Predictable demand
Dedicated GPUs need sustained utilization. Traffic shape, concurrency, peaks, and batchability matter.
Managed AI infrastructure
Own the AI workloads that cost the most.
Norite finds repeatable inference traffic that can move safely from model APIs to dedicated GPUs, proves the economics, migrates it, and operates the stack.
Proprietary, irregular, or difficult requests can stay on external APIs. The goal is a cheaper workload mix, not migration for its own sake.
Selective routingworkload by workload
Predictable trafficRepeated, benchmarkable requests
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Candidate routeNorite-managed dedicated GPUs
Frontier / burst trafficNovel, proprietary, or irregular requests
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Retained routeExternal model APIs
Qualification
Dedicated capacity only works when the workload earns it.
Norite is for AI companies with enough stable inference demand for infrastructure savings to exceed migration and operating cost.
Suitable model quality
An open-weight candidate must pass the customer’s real quality, context, tool-use, and reliability requirements.
Sufficient scale
Avoided API cost must cover hardware, financing, power, hosting, redundancy, operations, migration, and management.
Operational fit
Latency, availability, data residency, security, fallback behavior, and growth must fit the deployment.
The migration thesis
Move the cheap-to-own work. Keep the rest flexible.
A strong deployment is usually hybrid. Norite can recommend partial migration or no migration at all.
Good candidates
- Routine generation with stable quality requirements
- Embeddings, reranking, and repetitive agent jobs
- Consistent regional workloads
- Traffic that can keep expensive GPUs occupied
Requests that may stay on APIs
- Frontier work with no acceptable open-weight replacement
- Temporary demand spikes and burst overflow
- Tasks that fail quality or latency testing
- Workloads where self-hosting increases total cost
How it works
Evidence first. Hardware later.
The deployment starts with workload data, not a preferred GPU model.
Measure the workload
Review invoices, traffic, latency, quality, security, and region.
Test replacements
Evaluate candidate models and measure throughput and latency.
Size the system
Model capacity, redundancy, growth, hosting, financing, and full TCO.
Migrate and run it
Move qualified traffic gradually and retain API overflow.
Workload economics
Start with the part of the bill that could actually move.
This calculator splits current API spend into a candidate migration share and retained API spend. Hardware savings stay pending until a measured configuration exists.
Use the actual monthly invoice when available.
Current API-only cost$60,000
Candidate API spend to evaluate$39,000
Retained API spend$21,000
Managed infrastructure cost and savingsBenchmark required
Before savings are shown, model quality, memory fit, throughput, latency, redundancy, hosting, maintenance reserve, and growth must pass validation.
Deployment options
The infrastructure can live where the workload needs it.
Customer premises
Dedicated hardware installed at the customer site and managed by Norite.
Norite-hosted dedicated
Dedicated capacity hosted in an appropriate EU or US facility.
Shared managed capacity
For workloads that do not yet justify a full dedicated deployment.
Hybrid infrastructure
Qualified traffic runs on managed GPUs while difficult or burst requests stay on external APIs.
FAQ
Questions before an assessment
Does Norite replace every model API?
No. Norite focuses on traffic that is technically suitable, predictable, and expensive enough for dedicated capacity to make sense.
Can difficult requests stay on external APIs?
Yes. Hybrid routing is a first-class deployment pattern.
How is hardware selected?
After workload analysis and model testing, using measured throughput, latency, peak demand, redundancy, maintenance reserve, and growth.
Can Norite recommend not migrating?
Yes. If model quality, latency, utilization, security, or economics fail, keeping the workload on APIs is the correct result.