A sandbox backend for agent-builder and workflow platforms
Promigence gives agent-builder and workflow platforms a sandbox backend for the code their users' agents run: isolated, ready in milliseconds, billed by the second, and compatible with the sandbox API many platforms already integrate. It fits as a second provider next to the one you have.
Who this is for: Agent-builder, workflow-automation and low-code AI platforms that run user-defined code or agents.
at 200 concurrent, all served
forks in six hours, zero failures
end to end, through the CLI
Three things that are true of almost every team doing this
One provider is a single point of failure
When your only sandbox provider has a bad day, every one of your customers' workflows fails with it.
Your users' code is untrusted
Workflows run code your platform did not write. Each run needs its own isolated sandbox and a network boundary.
Idle workflows still cost money
Workflows wait on models, tools and people. Paying for sandboxes through that wait turns every idle workflow into a bill.
With Promigence underneath
A second provider behind the same API
Promigence works as a drop-in replacement for the sandbox API many platforms already integrate, so it can take traffic next to your current provider.
Isolated runs with network you decide
Every run gets its own isolated sandbox, which can sit behind an outbound allow-list.
Billed by the second, not for the wait
Usage is billed per second, and a sandbox can pause itself when idle. Paused time is not billed.
# Know the most a batch can cost before it runs
promigence run quote --snapshot workflows --count 20
# Run it with a hard cap
promigence run --snapshot workflows --count 20 --cap 2 -- ./run_workflow.sh
Run your own workload on it, free
Send a repo and the command you run against it, whatever that is: an eval suite, an RL rollout, a CI job, a queue of coding tasks. We build the environment once, run it a thousand times, and send back the timings, the failures and an exact price. Free, once, on your real workload.
- 1,000 runs of your own command, on your own repo
- What each one cost in wall clock, and anything that failed
- Whether a failure was your code or the environment
- An exact price for your real volume
Not ready to hand over a repo? Read the quickstart or check the numbers first.