Government & Public Sector
Data sovereignty, ISM controls evidenced through IRAP assessment, and citizen service infrastructure that stays up on the day everyone needs it at once.
Primary constraint — jurisdiction and assurance
Sovereign AI · HPC · Ultra-Low Latency
Enterprise Cloud & High Performance Computing Built for the Frontier.
We design, build and operate the compute layer beneath the hardest problems in Australia — sovereign AI factories, petascale HPC clusters, nanosecond-tuned trading systems and multi-petabyte data platforms. On-premise, hybrid or sovereign cloud. We design around the constraint your own measurement exposes first — power, memory bandwidth, the storage path or the queue — not the product catalogue. Benchmarked before you commit, monitored every second after.
Ecosystem & Accreditation
Silicon, cloud and accelerator partners across the stack
NVIDIA
AMD
Intel
Supermicro
DDN
WEKA
VAST Data
NetApp
Arista
AWS
Azure
Google Cloud
Sovereign by design
IRAP assessed to PROTECTED
ISO/IEC 27001
Defence Industry Security Program
Australian owned and operated
Solutions
Seven practices. One engineering team.
We do not resell reference architectures. Every engagement starts with your workload on our bench — profiled, bottlenecked and costed — before a single component is quoted.
AI & AI Factories
Purpose-built AI infrastructure that keeps your weights, your prompts and your customer data inside your own perimeter. We deploy on-premise and hybrid LLM estates, govern them to sovereign standards, and tune the token pipeline until the economics work.
- Enterprise AI infrastructure sizing, from single-node to multi-rack GPU fabric
- On-premise and hybrid LLM deployment with private inference endpoints
- Sovereign AI data governance, lineage and retention controls
- Token pipeline optimisation — batching, quantisation, KV-cache and routing
10×Model training acceleration versus prior estate
41%Lower cost per million tokens after pipeline tuning
100%Inference retained in-country, no data egress
Architecture diagram — AI factory reference topology
High Performance Computing
Clusters built for the science, not the spec sheet. We design scalable compute estates, orchestrate competing R&D workloads fairly, and tune interconnect and scheduler until your simulations finish inside the research window rather than after it.
- Scalable compute clusters, CPU and GPU, air- or liquid-cooled
- R&D workload orchestration with fair-share scheduling and quotas
- Advanced simulation — CFD, FEA, molecular dynamics, climate
- High-throughput parallel computing and MPI topology tuning
8.4 PFPeak aggregate across deployed clusters
92%Sustained cluster utilisation after scheduler tuning
3.1×Faster time-to-result on reference simulation suites
Architecture diagram — HPC cluster and interconnect fabric
Data Management & Storage
Compute is only as fast as the data reaching it. We build ultra-low-latency storage architectures, high-IOPS tiers that keep accelerators fed, and hybrid pipelines that move multiple petabytes without stalling the science or the trading day.
- Ultra-low-latency architectures with NVMe-oF and RDMA data paths
- High-IOPS parallel file systems sized to accelerator demand
- Scalable multi-petabyte hybrid pipelines with policy-driven tiering
- Sovereign backup, immutability and ransomware-resilient retention
140 PBUnder management across client estates
68%Reduction in p99 read latency after redesign
1.2 TB/sSustained aggregate throughput, largest deployment
Architecture diagram — tiered data pipeline
High-Frequency Trading Systems
In this domain the requirement is not "fast" — it is a deterministic number, measured and defended. We build mission-critical custom architectures, strip jitter out of the whole path, and prove the result with hardware timestamping rather than assertions.
- Ultra-low-latency design: kernel bypass, NIC tuning, cache-aware layout
- Mission-critical custom architectures, FPGA and host co-design
- Performance-tuned infrastructure with jitter and outlier analysis
- Colocation, cross-connect and precision time sync (PTP) engineering
<900 nsMedian tick-to-trade, tuned reference build
74%Reduction in p99.9 jitter after path rework
±50 nsTime sync accuracy against grandmaster clock
Architecture diagram — tick-to-trade signal path
Quantum Computing
Useful quantum advantage is not here yet, and we will not pretend otherwise. What we build is the classical scaffolding around it: hybrid quantum-classical frameworks and exploratory environments so your team is fluent and your pipeline is ready when the hardware arrives.
- Hybrid quantum-classical computing frameworks and orchestration
- Exploratory development environments with simulator back-ends
- Access integration to third-party QPUs via cloud brokers
- Post-quantum cryptography readiness assessment for existing estates
36 qubitState-vector simulation capacity on deployed nodes
4QPU back-ends reachable from one orchestration layer
2026Target for PQC migration readiness reviews
Architecture diagram — hybrid quantum-classical workflow
Servers & Workstations
Specified for the workload, built in-country, burned in before it ships. GPU-dense racks for training and rendering, and data science workstations that let researchers iterate at their desk instead of queuing for the cluster.
