Case Study
Transforming AI Security Training
Salt Security achieved 80% cost reduction and 90% less personnel time on infrastructure, freeing their team to focus on building the world's leading API security platform.
“SwarmOne boosted personnel efficiency by about 90%, significantly reduced training costs, and enhanced delivery, making us far more competitive in our market.”
Company
Salt Security
Industry
API Security / Cybersecurity
Key Outcome
80% cost reduction, 90% less ops time
The Challenge
Scaling AI Security Without Scaling Costs
Salt Security's AI-driven API protection platform relies on continuously trained threat detection models. As their model complexity grew, so did the infrastructure burden - threatening to slow the very innovation that set them apart.
- AI security model training consuming excessive cloud compute budget, with costs growing faster than the team could justify
- Engineering team spending the majority of their time on infrastructure operations - provisioning GPUs, monitoring jobs, and troubleshooting failures - instead of building better threat detection models
- Manual GPU provisioning creating unpredictable delays in the training pipeline, blocking time-sensitive security model updates
- No visibility into per-workload cost attribution, making it impossible to optimize spend or forecast infrastructure budgets accurately
The Solution
Why Salt Security Chose SwarmOne
Salt Security needed infrastructure that could keep pace with their rapid model iteration cycles while dramatically reducing the operational burden on their engineering team.
- Intelligent scheduling for optimal GPU allocation across training jobs, automatically selecting the most cost-effective hardware for each workload
- Automated infrastructure management eliminating manual ops entirely - from provisioning to teardown, no human intervention required
- Real-time cost analytics with per-model cost tracking, giving the team clear visibility into exactly what each training run costs
- Multi-cloud price arbitrage to automatically access lowest-cost compute across providers without manual comparison or migration
The Impact
Results That Speak for Themselves
80%
Cost Reduction
90%
Less Personnel Time
$180-230K
Annual Savings
Cost efficiency: 80% reduction in compute costs through intelligent GPU allocation and multi-cloud price arbitrage - saving $180K–$230K annually.
Team productivity: 90% less personnel time on infrastructure, allowing security researchers to focus on threat model development instead of GPU management.
Operational clarity: Per-model cost tracking gives leadership full visibility into infrastructure spend and enables data-driven budgeting.
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