> For the complete documentation index, see [llms.txt](https://docs.loci-dev.net/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.loci-dev.net/ai-binary-analysis-in-your-ci-cd.md).

# AI Binary Analysis in Your CI/CD

LOCI adds AI-based binary analysis to your CI/CD workflow.

It helps teams review performance before issues reach testing or production.

### In this section

* [Ready to integrate in Your CI/CD](/ai-binary-analysis-in-your-ci-cd/ready-to-integrate-in-your-ci-cd.md)
* [GitHub Integration](/ai-binary-analysis-in-your-ci-cd/quick-start-loci-github-integration.md)
* [Azure DevOps Integration](/ai-binary-analysis-in-your-ci-cd/quick-start-loci-azure-devops-integration.md)

Start with the workflow. Then use the GitHub pages for setup and examples.

***

### CI/CD Workflow

LOCI fits into your existing build workflow with two steps.

{% stepper %}
{% step %}

### Upload

Run this step right after your build.

* Upload compiled binaries to the LOCI backend.
* Start analysis immediately.
* Trigger automatic PR comments when the LOCI GitHub App is installed.
  {% endstep %}

{% step %}

### Summary

Run this step when you want results in the workflow UI.

* Wait for analysis to finish.
* Pull results back into the job.
* Show the Agent Report and Function Insights in the workflow summary.
  {% endstep %}
  {% endstepper %}

Use `upload` on every run. Add `summary` when reviewers need results inside GitHub Actions.

***

### CI/CD Benefits

LOCI adds hardware-aware analysis to your pipeline before tests finish.

### What you gain

* **Pre-test analysis** catches performance and hardware interaction issues early.
* **Autonomous optimization** gives concrete suggestions for bottlenecks.
* **Performance gates** help block regressions in pull requests. Gates are defined in your repository's Contract Envelope (`.loci/contract.yaml`) — see [contract](/loci-plugin-for-ai-coding-assistants/loci-claude-plugin/skills-reference-for-loci-claude-plugin.md)

### Where results appear

* In the LOCI backend after upload.
* In the workflow summary when you run `summary`.
* In pull requests and checks when the LOCI GitHub App is installed.

This helps teams catch regressions sooner and review performance in the same flow as code changes.