Alpha: analyze and reduce CI build times with Swarmia

If you’ve worked as a developer, you know that waiting for CI builds can be a real pain. In fact, unreliable CI/CD setups can result in hours of waiting time per developer per week. This only gets worse as the organization scales, translating into six-figure losses and weeks of idle time in larger organizations every year.

Today, we’re excited to announce our new alpha feature that helps engineering organizations measure how much time they spend waiting on CI builds and analyze how the situation has changed over time. The new CI insights also help you identify which services and workflows contribute to those waiting times, so you can pinpoint issues and address the root causes.

👉 Join the Swarmia alpha program. As of today, the new CI insights are available to select Swarmia customers using GitHub Actions. To participate, reach out to your customer success manager or contact us directly at hello@swarmia.com.

More updates

  • We’ve added support for canceled issues for both Jira and Linear customers. Now, when you set the issue status as canceled (won’t do, won’t fix, or similar) in your issue tracker, it will be displayed as such in Swarmia. By default, work on canceled issues will still be visible in Swarmia. In issue insights, you can exclude them by applying a filter for issues with a status is not canceled from the filter bar.
  • When you connect Jira to Swarmia, we now automatically map issue statuses, cutting the setup time in half for larger organizations. We also applied the new, automated mapping to all our existing customers.
  • It’s now easier to look back at merged and closed pull requests. In the pull requests view, work is now grouped by date, pull requests are sorted by merge time, and the total cycle time is displayed on the right.

Subscribe to our newsletter

Get the latest product updates and #goodreads delivered to your inbox once a month.

More changelog updates
· Aug 7, 2026

Measure the ROI of your AI coding tools

If you’re paying for AI coding tools, someone will eventually ask what that spend is buying. Until now, answering that question meant stitching together tool invoices, headcount, and delivery data by hand. The new ROI tab in AI impact turns that one-off analysis into a standing view. It shows what…
Read more
· Aug 5, 2026

See where your AI coding tool spend is going [beta]

Every AI coding tool reports usage in its own way: credits in one place, requests in another, raw token counts in a third. None of those add up, which makes it hard to answer two simple questions: what is our AI tool usage actually worth, and where is it going? The new AI cost page answers both. It…
Read more