Run every model, project and workload from one place.
Control spend. Scale when you need it.
Automate what should not be manual.
AI workloads move fast — machines, projects, models and teams all consume resources. One clear view shows what is running, what it costs and where to optimise. No hidden compute. No surprises at the end of the month.
Control AI spend before it controls you.
AI is easy to prototype, hard to scale. Run demanding workloads with high performance — text and audio streaming, image analysis, content generation, knowledge-grounded apps. Use the models you need, serve real-time experiences, all without managing the complexity behind it.
More capacity when you need it. Less friction when you grow.
Your developers shouldn't fight the infrastructure to ship AI. Run multiple instances of vLLM, SGLang, Ollama or llama.cpp behind one endpoint, swap engines as you scale, and keep building on the tools they already know. The platform handles the infra — your devs handle the AI.
Built for teams scaling AI — not fighting infra.
Same URL · swap the engine behind it
Not every workload needs a machine running 24/7. Smart rules let you define how workloads run — start machines when there is work, stop them when there is none, group tasks, prioritise what matters. Less idle time. Lower costs. Better use of infrastructure.
Let rules handle the work. Keep compute under control.
Unlimited cloud servers on every plan. Financial control on every plan. You only pay for how many private servers you run.
Create a project, connect a server, route your first workload in minutes.
Open InferenceKey Cloud cloud.inferencekey.com