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Edge AI & Private LLMs
Custom private AI servers on high-performance local hardware — secure, intensive compute without third-party cloud reliance.
The challenge
Public LLM APIs create data residency risk, unpredictable costs, and latency that breaks real-time edge workflows.
How CES helps
We design bare-metal and rack-scale arrays with optimized PCIe topology, local model serving, and hybrid routing to your existing web tier.
Deliverables
- Hardware sizing & PCIe lane mapping
- Private inference runtime & model registry
- Hybrid cloud + on-prem orchestration
- Monitoring, rollback, and capacity planning
Typical stack
CUDAvLLMDockerKubernetesNVIDIAAMD ROCm