Private AI: Sovereign, Controlled, Secure

Public AI services are the right solution for most organisations. But for some, the requirements are different.

Large enterprises with strict data sovereignty requirements, Australian government agencies operating at PROTECTED or above, defence contractors with DISP obligations, healthcare organisations handling sensitive clinical data, and financial institutions with regulatory data residency requirements may need AI capability that stays entirely within their own controlled environment.

Evocate helps these organisations plan and implement private AI infrastructure, bringing large language model capability in-house, on Australian soil, within environments they control.

Private AI Infrastructure Consulting Australia

Infrastructure assessment

Infrastructure Assessment and Planning

We assess your current data centre or private cloud environment against the compute, storage, networking and cooling requirements of large language model workloads. AI inference workloads are GPU-intensive. Planning the right hardware and infrastructure configuration upfront avoids costly rework. We help organisations understand the realistic costs and complexity of private AI infrastructure, and where a hybrid approach (private for sensitive workloads, cloud for general workloads) may be more practical.
LLM model selection

Model Selection and Deployment

The private AI market has matured significantly. Open-weight models such as Meta’s Llama series, Mistral, and Microsoft Phi are deployable on private infrastructure with performance that is suitable for many enterprise use cases. We help organisations select the right model for their use case, performance requirements and hardware constraints. We deploy and configure model serving infrastructure using frameworks such as Ollama, vLLM and Azure Arc for on-premise AI, creating endpoints that can be consumed by enterprise applications in the same way as cloud AI APIs.
Business systems integration

Integration with Business Systems

Private AI infrastructure is only valuable when it is connected to the data and applications your organisation uses. We integrate private AI endpoints with SharePoint, business applications, document management systems and workflow platforms, enabling AI-powered search, summarisation, drafting and automation that operates entirely within your environment.
Security and access controls

Security and Access Controls

We implement role-based access, network segmentation, audit logging and monitoring for private AI infrastructure, ensuring that AI capability is available to authorised users and auditable for compliance purposes.
Operational support

Operational Support and Maintenance

Private AI infrastructure requires ongoing maintenance: model updates, performance monitoring, capacity management and security patching. We can provide managed services support for private AI environments, or train your team to manage them.

Why Some Organisations Need Private AI

Several scenarios drive the need for private AI infrastructure:

Data Sovereignty

Organisations that cannot send data to external AI services regardless of contractual protections: certain government agencies and intelligence-adjacent contractors.

Regulatory Compliance

Healthcare, financial and legal data subject to regulations that restrict where it can be processed.

Security Classification

Organisations working with classified information that cannot process data through public APIs.

Model Control

Organisations needing to control which AI models are used, how they are updated, and what data they have been trained on.

Latency & Reliability

High-volume AI workloads or latency-sensitive applications where private infrastructure is more performant.

Private AI Infrastructure Capabilities Evocate Delivers

Practical delivery areas with the architecture, governance, and adoption detail needed for production Microsoft environments.

1

Infrastructure Assessment and Design

Evocate evaluates your current infrastructure, workload requirements, and security constraints to design a private AI architecture that balances performance, cost, and sovereignty obligations.

  • Workload profiling and compute requirement analysis
  • GPU hardware specification and procurement guidance
  • Network architecture design for AI inference
  • Storage and data pipeline planning
  • Hybrid architecture design combining private and cloud
2

Model Selection and Deployment

Evocate selects, configures, and deploys open weight language models optimised for your specific use cases on private infrastructure with appropriate quantisation, context windows, and inference settings.

  • Use case to model matching and benchmark evaluation
  • Model quantisation and optimisation for target hardware
  • Inference server deployment and configuration
  • Model versioning and update management
  • Performance tuning and throughput optimisation
3

RAG and Knowledge Integration

Evocate builds Retrieval Augmented Generation systems that connect private models to your organisational knowledge without exposing data to external services.

  • Vector database selection and deployment
  • Document ingestion pipeline development
  • Embedding model selection and configuration
  • Retrieval strategy design and relevance tuning
  • Knowledge base maintenance and refresh procedures
4

Security and Access Controls

Evocate implements security controls for private AI infrastructure including authentication, authorisation, audit logging, and network segmentation appropriate to your classification requirements.

  • Authentication and authorisation framework
  • Network segmentation and access controls
  • Audit logging for all AI interactions
  • Data classification enforcement at inference time
  • Encryption for data at rest and in transit
5

Operations and Managed Services

Evocate provides ongoing operational support for private AI infrastructure including monitoring, model updates, performance optimisation, and capacity planning as usage grows.

  • Infrastructure monitoring and alerting
  • Model performance tracking and degradation detection
  • Capacity planning and scaling recommendations
  • Security patch management and vulnerability response
  • New model evaluation and upgrade planning

Business Benefits and ROI

Outcomes designed around measurable business value, stronger governance, and lower operational friction.

Data Sovereignty

AI processing stays within your controlled environment on Australian soil.

Compliance Alignment

Meet strict regulatory and classification requirements that prohibit public cloud AI.

