Local-first CI / client preview
Your compute.
Your pipelines.A smaller bill.
Put the capacity you already own to work. We’re building a managed path from customer-owned workers to cloud overflow, with the economics out in the open.
Product preview. Savings are workload-dependent. No benchmark claims without evidence.
Company hardware · warm build cache
Resource limits · eligible workloads only
Overflow capacity · approved budget
Dedicated workers first. Workstations by choice.
Designed around the official GitHub runner.
Separate models, measurements, and targets.
The idea
The best cloud minute might be the one you never buy.
There is more to a CI bill than the price per minute. Repeated setup, cold caches, unused capacity, and retries all count. Our design starts there.
Keep the useful state.
Preserve dependency downloads and build caches near the worker. Start each job in a clean environment, without starting every build from nothing.
Read the cache designUse what you already have.
Make company-owned machines a managed worker pool. Reserve headroom so CI does not take over the machine someone needs to do their job.
Understand worker placementGive the cloud a clear job.
Use approved cloud capacity for overflow and workloads that cannot run locally. A deadline, a trust boundary, and a budget should guide the decision.
See the methodologyA different kind of claim
A model is not a benchmark.
We publish the difference.
Inspect the break-even argument, change the assumptions, and see when local execution costs more. Comparative runner measurements have not been published yet.
Open the evidence registerBuilt for the right workload
Start with a team.
And a real baseline.
The strongest candidate is a private-repository team with a meaningful CI bill, repetitive builds, and spare company hardware. A tiny workload inside a free allowance may already have the better deal.
Start with your actual workload.
Explore the model, then apply for a scoped pilot. No card or compute commitment.