The company followed in June with SmartPages, an AI-powered payment-page creator embedded in its payment gateway dashboard. Merchants can describe what they are selling in ordinary language, including vernacular languages, and the system generates product copy, selects relevant customer information fields and structures a mobile-oriented payment page.

PhonePe is considering further agentic functions for its business app, including answering merchant and customer queries and helping businesses create and distribute offers or coupons. The company has also examined tools that could connect commerce activity with services such as WhatsApp and Instagram.

Artificial intelligence is being incorporated throughout PhonePe’s software development process, including solution design, coding, code reviews, testing, deployment, troubleshooting and debugging. Internal tools include TraceMine for crash analysis, Lens for initial root-cause analysis using logs and deployment data, and KadAI for code orchestration and agent-based development.

Corporate functions are being brought into the same framework through an internal Agent Hub designed to let non-technology teams automate workflows. Legal, compliance, finance and human resources teams are among those using the platform.

PhonePe says the system was built for a regulated financial-services environment, with controls covering data access, leakage and localisation. Its architecture includes an in-house large language model router, open-source models hosted on company premises, and internal data and tools.

One target is the company’s new-product introduction process, where reviews involving compliance, privacy, legal, trust and safety can take about 30 days. PhonePe is exploring whether AI-enabled workflows can compress that process to less than a day.

The BG-5 Golden Dragon Fish was demonstrated at the 2026 China International Fair for Trade in Services, held at Shougang Park from September 9 to 13. Developed by Boyagongdao Marine Technology Group, the robot is designed to resemble a golden arowana and propel itself through water with a flexible, multi-joint tail rather than a conventional propeller.

The machine can detect obstacles and adjust its route autonomously instead of following only a fixed, pre-programmed path, according to information released by the developer and statements made at the exhibition. Its fish-like movement is intended to improve manoeuvrability while giving the platform a less conspicuous profile than many conventional underwater vehicles.

Boyagongdao lists the BG-5 as a 640-millimetre-long robot weighing about 3 kilograms. The published specifications give it a maximum operating depth of 5 metres and a top speed of 0.6 metres per second. The company says infrared recognition supports autonomous obstacle avoidance, while wireless communications allow online debugging and control.

The manufacturer also offers a BG-5V configuration that combines the robotic fish with a software platform for more advanced experiments. The listed capabilities include global and local path planning, task allocation, formation control, cooperative transport and coordinated operations involving multiple robots.

Those functions broaden the possible uses beyond a single demonstration unit. Groups of small robotic fish could, in principle, divide an underwater area for inspection or monitoring, maintain formations and coordinate tasks in locations where larger vehicles would be harder to deploy. The company presents the platform for research and teaching as well as operational fields including search and salvage, hydropower, safety and rescue and national defence.

Claims that the robot has been formally deployed as an underwater surveillance system have not been substantiated by publicly available official information. The specifications and the developer’s stated defence-related work show that reconnaissance or monitoring applications are technically plausible, but the model displayed at CIFTIS was presented as a biomimetic robotic platform rather than as an announced military deployment.

Boyagongdao says its bionic robot series draws on more than a decade of research associated with Peking University’s College of Engineering. The systems use high-speed biomimetic drive mechanisms and central pattern generator control algorithms intended to reproduce the smooth, rhythmic movement of aquatic animals.

The company has also disclosed work on defence-oriented underwater technology. Its website says technologies developed for military-related directions have been adapted for higher education products, and company material from earlier exhibitions describes unmanned and intelligent underwater equipment as an area of military development. It has separately publicised the ROBO-SHARK, a larger shark-inspired underwater robot developed with a military unit.

The BG-5 itself is not a newly created model. Boyagongdao had displayed the robotic fish before this month’s services trade fair and promoted it earlier this year at Beijing technology events. The latest CIFTIS appearance nevertheless drew renewed attention because of the machine’s autonomous obstacle avoidance and increasingly realistic biomimetic movement.

China’s work on underwater robotics extends well beyond fish-shaped machines. Universities, research institutes and commercial groups are developing autonomous systems for coral monitoring, infrastructure inspection, marine ranching, emergency rescue and deep-sea research. Some platforms are designed to carry cameras, sonar or environmental sensors, while others use robotic arms for intervention tasks.

A separate ecological-monitoring deployment in Hangzhou has used biomimetic robotic fish to patrol West Lake, measuring indicators including water temperature and pH, detecting invasive species and transmitting data to monitoring centres. Other Chinese underwater robots have been used for reef observation and for identifying and removing crown-of-thorns starfish.

The BG-5 demonstration at CIFTIS focused on embodied intelligence underwater, where navigation software, sensing and propulsion are integrated into a machine that moves more like a living animal than a standard remotely operated vehicle.