Dev
GitHub
Code collaboration platform hosting Git repositories, pull requests, and CI/CD pipelines for software teams. Roiva syncs merged pull request data and GitHub Copilot usage metrics to measure engineering velocity and AI coding assistant adoption before and after rollout.
What gets synced
Roiva writes these metric observations on each sync. Reference the key in a value formula to use this data in your ROI calculations.
Pull Requests
github.pull_requests.merged_count
Merged PR Count
count
github.pull_requests.cycle_time_avg
Avg Cycle Time (hours)
duration
github.pull_requests.additions_avg
Avg Lines Added per PR
count
Copilot Usage
github.copilot.suggestions_accepted
Suggestions Accepted
count
github.copilot.acceptance_rate
Acceptance Rate (%)
percentage
github.copilot.lines_accepted
Lines of Code Accepted
count
github.copilot.active_users_avg
Avg Daily Active Users
count
Common use cases
- Track merged PR volume and cycle time before and after deploying an AI coding assistant such as Copilot or Cursor
- Measure lines-of-code output per engineer per month as a productivity proxy
- Correlate AI coding tool adoption with repository velocity trends over time
- Use cycle time reduction as the primary ROI signal for AI-assisted development initiatives
How to connect
- In Roiva: Click Connect — you will be redirected to GitHub to install the Roiva GitHub App
- In GitHub: Select the organisation (or personal account) and choose which repositories to grant access to
- Back in Roiva: Your connection is created automatically — PR data and Copilot usage will sync nightly
- Back in Roiva: Link this connection to an initiative on the Initiatives tab
Tips for capturing value
- Grant access to all repositories for the broadest signal; you can scope data per-initiative using the object type selector
- Cycle time (hours from PR open to merge) is the strongest leading indicator of AI coding assistant ROI
- Compare a 3-month baseline period against the 3 months after tool rollout for a clean before/after view
- High additions_avg alongside lower cycle_time_avg suggests engineers are writing more code, faster
- Copilot usage metrics require GitHub Copilot Business or Enterprise on the connected organisation
GitHub
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