Reusable Agent Pipelines

Langbase lets teams assemble an AI agent from smaller, reusable building blocks, such as a prompt step and a data lookup step, rather than writing one large program. A Beam agent reads a request from a connected application, matches it to the approved pipeline for that task, and calls Langbase to run it with the supplied input. It records the pipeline's output against the original request so results can be traced. A request to change which pipeline steps run, or to add a new step, is routed to a human before the pipeline is edited.

Serverless Endpoint Deployment

Langbase runs deployed agent pipelines as serverless endpoints, so a team does not have to manage its own servers to keep an agent available. A Beam agent reads a completed pipeline configuration a team has approved and deploys it to Langbase, then checks that the resulting endpoint responds correctly before marking it live. It notifies the team once the endpoint is reachable. Deployments that fail their initial check, or that would replace an endpoint already serving live traffic, are routed to a human rather than retried automatically.

Version and Rollback Control

Langbase keeps a history of each pipeline's previous versions, so a team can return to an earlier one if a change causes problems. A Beam agent reads the deployment history on request, applies the approved version a team wants restored, and rolls the endpoint back to it in Langbase. It records which version is now live against the pipeline so the change is easy to trace later. A rollback that would affect an endpoint currently handling a high volume of requests is routed to a human to confirm timing first.