Frontier AI
The strongest models, applied to work that was out of reach.
Where Digital AI puts agents inside the systems you run, Frontier AI raises what the model itself can do for the enterprise — and puts engineers beside your teams to make it stick.
What it means
The model and infrastructure layers
frontier models, sovereign and self-hosted LLM/SLM, multimodal, fine-tuned and on-device — on cloud GPU, NVIDIA AI Enterprise, AMD and edge hardware.
Outcome
Frontier capability running in production, under your own governance.
Five layers that take an organisation from first access to frontier models running in production.
The Frontier platform · five layers
- 01
Enablement
Role-based skills, sandboxes and guardrails so people use Claude well and safely.
- 02
Adoption
Use cases ranked, piloted and rolled out with measured uptake.
- 03
Governance
Claude inside your ISO/IEC 42001, NIST AI RMF and EU AI Act posture.
- 04
Forward-deployed engineering
Engineers inside your teams taking frontier capability into production systems.
- 05
FrontierOps
Model routing, cost and latency, evaluation, drift and upgrades handled.
Where it lands
Three kinds of work it changes.
Enterprise productivity
Frontier models on the work that runs the business: procurement, finance, legal, operations. Long-context reasoning over the documents and decisions a department actually handles.
Employee productivity
Every knowledge worker with a governed assistant that knows the company's own systems, policies and data — adopted, not just licensed.
Frontier intelligence systems
New capability the organisation could not buy before: multimodal understanding, multi-agent orchestration, and evaluation and assurance around all of it.
The Frontier platform · with Anthropic
Claude, delivered as a platform your enterprise can run.
An Anthropic channel and forward-deployed engineering partnership is how we bring Claude into enterprise and government work in Australia and India: five layers that take an organisation from first access to frontier models running in production, under its own governance.
What the partnership covers
- Channel access to Claude models for enterprise and government
- Forward-deployed engineers embedded with client teams
- Governed deployments: evaluation, guardrails, audit evidence
Forward-deployed engineering
Blended consulting and AI engineering, inside your teams.
A forward-deployed engineer works with business and IT stakeholders to take AI pilots into production — and stays until the organisation can carry it. Enablement, adoption, ROI.
One engineer, five disciplines
- 01
Business analysis
Works with business users to turn ideas into AI systems, agents or skills.
- 02
Data engineering
Pulls in and transforms the data sources a model actually needs.
- 03
ML engineering
Hosts models and runs post-training to fit the customer's domain.
- 04
Cloud & platform
Deploys and integrates APIs as containers, production-grade.
- 05
Full-stack delivery
Integrates with applications and tests it end to end, like a developer.
Next domain
Sovereign AIStart the conversation
Extending the reach of AI beyond the screen — from the field to the factory floor and everything in between.
Ready to move forward? Let’s talk about your specific needs and how we can help you succeed.