Own your model. Deploy it anywhere.
A trained model only earns once it is serving traffic. We take the open model we fine-tuned on your data and deploy it on the fastest, most cost-effective inference for your case — serverless, dedicated, or inside your own cloud — behind a governed gateway, with your weights portable and no lock-in.
From an open model to your app.
One continuous path: start from a strong open model, specialize it on your data, serve it on optimized inference, and put a governance gateway in front — so what reaches your users is fast, grounded, and controlled.
Serve it the way your case demands.
The same model runs three ways. We choose for latency, cost, and compliance — and you can move between them as you scale.
Serverless
Pay per token, no infrastructure to manage — the fastest way to ship. Ideal for spiky or early-stage traffic, with OpenAI- and Anthropic-compatible APIs so your app barely changes.
Dedicated / on-demand
Reserved GPU capacity for predictable, low latency at steady volume — multi-region, with room for your post-trained models and higher quotas.
Self-hosted / in your VPC
Runs in your own cloud or on-prem for full control, data residency, and air-gapped options — the same model, inside your walls.
Your model. Your weights. Portable.
We do not run our own GPU cloud, and we do not tie you to one. We deploy your model on whichever inference layer fits best — a managed provider for speed and elasticity, or self-hosted open runtimes in your cloud for control — and because you keep the weights, you can change providers without a rebuild. Our value is the last mile: specialization, the gateway, evaluation, and operations, not the silicon.
Representative — we integrate with the provider or runtime that fits your latency, cost, and compliance needs.
Serving open models well is where cost and latency are won or lost. We quantize, batch, cache, and right-size the deployment — and route easy queries to cheaper models — so quality holds while the bill drops. The full treatment lives in AI Operations.
Bring us a hypothesis. Leave with a system.
Tell us what's eating your team's time. We'll give you an honest read on whether AI is the right tool — and if it is, a scoped v1 with a timeline and cost.