Adaptive Learning Path Engine

Close the skill gaps your surveys never found.

Tunlai reads your codebase, pull requests, and incident data to build personalized upskilling paths. No guesswork. No surveys. Just signal from where engineers actually work.

3 engineering teams already closing real gaps
Abstract amber node-graph on deep ink background representing skill competency mapping
~34% faster
time-to-proficiency for new engineers
~2.1x more
relevant skill paths vs. survey-based methods
~87% match
to actual incident patterns in your codebase
Connects with
GitHub
GitLab
Jira
Confluence
Slack
PagerDuty
Why Tunlai

Most L&D tools ask engineers what they want to learn. We read what your codebase actually needs.

Survey-based skill assessments reflect how engineers perceive their abilities — not where the real gaps are. Tunlai ingests your actual workflow data to surface what matters.

See the mechanism
Survey-based Signal-based (Tunlai)
Engineers self-report skills Observed from PR patterns & incidents
Runs once a year Continuously updated from live data
Confident areas overreported Blind spots surface automatically
Generic content catalog Path tailored to your actual codebase
L&D guesses what engineers need Engineering VP sees the data directly
The Platform

Three engines. One coherent picture of your team's skills.

From raw codebase signal to personalized paths, every layer works together.

Competency Graph

A live map of what your codebase demands and how each engineer measures against it. Built from PRs, reviews, and incident data — not self-assessments.

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Path Engine

Generates personalized learning sequences for each engineer based on their current proficiency, your codebase's requirements, and real incident patterns.

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Skill Gap Analytics

Team-level and individual dashboards that give Engineering VPs and L&D managers a shared view of skill coverage, risk areas, and upskilling progress.

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Integrations

Plugs into the tools your team already uses.

Read-only OAuth connections. No code stored. Setup in under 30 minutes.

GitHub
PR reviews, code patterns, commit history
GitLab
Merge requests, pipeline signals, review patterns
Jira
Ticket patterns, skill distribution, escalation chains
Confluence
Documentation coverage, knowledge gaps
Slack
Help-seeking patterns, knowledge flow signals
PagerDuty
Incident signals, on-call patterns, skill risk mapping
See all integrations
We ran surveys for years and thought we knew where our engineers were struggling. Tunlai showed us three skill gaps we'd never have found otherwise — all confirmed by two P1 incidents in the last quarter.

Director of Engineering, Financial infrastructure company

Ready to build learning paths from real data?

Connect your codebase and see your first competency graph in days, not weeks.