01
Sized from real workloads
We start with the models, context sizes, concurrent users and growth you expect, then choose hardware with stated assumptions instead of guessing or overbuying.
Private AI · Hardware
AI servers specified for the work, not the spec sheet.
GPU memory, storage speed and networking decide what models you can run and how fast. We specify AI servers from your workloads, coordinate procurement, assemble and configure them in our IT lab, and manage them after installation.
02
Built and tested before it ships
Our East Syracuse Tech Center includes an IT lab where systems can be assembled, burned in and configured before deployment.
- GPU, CPU, memory and storage selection
- OS hardening and model runtime installation
- Remote management and monitoring setup
- Documentation of configuration and access
GMTWhat we manage
- Workload-based hardware specification
- Procurement coordination with manufacturers
- Assembly, burn-in and configuration
- Deployment on-site or in hosting
- Ongoing patching, monitoring and support
Component availability and pricing change frequently. Quotes are valid only as written; hardware warranties are provided by manufacturers.
FAQCommon questions
Can you build workstations for developers too?
Yes, where a local AI workstation is the right fit. We specify them using the same workload-first approach.
Can the server be hosted instead of on-site?
Yes. See hosted private AI for options where Growth Mode operates the environment.
NEXTRelated
The humans your AI calls for tech support