Workflows for AI/ML

Buildkite supports non-linear workflows, letting you adjust pipelines at runtime. This means you can optimize compute dynamically by only running what you need for each step in experiments. Automate what you can, and pause execution when you want to inspect the output and decide how to proceed.

1. Robust workflow controls out-of-the-box, including options to block, retry, inspect results, provide inputs, and resume.
2. Right-size compute by matching workflow steps to the appropriate hardware.
3. Auto-scale to 100,000+ concurrent agents.

Buildkite’s hybrid architecture lets you adopt the security posture you need without compromising speed or user experience. With self-hosted agents, you control the build environment, and Buildkite has no access to your models, source code, or secrets.

1. Retain control of your models and data with self-hosted agents.
2. SOC 2 Type II compliant SaaS control plane.
3. Bake in security and environment checks through the pipeline lifecycle.

In an emerging field like AI/ML, moving fast is critical. Buildkite’s cross-platform agent is lightweight and can be used anywhere. Run the agent on the latest hardware as soon as it’s available rather than waiting for a SaaS solution to update.

1. Run agents on any platform or cloud.
2. Quickly experiment with new approaches to get ahead of changes in the field.
3. Update the build environment on your schedule.

With more models on the horizon, Buildkite’s flexible primitives let you consolidate workflows to support efficient delivery across all teams. Easily blend conventional CI/CD practices with research methodologies, and manage disparate workflows with secure boundaries around pipelines, compute, projects, and more.

1. Create a common delivery language to make collaboration smooth between specialties.
2. Pave golden paths so that any team can operationalize their work.
3. Work together to automate the flow of data, code, models, and applications across any compute, workflow, or scale.