Delivery figures from the pull requests you already have
inline already sees every pull request it reviews and every deploy your repositories record. The metrics page turns that into DORA figures, where the time between a first commit and production goes, how much of the work an AI wrote, and what inline returned for what it cost. Team figures only: nothing is ever broken down by person.
DORA, and the stages
behind each number
Deployment frequency, lead time for changes, change failure rate and time to restore, counted from whichever deploy signal each repository really emits: deployments, workflow runs, releases or pushes. Cycle time splits into coding, pickup, review and merge, so a slower quarter points at the stage that slowed.
What inline returned,
in hours and dollars
Only outcomes your team confirmed count: a finding when it was fixed or accepted, a coding session when its pull request merged. Each is priced in minutes you set and an hourly rate you set, next to every dollar inline spent on AI runs for those repositories.
Included
Related
The review
Line-anchored findings with a severity, a confidence and a validation pass behind them, from a review that reads the code around the diff.
Read moreRepo memory
Outcomes harvested when a pull request closes, house rules with evidence, a profile of each repository and a wiki kept current on every push.
Read moreCoding agents
An MCP server any coding agent can call for a review before the pull request exists, and visual plans a person signs off before the agent writes code.
Read more
See your own numbers
Metrics start from the pull requests inline already reviews, and a backfill reads earlier ones from GitHub so the page has history from day one.