Central Global Technology · Kuala Lumpur
Model-as-a-Service, engineered for the region's next decade.
We build and operate AI compute infrastructure, electric-vehicle charging systems, and enterprise IT and cloud platforms — helping organisations across Southeast Asia put advanced technology into dependable daily operation.
Who We Are
A technology company with industrial roots and an infrastructure mindset.
Central Global Technology Sdn. Bhd. is the technology arm of Central Global Berhad, a group with a business heritage dating back to 1972. We apply the same discipline that built the group's manufacturing and construction businesses to a new generation of digital infrastructure: AI compute, electrified mobility, and enterprise technology operations.
What We Do
Four practices, one operating standard.
01AI Model-as-a-Service
A unified compute resource pool combining self-hosted open-source foundation models with brokered access to leading closed-source models — served through one governed API layer.
Explore 02EV Solutions
Charging infrastructure, smart energy management, and battery-related technology for vehicle manufacturers, fleet operators, and property developers.
Explore 03IT Services
Consulting, systems integration, and managed operations that keep enterprise technology estates reliable, secure, and cost-predictable.
Explore 04Cloud Services
Scalable and secure cloud architecture, migration, and ongoing platform operations aligned to each organisation's regulatory and performance needs.
ExploreStrategic Focus
AI MaaS is our principal line of business.
We operate a unified model-serving resource pool built on two complementary pillars: a self-built GPU compute pool hosting leading open-source models, and an aggregation gateway that brokers closed-source models as managed APIs. Customers consume both through a single, metered, enterprise-grade interface.
Connected Advantage
From charging networks to driving intelligence.
Our EV practice maintains working relationships with automotive manufacturers. Building on that foundation, we route the compute demands of assisted-driving development — model training, simulation, and data processing — into our own MaaS resource pool.
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