AI infrastructure · Malaysia
GPU capacity you can point at on a map.
Falcon Compute runs AI workloads on infrastructure we operate ourselves — in Malaysian datacenters, with real power, real cooling and a team you can call. Not resold capacity in someone else’s region.
What we do
Four ways to put our infrastructure to work.
From a single reserved GPU to a private cage with your own hardware in it — with the managed layer on top if you’d rather not run it yourself.
GPU compute
Reserved and on-demand accelerated capacity for training, fine-tuning and inference, provisioned in-country.
- Dedicated nodes, not shared slices
- Monthly and committed-term pricing
- High-speed interconnect between nodes
- Direct access — no queue for someone else’s quota
Private LLM hosting
Run open-weight models on hardware nobody else touches, with data that never leaves the country.
- Open-weight models deployed and tuned for you
- OpenAI-compatible API endpoints
- No training on your data, ever
- Built for PDPA and sector data-residency rules
Colocation
Bring your own GPUs into cold-aisle-contained racks built for the power and heat that AI hardware actually produces.
- High-density racks, contained aisles
- Redundant power distribution
- Remote hands and escorted access
- Carrier options and cross-connects
Managed AI infrastructure
The layer most teams underestimate: cluster provisioning, drivers, orchestration, monitoring and the 3am pager.
- Cluster build-out and scheduler setup
- Driver, CUDA and framework lifecycle
- Utilisation and cost reporting
- Local-hours support, local escalation
Infrastructure
Most AI hosting is a reseller agreement. Ours is an operation.
Falcon Compute deploys and runs its own hardware in carrier-neutral datacenters in Malaysia. Which site your workload lands in depends on what it actually needs — power density, network, and where your data has to sit — and we tell you that before you sign, not after.
That matters for AI hardware specifically. Accelerated compute doesn’t fail gracefully when a hall was designed for 3 kW racks and is asked to carry ten times that. We deploy into space built for the density, and we’ll walk you through the power and thermal envelope for your configuration before you commit to anything.
We’re currently qualifying deployments for next-generation accelerators, including NVIDIA Blackwell-class hardware.
Vendor ecosystem
Built on hardware and networks you already trust.
Why Falcon
Between a hyperscaler and a reseller, there’s a gap. We’re in it.
Most Malaysian teams choosing AI infrastructure end up picking between two bad fits. Here’s the honest comparison.
Global hyperscaler
- Capacity in another jurisdiction, with the data-residency questions that follow
- GPU quota you queue for, on someone else’s schedule
- Egress and cross-region charges that surprise you at month end
- Support through a portal, in a timezone that isn’t yours
- No possibility of seeing the hardware
Falcon Compute
- Capacity in Malaysia, on infrastructure we operate — and you can come and see it
- Dedicated hardware, allocated when we say it is
- Pricing you can model before you sign
- Named engineers, local hours, local escalation
- Colocation if you’d rather own the hardware outright
GPU reseller
- Rents the same capacity you could rent, with a margin on top
- No control over the facility or its power envelope
- Support is a ticket forwarded upstream
- Nothing to visit, nothing to audit
- Disappears when their supplier reprices
Getting started
Three conversations, not a procurement cycle.
Tell us the workload
Model sizes, training or inference, concurrency, and where the data has to live. Fifteen minutes on a call is usually enough to size it.
We size and quote
A written configuration with the power and thermal envelope, the hardware, the term options, and what it costs. No obligation to proceed.
Provision and hand over
We build the cluster, run acceptance tests with you, and hand over access — or keep running it, if that’s the arrangement.
Tell us what you’re trying to run.
Whether that’s a fine-tuning job next month or a cage of your own hardware next quarter — start with the workload and we’ll tell you honestly whether we’re the right fit.