AI COMPUTE
INFRASTRUCTURE.
Infrastructure for training, fine-tuning, inference
and large-scale AI workloads.
Built to integrate with your existing
compute orchestration platform.
Real infrastructure.
Connected thinking.
Compute for the
work that matters.
From model development to production workloads.
Engineering across the AI compute lifecycle.
01Model Fine-tuning
Adapt models to your data and domain.
Compute infrastructure for fine-tuning large language models and other AI models. Bring your models, datasets and training workflows to an environment shaped around your workload.
MODELS → DATA → ADAPTATION02AI Inference
Put trained models to work.
Accelerated compute for running model inference. Align infrastructure with your application’s workload characteristics and deployment requirements.
TRAINED MODELS → APPLICATION WORKLOADS03Deep Learning Computing
A foundation for demanding AI workloads.
GPU-accelerated infrastructure for deep learning training, experimentation and compute-intensive workloads, from development through to execution.
EXPERIMENTATION → TRAINING → EVALUATION04GPU Virtualization
Connect physical resources to workload needs.
A virtualization layer between GPU resources and AI workloads, enabling compute environments to be configured around the requirements of your applications.
GPU RESOURCES → COMPUTE ENVIRONMENTS05Workload Scheduling
Coordinate work across compute resources.
Workload scheduling that connects execution requirements with available accelerated compute, with integration into your existing compute orchestration platform.
ORCHESTRATION → SCHEDULING → EXECUTIONEvery layer.
Working together.
From the models you build to the compute they run on, each layer has a clear role.
Keep your orchestration environment. Connect it to the scheduling, virtualization and accelerated compute beneath it.
See how we integrate ↗Conceptual infrastructure architecture.
Integration scope is defined with your team.
Your platform.
Our infrastructure.
Build on the systems your team already uses.
Integration with your existing, on-premises compute orchestration platform.
Our approach starts with your environment and workload requirements. Integration scope is assessed against your platform interfaces and workload requirements, without requiring a move to a closed platform.
About LABUBUDE ↗- 01 / UNDERSTAND
Start with your environment.
Review your orchestration platform, AI workloads and compute requirements.
- 02 / CONNECT
Define the integration.
Agree the interfaces and responsibilities between your platform and our infrastructure layers.
- 03 / VALIDATE
Plan workload execution.
Align scheduling, GPU virtualization and compute resources with your deployment needs.
Compute infrastructure.
Deployed in Australia.
We deploy compute infrastructure in Australia for large language models and AI workloads.
Meet LABUBUDE ↗Engineering the foundation
for AI.
LABUBUDE PTY LTD is an AI infrastructure engineering company registered in New South Wales, Australia.
Our focus is the infrastructure behind AI: accelerated compute, GPU virtualization, workload scheduling and integration with customer orchestration platforms.
- LEGAL ENTITY
- LABUBUDE PTY LTD
- AUSTRALIAN COMPANY NUMBER
- 689 160 549
- REGISTERED IN
- New South Wales, Australia
Infrastructure.
Engineering. Integration.
Business enquiries
AI workloads, compute requirements and integration with existing orchestration platforms.