Badgr Compute API / Build on Badgr
Build on Badgr
The Badgr dashboard is one way to use Badgr. The Badgr Execution API is how other products build on Badgr: use it as the cloud execution layer behind your own AI product — agents, GPU workloads, and model-serving endpoints — without exposing the Badgr dashboard to your users.
They build the app. Badgr runs the work.
Your product, your UI, your users, your branding, your workflows. Badgr owns execution, compute, runtime limits, retries, recovery, verification, artifacts, and teardown underneath it.
Common architecture
Your users never need to see the Badgr dashboard — Badgr can operate entirely behind your product.
Choose a use case
Coding Agent SaaS
Build a cloud coding agent without building worker infrastructure.
Build this with Badgr →AI Employee / Agent Workspace
Build autonomous workers without operating the execution infrastructure.
Build this with Badgr →Research / Browser Agent
Run long autonomous research and browser work without managing persistent workers.
Build this with Badgr →GPU AI Application
Add GPU execution to your product without operating a GPU fleet.
Build this with Badgr →Model-Serving Product
Offer hosted AI models without building your own serving infrastructure.
Build this with Badgr →One API, many workload types
Every use case above calls the same Jobs API. Here's the Agent Job that a coding-agent product would submit:
POST /v1/jobs
{
"type": "agent",
"input": {
"repository": "https://github.com/acme/payments",
"instruction": "Fix checkout"
},
"policy": {
"max_cost": 2,
"max_runtime_minutes": 20
}
}Other job types (custom.run, model.serve, train.lora, comfy.batch) run on the same underlying execution platform — see /docs/compute-api for the full job type reference.
The mental model
Your product. Your users. Badgr underneath.
OpenAI is an intelligence API. Stripe is payments infrastructure. Badgr is AI execution infrastructure — the cloud that runs the work your product asks for.