Private AI cuts costs and speeds up decision-making
A national infrastructure operator worked with Xtravirt to prove private AI could match public cloud on quality while costing them less. Built on VMware Private AI Foundation and VMware Cloud Foundation, the platform gives teams faster, evidence-grounded answers from years of internal knowledge, with data and cost under their own control.
UK national infrastructure operator, with strict data governance requirements.
- Concerns regarding the cost and risk of Public Cloud AI
- Data sensitivity made public cloud inappropriate choice
- Operational documents siloed with no effective way to search
- Correlating huge volumes of disparate data was complex
- Minimum of three GPU-equipped hosts required for AI workload
- Harbor restricts AI models to a vetted, approved list only
- Among the first live UK deployments of this VMware solution
- Self-service catalogue gives on-demand access to GPU compute
- Predictive modelling now runs on elastic, on-demand compute
成果
- On-prem AI inference gives predictable cost and performance
- Benchmarking favoured private cloud AI for retrieval quality
- Cost modelling validated the on-premises advantage
- Private AI enabling faster, evidence-grounded decisions
- Data science team freed from manual resource constraints
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