Model Control

Full control over model selection, updates and training data exposure.

Hybrid Flexibility

Option to combine private infrastructure for sensitive workloads with cloud for general use.

Evocate’s EVOLVE Methodology

A structured delivery rhythm that keeps discovery, validation, launch, and continuous improvement connected.

1

Engage

Understand your data sovereignty requirements, target AI use cases, existing infrastructure, and organisational constraints that drive the need for private deployment.

2

Validate

Assess workload requirements, evaluate hardware options, confirm network and security prerequisites, and validate that private deployment meets your compliance obligations.

3

Optimise

Design the target architecture, select models, plan RAG infrastructure, and establish security controls before procurement and deployment begins.

4

Launch

Deploy infrastructure, configure models, build knowledge pipelines, and deliver to pilot user groups with monitoring and feedback mechanisms active.

5

Verify

Validate model performance against benchmarks, confirm security controls through testing, and measure user satisfaction with response quality and latency.

6

Evolve

Ongoing infrastructure management, model upgrades as open weight capabilities improve, capacity expansion, and new use case enablement.

Industries We Serve

Government

Private AI for government agencies with PROTECTED-level data and sovereignty requirements.

Utilities & Energy

Private AI for utilities and energy organisations with critical infrastructure data that cannot leave controlled environments.

Defence

Private AI for defence organisations with classified environments and DISP obligations.

Transport & Logistics

Private AI for transport and logistics companies with proprietary route optimisation data and competitive supply chain intelligence.

Healthcare & Aged Care

Private AI for healthcare organisations with sensitive clinical data and privacy legislation requirements.

NDIS & Community Services

Private AI for NDIS and community service providers with sensitive participant data requiring on-premise or sovereign cloud processing.

Mining & Resources

Private AI for mining and resources companies with geological survey data, operational intelligence and remote site processing requirements.

Professional Services

Private AI for professional services firms with client-privileged data, legal confidentiality and regulatory data residency requirements.

Integration with the Microsoft 365 Ecosystem

Clean integration points across Microsoft 365, Power Platform, security, automation, and employee experience.

Azure Stack HCI

On premises infrastructure for organisations running private AI workloads on Microsoft hybrid cloud hardware with Azure management.

NVIDIA AI Enterprise

GPU infrastructure and inference optimisation for production AI workloads on private hardware.

SharePoint

Knowledge source integration for RAG systems connecting private models to organisational content stored in SharePoint libraries.

Microsoft Entra ID

Identity and access management controlling who can interact with private AI services and under what conditions.

Azure Arc

Unified management plane for private AI infrastructure with Azure policy, monitoring, and security controls.

Vector Databases

Embedding storage and retrieval infrastructure for RAG systems including Azure AI Search, Qdrant, and Weaviate deployments.

Delivery that fits your business

Microsoft Partner

Practical guidance across Microsoft 365, Azure, SharePoint, Teams, Dynamics 365, Power Platform, security, and governance.

Certified Consultants

Senior specialists who can move from strategy into delivery, adoption, migration, support, and continuous improvement.

Australian Business

Local consulting for Australian organisations, backed by national experience and a delivery record across the country.

Why Evocate

Experience

Delivering Microsoft consulting outcomes since 2009.

Clients

Trusted by 186 clients across Australia and the Asia-Pacific region.

Delivery

622 completed projects and 1,068 total engagements.

Trusted by 186 organisations across Australia

Government Defence Utilities Healthcare Aged Care NDIS Mining Financial Services Professional Services
Basslink
Linx Cargo Care
Melbourne Airport
Mazda
Rinnai
Linfox
Penske
Sigma Healthcare
DJPR
EPA Victoria
Hostplus
University of South Australia
MACG
AIDA
Vinnies
VMCH
EACH
Cohealth
MyHealth
Asteria
Elbit Systems
Microsoft Solutions Partner for Modern Work Microsoft CSP Tier 1 Partner
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Frequently Asked Questions

Meaningful LLM inference requires GPU hardware. For smaller open-weight models (7B-13B parameters), modern enterprise GPU servers (such as NVIDIA A-series or H-series) provide suitable performance. Larger models (70B+ parameters) require multi-GPU configurations. We assess your target use case and recommend hardware accordingly.
Open-weight models have improved significantly. For many enterprise use cases (document summarisation, question answering over internal knowledge, structured data extraction) modern open-weight models perform comparably to commercial models when correctly configured. For tasks requiring the highest level of general reasoning, cloud models currently have an advantage, which is why many organisations use a hybrid approach.
It depends on usage volume and data sensitivity requirements. For high-volume AI workloads where data sensitivity makes cloud unsuitable, private infrastructure can be cost-effective. For lower-volume workloads, cloud AI is typically more economical. We help organisations model both options.
Evocate has experience with Australian government environments and understands the requirements of PROTECTED-level deployments including the ISM controls and Microsoft’s Australian government cloud. We can help organisations assess whether private infrastructure or the Microsoft government cloud region is the appropriate solution for their classification requirements.