- Specialised compute built to workload profile, not catalogue tiers
- GPU-dense server racks with power and thermal modelling
- AI/ML and data science workstations, validated driver stacks
- Burn-in, benchmark reporting and on-site commissioning
72 hMinimum burn-in before any system ships
132 kWHighest per-rack density deployed to date
3 yrIndicative on-site warranty and spares cover; the term is set in the signed agreement
Product photography — GPU-dense rack and workstation range
Cloud Natives Managed Services
The build is the easy part. We run the estate afterwards — watched every second from a sovereign NOC, with capacity and spend reviewed monthly and an engineer who already knows your architecture answering the phone at 3 a.m.
- 24/7 infrastructure monitoring from an in-country NOC
- Deployment, commissioning and handover against written acceptance tests
- Cloud optimisation — rightsizing, commitment strategy, egress control
- Consulting and architecture review on a retained basis
99.999%Measured availability across managed platforms
11 minMedian time to human acknowledgement, P1
34%Average cloud spend reduction in year one
Operations imagery — sovereign NOC
Industries
A genomics pipeline is not a trading engine.
Filter by sector to see the constraint we design around first — the regulatory perimeter, the data gravity, or the deadline that cannot move.
Defence & National Security
Ruggedised, mission-critical compute, strict sovereign compliance and secure air-gapped environments where the network is deliberately absent.
Primary constraint — classification and isolation
Health Tech & Life Sciences
Accelerating genomic sequencing, diagnostic AI workloads and medical imaging pipelines without the patient data ever leaving its jurisdiction.
Primary constraint — throughput under privacy law
eResearch & Academia
Scalable HPC clusters enabling scientific discovery, climate modelling and multi-university collaboration under shared, auditable allocation.
Primary constraint — fair-share across institutions
Media & Entertainment
GPU rendering pipelines, VFX workflows and high-throughput media storage that keeps a hundred artists working against a locked delivery date.
Primary constraint — deadline and artist idle time
Startups & Scale-ups
Right-sized, growth-oriented infrastructure that scales from proof-of-concept to production without the rebuild that usually arrives with Series B.
Primary constraint — capital efficiency
The Arts & Culture
Large-scale digital archiving, GPU-accelerated interactive media and creative technology built to outlive the grant that funded it.
Primary constraint — permanence on a fixed budget
Capital Markets
Ultra-low-latency architectures where the entire competitive position is measured in nanoseconds and defended with hardware timestamps.
Primary constraint — determinism
No sectors match that constraint yet.
Measurable Outcomes
Numbers we are willing to be held to.
Every figure below comes from a deployed production estate, measured on the client's own workload. We publish the method with the number on request.
99.999%
Platform uptime
Measured availability across managed platforms over the trailing 12 months, excluding scheduled maintenance windows.
10×
Model training acceleration
Median speed-up moving customer training runs from prior mixed estate onto a purpose-built GPU fabric.
8.4PFLOP/s
Multi-petaflop deployments
Aggregate peak double-precision capability across HPC clusters delivered and in production.
68%
Latency reduction
Average p99 improvement on read-heavy pipelines after storage path and interconnect redesign.
41%
Compute efficiency gain
Improvement in useful work per kilowatt after scheduler, thermal and utilisation tuning.
3.2× ROI
Return on infrastructure
Three-year modelled return versus equivalent public-cloud consumption for steady-state training workloads.
Placeholder data. These six figures are illustrative and must be
replaced with audited measurements before this site goes live. Send me the real
numbers and their measurement method and I will wire them in, including the
methodology footnotes.
Insights & Deployment Stories
What we learned building it.
Deployment Story
Cover image — 1600×1000
Standing up a PROTECTED-level AI factory without a single byte leaving the country
How we designed a sovereign inference estate for a federal agency, and what the IRAP assessment changed about the network topology.
Deployment Story
Cover image — 1600×1000
Cutting a genomics pipeline from eleven days to nineteen hours
The bottleneck was never the CPUs. A storage-path teardown, and the three changes that recovered the other ten days.
Thought Leadership
Cover image — 1600×1000
Nanoseconds are an engineering budget, not a marketing number
Why tick-to-trade medians mislead, what p99.9 jitter actually costs a desk, and how to specify latency in a contract.
Deployment Story
Cover image — 1600×1000
One cluster, four universities, zero arguments about allocation
Designing fair-share scheduling and transparent accounting for a shared national research facility.
Thought Leadership
Cover image — 1600×1000
The real cost per token is a facilities question
Power, cooling and utilisation dominate inference economics long before the GPU invoice does. A costing model you can argue with.
Let's Talk
Bring us the workload that keeps missing its window. We'll benchmark it first.
No product catalogue, no discovery theatre. Send us the job, the dataset shape and the deadline. You get a profiled bottleneck analysis and an honest answer about whether we are the right team — often within a fortnight.
- New engagements
- hello@cloudnatives.example
- Direct line
- +61 0 0000 0000
- Existing clients — 24/7 NOC
- +61 0 0000 0001
Sydney · Melbourne · Canberra. Australian owned, Australian staffed.