$1.92T market by 2030. Energy storage, battery, and green hydrogen companies cut cloud costs 15–25% without slowing R&D. FinOps optimization reduces burn rate immediately.
Simulation-heavy platforms. Founders are engineers, not cloud economists. Cost control enables faster innovation.
Battery simulations, molecular modeling, grid optimization—compute-hungry. Cloud costs spiral; founder teams lack DevOps expertise.
Battery modeling, thermal analysis, grid simulations require GPU/HPC. Right-sizing is critical; waste is easy.
PHD scientists, not cloud engineers. No one owns cloud cost or optimization. Bill surprises kill progress.
R&D-stage companies spending $100K+/month on cloud before any revenue. Burn rate matters to investors.
Rapid experimental iterations + prototype scaling. Infrastructure balloons; old prototypes linger.
CleanTech companies market sustainability. Cloud carbon footprint matters; need reporting.
Investors ask: "How much is cloud costing? Is it optimized?" Growth + efficiency story matters.
Continuous cost optimization + sustainability metrics. Founders focus on innovation; we own the cloud efficiency.
Monthly waste reduction: GPU right-sizing, batch job optimization, data storage tiering, spot instance strategy.
Production SageMaker pipelines for battery prediction, thermal modeling, grid optimization models.
Early-stage cleantech startup: $120K/month AWS spend (battery simulation + prototype infrastructure).
Problem: No optimization. Old prototypes still running. GPU instances idle nights/weekends. CFO burning runway.
Identified $28K/month waste: idle GPUs, unshut dev environments, simulation output storage billing as "hot" data.
Implemented: Auto-shutdown, spot instances, lifecycle policies, batch job scheduling.
New run-rate: $92K/month (23% reduction = $28K/month savings)
Retainer cost: $6K/month → ROI immediate + ongoing
VC pitch: "Cloud efficiency: 23% improvement, still scaling R&D spending"
20 minutes to identify cost waste. VC-ready efficiency metrics included.
Cut design and fab simulation costs 15–25%. Enterprise-grade SLA compliance for chip design operations.
Reduce cost-per-transaction while maintaining SOX/PCI-DSS compliance. Essential for payment processors and neobanks.
Audit-ready infrastructure with cost optimization. Combine genomics compute optimization with compliance.
Maintain 99.99%+ SLA compliance while cutting infrastructure costs. Multi-region optimization for carriers.