The engine under every path.
Three interconnected engines — Competency Graph, Path Engine, and Skill Gap Analytics — each powered by your live engineering data and each informing the others.
Competency Graph
A living model of what your codebase actually demands — and where each engineer's proficiency sits against that demand. Built continuously from PR review comment patterns, incident involvement records, commit surface area, and documentation contribution history. Skill nodes map to the domains your codebase operates in — not a generic skills taxonomy. Not a spreadsheet. Not a survey. A competency framework derived from observed behavior.
Path Engine
Takes the Competency Graph and generates a ranked learning sequence for each engineer — ordered by urgency, not alphabetically by topic. Gaps that correlate with recent incident postmortems surface first. Gaps relevant to active project work surface next. The path reranks automatically as new signals arrive. Tunlai is not a content library: paths connect to the learning resources your team already uses, so you're not replacing Pluralsight or O'Reilly — you're directing them more precisely.
Skill Gap Analytics
A shared dashboard for Engineering VPs and L&D managers. Team-level skill coverage by domain, individual path progress, incident-linked gaps identified vs. closed, and DORA-aligned metrics showing where proficiency bottlenecks affect delivery. One view. No spreadsheet hand-off between engineering and L&D.
See it working on your data.
Connect your first integration and see your team's competency graph in days.