Core offering
AI Managed Services
Round-the-clock operations, so your team can focus on what matters.
Running infrastructure shouldn't slow your business down. ApexInfer's managed services take ownership of day-to-day operations: monitoring performance, responding to incidents, applying patches, managing backups, and keeping your environment secure, compliant and cost-efficient. We run GPU fleets and AI platforms as confidently as traditional cloud and infrastructure. That means model-serving uptime, GPU utilisation and inference latency sit alongside CPU, storage and network health. It covers our bare metal and private cloud, your own data centre, and AWS, Azure and Google Cloud. From startups scaling fast to enterprises running mission-critical workloads, we deliver enterprise-grade reliability without the overhead of a large in-house team.
Service scope
| Area | What we manage | Key measures |
|---|---|---|
| AI & GPU operations | GPU health and scheduling, driver/CUDA lifecycle, model serving (vLLM, SGLang, TensorRT-LLM), MLOps pipelines | GPU utilisation, inference latency, serving uptime |
| Cloud operations | AWS, Azure and GCP environments, Kubernetes clusters, landing-zone guardrails | Availability, change success rate, incident response time |
| Infrastructure operations | Bare metal, private cloud and on-premises servers, storage and network | Uptime, capacity headroom, patch compliance |
| Security, backup & FinOps | Threat detection, vulnerability management, backup/DR, cost governance | Open vulnerabilities, recovery tests passed, cost vs. budget |
What's included
- Monitoring, alerting and incident response
- Patch, upgrade and lifecycle management
- Backup and disaster-recovery management
- Security monitoring and compliance management
- Cloud governance, billing oversight and cost reporting
- GPU fleet and AI platform operations
- Runbooks, SLAs and clear escalation paths
- Monthly service reviews against agreed measures
Outcome
Always-on operations, predictable performance, and peace of mind.