Managed AI servers and platforms
Day-to-day administration of your AI environment.
EXZAI Managed Services
Keep your AI reliable beyond launch.
Monitoring, maintenance, security, model lifecycle and cost optimization for enterprise AI environments.
An AI platform is a living system: models change, dependencies age, usage grows and costs drift. EXZAI Managed Services keeps it observable, secure and efficient after go-live.
What we deliver
GPU and inference monitoring
Utilization, latency, errors, capacity and availability.
Patch and lifecycle management
Updates, dependency management and lifecycle planning.
Security hardening
Privileged access, network segmentation, vulnerability review and incident coordination.
Backup and restoration testing
Where included in the agreed scope.
Model lifecycle management
Version pinning, evaluation, rollout and rollback.
RAG quality monitoring
Data ingestion and retrieval quality tracking.
Cost and performance optimization
Batching, quantization, caching and routing as appropriate.
Service desk and escalation
Optional, with coverage windows defined by contract.
Runbooks and governance reporting
Documentation, knowledge transfer and regular reporting.
Indicative service tiers
Essential
Health monitoring, scheduled maintenance and reporting.
Business
Broader operational coverage, security review and regular optimization.
Enterprise
Tailored coverage, resilience, governance and contractual service levels.
Tiers describe scope only. Coverage, pricing and service levels are defined in each contract.
Your data. Your deployment choices.
Run AI on your own servers, in a dedicated environment or in a carefully designed hybrid architecture. EXZAI helps you choose the right combination of model performance, governance, cost and operational control.
On-premises
AI on your own infrastructure
For sensitive workloads, internal network access and customer-owned hardware. Security and data residency depend on configuration and controls.
Private cloud
A dedicated, managed environment
Managed isolated infrastructure with less hardware for your team to operate. Hosting location and contractual terms are specified for each engagement.
Hybrid
Private data, selective external compute
Keep private data operations in your environment and use external compute or APIs where appropriate. Requires a data-flow map and review of cross-border considerations.
Edge & desktop
Local AI for teams and edge sites
For developer teams, local prototyping and disconnected or edge needs. Capacity depends on the chosen machine and model.
From first assessment to daily operations.
We prioritize measurable use cases, a clear technical architecture, responsible deployment and long-term maintainability.
- 01
Discover
Business outcomes, data landscape, constraints and target users.
- 02
Design
Architecture, model selection, security approach, total cost and pilot metrics.
- 03
Pilot
A narrow proof of value measured against agreed evaluation criteria.
- 04
Deploy
Production infrastructure, integrations, access, tests and documentation.
- 05
Operate
Monitoring, updates, support and optimization.
- 06
Enable
Administrator training, user adoption and ongoing improvement.
Ready to make AI work for your organization?
Tell us what you want to build. We will help define a practical technical and commercial path.