Infrastructure

Flexible deployment options that respect your data sovereignty requirements while delivering exceptional performance.

Your Data, Your Control

We believe organisations should have complete control over their data and AI infrastructure. That's why we offer flexible deployment options that respect data sovereignty requirements.

Honouring Data Sovereignty

As a company we understand the importance of data sovereignty. The principles of Te Mana Raraunga (Maori Data Sovereignty) recognise that Maori data should be subject to Maori governance and that Maori have inherent rights over their data.

We extend this philosophy to all our customers: your data belongs to you, and you should have complete control over where it resides, how it's processed, and who has access to it. Our flexible deployment options ensure you never have to compromise on data sovereignty.

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Fully On-Premises

Deploy Wairua.ai entirely within your own infrastructure using Apple Silicon Macs. Your data never leaves your premises.

  • Complete data isolation
  • No external dependencies
  • Full regulatory compliance
  • Air-gapped deployment option

Cloud Mac Deployment

Leverage dedicated Mac infrastructure in the cloud with guaranteed hardware isolation and regional data residency.

  • Dedicated Mac hardware
  • Choose your data region
  • No shared infrastructure
  • Enterprise SLA guarantees
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Traditional Cloud

For organisations comfortable with cloud deployment, we offer fully managed hosting on major cloud providers.

  • AWS, Azure, or GCP
  • Auto-scaling capabilities
  • Managed updates and maintenance
  • Global availability

Why Apple Silicon for AI Inference?

Exceptional Power Efficiency

Apple Silicon delivers up to 3x better performance per watt compared to traditional GPU servers. Run powerful LLMs while dramatically reducing your energy costs and carbon footprint.

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Unified Memory Architecture

With up to 192GB of unified memory on Mac Studio, run large language models that would require expensive multi-GPU setups on traditional infrastructure.

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Silent Operation

No noisy server rooms required. Mac hardware runs whisper-quiet, making it perfect for office deployment without dedicated cooling infrastructure.

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Lower Total Cost

When you factor in power consumption, cooling, and maintenance, Apple Silicon deployments often cost 50-70% less than equivalent GPU server infrastructure.

Environmental Impact: GPU vs Apple Silicon

Running AI workloads responsibly matters. Here's how Apple Silicon compares to traditional GPU infrastructure for LLM inference at enterprise scale.

Traditional GPU Server (NVIDIA A100)

400W
Power per GPU
6,400W
8-GPU Server Total
~2,400W
Additional Cooling
77,000 kWh
Annual Energy Use

Mac Studio M2 Ultra Cluster (4 units)

75W
Power per Mac (Avg)
300W
4-Mac Cluster Total
~0W
Additional Cooling
2,628 kWh
Annual Energy Use
96%
Less Energy
33 tons
CO2 Saved/Year
$8,400
Annual Savings
0 dB
Office Noise
Methodology: Comparison based on equivalent inference throughput for 70B parameter models. GPU server: 8x NVIDIA A100 80GB with liquid cooling. Mac cluster: 4x Mac Studio M2 Ultra 192GB. Energy costs calculated at $0.12/kWh average. CO2 emissions based on US grid average of 0.42 kg CO2/kWh. Actual results vary based on workload, model size, and regional energy mix.

Ready to Discuss Your Infrastructure?

Let us help you choose the right deployment option for your organisation's needs.

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