Aolani and NVIDIA Expand Southeast Asia AI Infrastructure
Singapore-founded AI cloud provider Aolani has signed a strategic compute collaboration with NVIDIA to expand AI infrastructure across Southeast Asia. The agreement will support new AI factories in Malaysia and the Philippines.
Under the plan, Aolani expects to deploy 22,000 NVIDIA Blackwell Ultra GPUs across the two facilities in early 2027. As a result, its total planned GPU deployment will exceed 48,000 units. The expansion will also take Aolani’s AI factory capacity above 100 megawatts.
Aolani has worked as an NVIDIA Cloud Partner since 2023. Through the latest collaboration, it will provide NVIDIA-powered cloud services to AI companies, enterprises, startups, developers, and institutions across Southeast Asia.
Malaysia and Philippines Lead Expansion
The planned facilities will extend Aolani’s regional infrastructure footprint. Malaysia already has a growing concentration of AI and data centre projects. Meanwhile, the Philippines is emerging as another market for large-scale AI infrastructure.
Aolani expects its Philippine deployment to become one of the country’s first large-scale AI infrastructure platforms. However, the company has not disclosed the exact facility locations or the GPU allocation between Malaysia and the Philippines.
The new infrastructure will support AI training, fine-tuning, inference, and production workloads. In addition, Aolani’s existing platform provides dedicated NVIDIA GPU clusters for customers that need high-performance computing.
The companies will also use a revenue-sharing and credit-support model. This allows infrastructure deployment to align more closely with customer demand while supporting Aolani’s expansion plans. The companies have not disclosed the financial terms or revenue-sharing ratio.
NVIDIA Blackwell Ultra Supports AI Workloads
Aolani plans to deploy NVIDIA Blackwell Ultra systems across the new facilities. These systems target advanced AI workloads that require substantial computing capacity.
Furthermore, Aolani describes its infrastructure as purpose-built for AI workloads across Asia. Its services include GPU cloud capacity, managed inference endpoints, fine-tuning environments, and dedicated AI clusters.
The expansion comes as Southeast Asia attracts greater investment in AI-ready data centres and cloud infrastructure. According to figures cited by Aolani from the Singapore Economic Development Board, global hyperscalers have invested more than $50 billion in AI-ready infrastructure across the region.
However, building AI factories at this scale requires more than GPUs. Power availability, data centre construction, financing, connectivity, and customer demand will all affect the rollout. The planned early-2027 deployment therefore depends on those infrastructure and commercial requirements.
Aolani Targets Wider Regional AI Access
The collaboration also reflects a broader push to expand access to accelerated computing within Southeast Asia. Aolani says its cloud services will support AI-native companies, enterprises, startups, developers, and institutions.
Meanwhile, the company is positioning regional infrastructure around data sovereignty and compliance. Its platform provides GPU capacity closer to customers and supports dedicated infrastructure for workloads requiring greater control.
Aolani CEO Nicholas Chia described the NVIDIA collaboration as a major step in the company’s effort to expand AI computing across the region. He also said Southeast Asia is becoming an important location for the next phase of global AI infrastructure development.
For NVIDIA, the agreement expands its AI infrastructure presence through another regional cloud partner. For Aolani, the deployment will significantly increase available computing capacity. If the planned rollout proceeds in early 2027, the company will operate a network exceeding 48,000 GPUs and 100MW of AI factory capacity.
The companies have not disclosed the total investment value, customer commitments, or detailed construction schedule. Therefore, the final scale and commercial impact will depend on deployment progress and demand for AI computing services across Southeast Asia.
