📣 Introducing $2.95/Hr H100, H200, and B200s: train, fine-tune, and scale ML models affordably, without having to DIY the infrastructure 📣 Introducing $2.95/Hr H100, H200, and B200s: train, fine-tune, and scale ML models affordably, without having to DIY the infrastructure 📣 Introducing $2.95/Hr H100, H200, and B200s: train, fine-tune, and scale ML models affordably, without having to DIY the infrastructure
CASE STUDY

Mercury Insurance, a Leading P&C Insurer, Accelerated Model Deployment
and Collaboration using Saturn Cloud

From months to a couple of clicks for model scoring -
plus a core data engine in 4 days.

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Mercury's Key Challenges
Slow Path from Notebook to Production

Models were built/tested on local machines and promoting to endpoints often took weeks to months, delaying business impact.

Fragmented Environments & Complex IT

Standing up centralized servers inside a legacy, multi-team stack was difficult—most work ran on laptops.

Collaboration Drag

Sharing code, environments, and results across data science, analytics, and contractors was cumbersome and slow.

Need for Large-Scale Risk & Fraud Analytics

Mercury needed high-throughput anomaly/fraud detection and a fast data engine tightly integrated with existing AWS & warehouse systems.

RESULTS AND IMPACT

Saturn Cloud’s Self-Service ML Platform

Faster Deployment & Scoring

Python notebooks run on scalable Saturn Cloud workspaces, and a recently built model now takes only a couple of clicks to run predictions.

Result Meaningfully shorter cycle from experimentation to production scoring.

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Centralized, Scalable Workspace

Data scientists and analysts run claims, fraud, and anomaly models in shared/semi-prod environments instead of on laptops.

Result Consistent environments, easier handoffs, and less ops friction.

Rapid Pipeline Integration

Saturn Cloud stood up a high-performance data engine in 4 days, now the backend core of Mercury’s anomaly detection engine.

Result Faster time-to-value and tighter fit with existing AWS + warehouse data flows.

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Cost-Effective Scaling & Collaboration

Auto-scaling infrastructure and cloneable environments help speed onboarding and collaboration across teams and contractors. GPU virtual clusters are planned next to boost ML efficiency (targeting 10×+).

ResultLower overhead and clear runway for GPU-accelerated workloads.

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“Saturn Cloud is our best machine learning, AI, and data partner - phenomenal service, phenomenal product, phenomenal team. I would 200% recommend Saturn Cloud to anyone who needs a similar solution.”

Chief Data & Analytics Officer, Mercury Insurance

Learn how your team can move from local notebooks to a secure, shared platform for faster deployment, simpler ops, and is GPU-ready.

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