AI FinOps & Cost Optimization
Most organizations overspend on AI infrastructure without realizing it. Idle GPUs, oversized instances, and inefficient serving pipelines can quietly drive up costs. We help teams optimize AI spend through GPU utilization analysis, training and inference cost profiling, model routing, serving efficiency, workload placement, and cluster right-sizing. We also establish FinOps governance with dashboards, alerts, and automated policies across AWS, Azure, and GCP.
Capabilities
- GPU utilization optimization and cluster right-sizing
- Training and inference cost profiling
- Model routing, caching, and serving efficiency
- Workload placement across cloud and GPU resources
- FinOps dashboards, alerts, and spend visibility
- Governance policies and automated cost controls
Typical Engagement Flow
We typically begin with an assessment, move into implementation, and then provide ongoing support as needed.
FinOps Assessment
Analyze cloud and AI infrastructure spend, identify waste and inefficiencies, and prioritize the highest-impact opportunities for cost optimization.
Starting at $3,000
Start AssessmentOptimization Implementation
Implement the cost optimization changes identified in the assessment, including cluster right-sizing, governance policies, and automated cost controls.
Custom scoped
Managed FinOps
Provide ongoing monitoring, optimization, and cost governance across your cloud and AI infrastructure, keeping spend aligned with usage as your environment evolves.
3–5% of cloud spend
Some clients start with an assessment only, but most continue into implementation and, where needed, ongoing support.
Ready to optimize your AI infrastructure costs?
Begin with an assessment, or start with a free AI infrastructure audit.