Dedicated inference
A reproducible serving stack for open-weight models, provisioned on capacity that is not shared with anyone else.
- Capacity planning from your prompts and concurrency, not from vendor benchmarks
- vLLM or SGLang, quantisation chosen against a measured quality threshold
- Autoscaling within a hard ceiling, so a runaway client cannot empty your budget
- Load and soak testing before go-live, with the numbers written down
- Blue/green model rollouts with a tested rollback path