Brittle code
Model choices buried in application code make every switch a release.
Deployments
Ship models
like you ship code.
Give every model a stable name, sensible defaults and the controls production deserves. Then change it without touching a line of code.
Free to start · No card required · Live in minutes
Minutes
from catalog to production
1 API
for every deployment
0
servers for you to manage
2×
the free allowance of typical platforms
Production AI shouldn’t feel like a science project.
Hard-coded model names, scattered settings and nervous redeploys turn every improvement into a risk.
Config drift
Defaults differ across services and nobody knows which one is right.
Ops overhead
Standing up and scaling serving infrastructure eats the roadmap.
Capabilities
Deployments, done properly
Everything you need to run AI models in production with confidence.
Named deployments
Reference a deployment, not a model, and upgrade underneath without a code change.
Default model
Set an account-wide default so every request has a sensible home.
Cache controls
Decide how long repeated answers stay valid for each workload.
Throughput limits
Requests-per-minute guardrails that protect your product and your budget.
Per-deployment insight
Tokens, latency, errors and spend, broken down the way you think about them.
Fully managed
No clusters, no capacity planning, no pager. We run it; you ship.
How it works
Deploy in three steps
- 1
Pick from the catalog
Choose the model that fits the job and try it in the Playground.
- 2
Configure
Set defaults, cache window and limits in the console.
- 3
Call it
Use your key and one endpoint. Your deployment is live.
Use cases
Teams deploy to
Launch new features
Go from prototype to production without a platform project.
Upgrade safely
Move to a better model while your application code stays put.
Separate workloads
Keep experimentation and production traffic cleanly apart.
Control cost
Route each workload to the model that fits its budget.
Outcomes
Why teams deploy here
0
infrastructure to run
Serving, scaling and metering are handled for you.
1
place to change a model
Swap models in the console, not in a release.
Full
request history
Every call recorded so you can prove what changed.
Your roadmap, not your infrastructure.
Spend your best engineers on product. We’ll handle the serving.
FAQ
Questions, answered
Do I need to manage servers?
No. Deployments are fully managed — you configure them in the console and call them over the API.
Can I change the model behind a deployment?
Yes. Update it in the console and your application keeps calling the same name.
How do I keep test traffic separate?
Use separate keys and deployments, and filter analytics by either.
What happens if I go over my limit?
Requests beyond your requests-per-minute limit are refused cleanly, so you can back off and retry.
Is there a free tier?
Yes — about twice the free allowance typical platforms give, with no card required to start.
Deploy something remarkable.
Your first deployment is minutes away, and it’s on us.