Team Rays, LLC helps government and regulated organizations modernize infrastructure with secure-by-design cloud, VDI/EUC, and AI-ready compute. We also advise AI startups and quantitative research teams on GPU architecture, cost modeling, and scalable deployment patterns.
Professional services built for fast decisions, clean delivery, and measurable outcomes.
We structure work in a way that supports regulated requirements, documentation, and secure handoffs. Designed to reduce risk and accelerate modernization.
Architecture and tuning for AWS/Azure/GCP, plus VDI/EUC environments (AVD, Citrix, VMware) with performance and user experience in mind.
We design GPU/cloud environments for training, inference, and research workloads—especially where latency, throughput, and cost curves matter.
Clear scope, clean execution, and practical architecture you can actually deploy.
Registered AWS Partner (Partner Central) supporting secure cloud and AI infrastructure deployments.
Government contracting readiness and key vendor identifiers.
Team Rays, LLC is a woman-owned professional services organization specializing in secure cloud, AI infrastructure, VDI/EUC modernization, and cyber services. Ready to support prime contractors and federal agencies.
Registered in SAM.gov with Active status and ready to bid on contracts requiring these capabilities.
GetGPUFast.ai operates as the AI Infrastructure division of Team Rays LLC. We help AI startups and quantitative research teams design secure, scalable GPU and cloud architectures for training, inference, and advanced workloads.
Case study style: A research team running bursty GPU workloads was overspending due to mis-sized instances and unoptimized job scheduling. We reworked the architecture with a hybrid strategy, introduced cost controls and right-sizing, and improved throughput while reducing monthly compute spend. The result was a predictable cost curve and faster iteration cycles—exactly what high-velocity quant and AI teams need.
GPU sizing, workload segmentation, multi-environment design, cloud cost modeling, secure reference architectures.
Deployment guidance, DevSecOps alignment, performance tuning, production hardening, and operational handoff.
Cost control, reliability engineering, GPU workload optimization, and ongoing architecture refinement.
We treat compute like a portfolio: manage variance, control downside risk, and optimize the cost/performance frontier.
Easy entry point → paid diagnostic → implementation oversight.
If you want a clean plan and a realistic path to production—book a strategy call. We’ll clarify scope, success criteria, and a delivery plan you can act on immediately.
Email a short description of your workload (GPU type, model size, dataset size, SLA/latency, and current cloud). We’ll respond with next steps and the right entry offer.
