Models & Infrastructure
AI Hardware & Infrastructure
Cloud GPUs, on-prem hardware, or managed inference: pick your compute strategy with real numbers.
Compute decisions get made under pressure and rarely get revisited, which is how companies end up over-provisioned on cloud GPUs or under-provisioned on hardware that can't keep up. This engagement builds an actual cost model comparing cloud GPU, on-prem, and managed inference options for your specific workload, then sizes and helps provision whichever one wins on real numbers, not vendor pricing pages.
Sound familiar?
- ✓GPU cloud bills are climbing and no one's sure if on-prem hardware would actually pay off
- ✓You're about to buy hardware for AI workloads and don't want to over- or under-provision
- ✓Choosing between cloud GPU providers feels like guesswork with no clear pricing logic
What the engagement looks like
Compute options analysis
Cloud GPU versus on-prem versus managed inference, compared on real cost and performance for your workload.
Sizing and vendor selection
Right-sized hardware or instance recommendations so you're not paying for headroom you'll never use.
Infrastructure setup
Hands-on help provisioning and configuring the compute environment you land on.
This is a good fit if you're…
- Teams with growing GPU cloud spend and no cost model behind it
- Companies weighing on-prem hardware for the first time
- Anyone comparing cloud GPU or inference vendors and wanting an unbiased read
Rate for this engagement runs $150–$250/hr, scoped after a free intro call.
Frequently asked questions
At what point does on-prem hardware make sense over cloud GPUs?
Usually once utilization is high and steady enough that the hardware pays for itself within 12 to 18 months versus ongoing cloud rates. Bursty or unpredictable workloads almost always favor cloud. The break-even point is calculated for your actual usage, not assumed.
Which cloud GPU providers do you evaluate?
The major clouds (AWS, GCP, Azure) plus specialized GPU cloud providers, compared on price, availability, and how well they fit your workload. Recommendations aren't tied to any one vendor.
Can you help with capacity planning as we scale?
Yes. Sizing recommendations include headroom for reasonable growth, and larger engagements can include a revisit point once usage data comes in.
Ready to get started with AI Hardware & Infrastructure?
No pitch deck, no obligation. Just a straight answer on whether AI can actually help your situation, and how.
$150–$250/hr · no contracts, no retainers required