Analyze your GitLab data with AI today.
Build dashboards, automate reports, and ask questions in plain English — all from your GitLab data, no complex infrastructure to maintain.
Have multiple GitLab accounts? Analytics across multiple GitLab accounts →
Want it to watch your GitLab data and act on its own? Meet the GitLab agent →
Everything GitLab exposes, modeled and queryable.
Extracts GitLab project, group, and user data, including issues, merge requests, commits, branches, releases, tags, labels, milestones, CI/CD pipelines and jobs, vulnerabilities, and configuration variables. This enables engineering analytics such as delivery velocity, code review throughput, CI reliability, release cadence, contributor activity, and security posture across projects and groups.
Tables & streams
Organizational container for related projects and members; enables portfolio rollups across teams, cross-project throughput, and program-level governance.
A single repository and workspace for code and work tracking; supports analysis of repository activity, CI/CD health, releases, and contributor engagement at the project level.
Contributors and members with access to groups and projects; enables analysis of author/reviewer workload, activity, and team-level performance segmentation.
Work items tracked in projects; powers backlog health, throughput, and cycle/lead time analyses by label, assignee, and milestone.
Cross-project initiatives grouping related issues (Ultimate); supports program-level progress tracking, scope management, and predictability across teams.
Time-bound goals at the project or group level; used for tracking delivery against plans, burndown, and schedule adherence.
Code change proposals and reviews; enables metrics on review throughput, cycle time, approvals, and merge rates.
Atomic code changes in the repository; supports analysis of commit velocity, code churn, contributor activity, and change volume over time.
CI/CD pipeline executions for a project; used to monitor success rates, durations, and trends in build and deployment reliability.
Individual CI jobs within a pipeline; enables step-level reliability, retry behavior, and bottleneck analysis.
Versioned releases with notes and associated tags; supports analysis of release cadence, change volume, and deployment readiness.
Taxonomy applied to issues and merge requests; enables segmentation of work by type, priority, team, or component for reporting.
Security findings detected in projects; supports risk posture tracking, severity distributions, and remediation throughput.
Uses a GitLab Personal Access Token you create in your GitLab profile to authenticate via the Private-Token header
Requires a GitLab account to connect.
Three steps. One afternoon.
Authenticate GitLab in a few clicks. OAuth, API key, or IAM role — we handle secrets and rotation.
We pull every stream into your warehouse. CDC where the API supports it; full + incremental otherwise. Hourly-or-faster, row-level secure.
SQL, dashboards, or ask Fi in plain English. Your GitLab data lives next to every other source — ready to join.
We'll set up a live sync and answer your first questions — on the call.
Build your own with the Definite SDK, or request it. Most go live in days.
Pair GitLab with the rest of your data.
Join GitLab with the rest of your data, then ask Fi questions across all of it.
