Proof & Benchmarks

See how organisations like yours are saving tens of thousands of dollars by eliminating hidden waste in their AI and ML workloads.

Impact in Numbers

23%

Waste reduction achieved by a global financial services firm using ML‑driven optimisation.

31%

Cost reduction delivered for a healthcare technology provider after deploying Guard and tuning resources.

28%

Monthly cloud spend saved by a leading e‑commerce platform through reinforcement learning‑powered scheduling.

35%

Increase in resource efficiency for a manufacturing conglomerate through automated rightsizing and OOM loop prevention.

Visual Benchmarks

Case Studies Savings

Savings distribution across multiple case studies

Training Cost Savings

Training cost savings achieved via GPU sharing and right‑sizing

Cost Inefficiencies

Persistent cost inefficiencies in AI workloads before optimisation

Multi‑Cloud Adoption

Adoption of FinOps across multi‑cloud environments

Balanced Outcomes

Balanced outcomes when cost, performance and impact are optimised

FinOps Priorities

FinOps priorities for 2025: waste reduction, cost allocation and forecasting

Put These Numbers to Work

These benchmarks are just the beginning. Every organisation has a unique waste profile. Use our ROI calculator or schedule a free assessment to see what MLMind can do for you.

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