Hardware and workload assessment
Node model, GPU count, power draw, cooling requirement and growth plan documented before rack space is proposed.
Solution · GPU Colocation
Place your own GPU servers in an in-country facility — with power, cooling, network and physical controls designed around dense AI racks.
Solution · GPU Colocation
General-purpose colocation is priced around space. Dense GPU racks are constrained by power distribution, heat rejection, cabling and east-west network traffic long before floor space runs out. We start from the node profile and the workload, then confirm what the facility can actually support.
Colocation is not a rack rental. For GPU workloads it is a power, heat and network design problem. We assess the facility, define the rack envelope and stay accountable for the environment around your hardware.
Capabilities
The facility, rack and network work required before your hardware can run production workloads.
Node model, GPU count, power draw, cooling requirement and growth plan documented before rack space is proposed.
Rack elevation, power distribution, redundancy and cabling designed around the hardware you intend to install.
Air or liquid cooling options assessed against the node heat load and the facility’s actual capacity.
Private connectivity, management network and east-west fabric planned for training and inference traffic.
Access control, visitor handling, CCTV coverage and hardware chain-of-custody reviewed with the facility operator.
Optional on-site assistance, vendor case coordination and replacement logistics under an agreed support model.
Process
A gated path from hardware assessment to an operating colocation environment.
Review the hardware profile, workload, power draw and growth assumptions.
Match the requirement to an in-country facility with the right power, cooling and security envelope.
Produce the rack, power, cooling, cabling and network design, including failure domains.
Install, cable, power on and validate the environment against agreed acceptance criteria.
Your team runs the hardware, or Bijak Cloud provides remote hands and lifecycle operations.
Use cases
Patterns where owning the hardware matters, but owning the building does not.
Move an owned GPU fleet into an AI-ready facility without a hardware refresh.
Keep large training corpora and model artefacts close to the compute that uses them.
Retain hardware ownership and administrative control while using a professionally operated facility.
Colocate the sensitive tier and connect it privately to sovereign cloud capacity for burst work.
Controls
Controls that keep customer-owned hardware and data under Malaysian jurisdiction.
Hardware is installed in Malaysia; cross-border access or replication requires written authorisation.
You retain administrative control of the hardware, firmware, encryption keys and model artefacts.
Physical access and change activity are logged and available for your audit process.
Access, retention and deletion procedures are mapped to Akta 709 obligations.
FAQ
Solution · GPU Colocation
Share the node model, GPU count, power draw and target location. We will return a facility assessment and a rack-level design brief.
Quotes are itemised by configuration, term and support. No fixed list price is published.