1
Engineer & Deploy
AI applications, models, infrastructure, storage and integrations are designed and implemented for the required environment.
AI OPERATIONS & LIFECYCLE
Production AI needs an operating model.
Models are only one part of an AI system. Applications, infrastructure, storage, integrations, security and dependencies all need to remain operational as the technology evolves.
We provide the ongoing oversight needed to maintain, protect and evolve production AI systems after deployment.
AFTER DEPLOYMENT
The AI may work. The environment still changes.
A production AI system is made up of moving parts.
Models evolve. Applications need updates. Dependencies change. Storage grows. Hardware ages. Security requirements increase. New versions become available.
An on-premise AI recording and transcription platform, for example, may continue functioning while its speech model becomes outdated, storage requirements increase or critical dependencies require attention.
Without ongoing ownership, a successful AI deployment can gradually become difficult to maintain.
The question is not only whether the system still works. It is whether it is still the right system to run.
AI OPERATIONS
Manage the whole system,
not just the model.
AI Operations provides ongoing technical oversight of the complete production environment.
1
System Operations
Monitoring the applications, services, infrastructure and integrations required to keep the system operational.
2
Models & Dependencies
Managing model versions, APIs, libraries and technical dependencies as the underlying technology evolves.
3
Security & Access
Maintaining access, credentials, permissions, security updates and appropriate controls around the AI environment.
4
Infrastructure & Capacity
Managing compute, storage and supporting infrastructure as utilisation and requirements change.
5
Backup & Recovery
Protecting relevant data, configurations and supporting systems, with recovery incorporated into the operating model.
LIFECYCLE MANAGEMENT
Maintain what works.
Maintain what works.
Improve what matters.
Retire what doesn't.
AI technology evolves quickly. Keeping every component simply because it is already deployed creates unnecessary cost and complexity.
We review production AI environments over time to determine what should be:
- Maintained - Continue operating components that remain appropriate and effective.
- Optimised - Improve performance, capacity, storage or infrastructure where there is a clear benefit.
- Updated - Introduce appropriate model, application, security or dependency updates.
- Replaced - Move to better technology or architecture when the improvement justifies the change
- Retired - Remove models, applications or infrastructure that no longer create enough value to justify maintaining them.
The objective is not to keep every AI system alive. It is to keep the right systems valuable.
One lifecycle.
Clear responsibility.
Our AI Systems Engineering & Integration capability designs, integrates and deploys production AI solutions.
AI Operations & Lifecycle takes responsibility for what happens after deployment.
2
Operate & Protect
The production system is monitored, maintained, secured, backed up and supported.
3
Review & Evolve
Models, infrastructure and dependencies are periodically reviewed as requirements and technology change.
AI should not become another isolated system nobody wants to touch.
Where appropriate, AI Operations can integrate with G2WS Managed IT, bringing the AI environment into the wider operational model for infrastructure, security, backup and support
AI OPERATIONS & LIFECYCLE
Keep production AI working, and worth running.
Whether you operate an on-premise AI system, an integrated AI application or a wider production environment, we can provide the ongoing operational and lifecycle support behind it.