Case study · CS·01
LEAD Academy: career guidance in production.
A guidance system that runs structured career assessments, maps skill gaps, and recommends learning paths from LEAD's own catalog. Paid engagement. Live today.
- Client
- LEAD Academy
- Sector
- EdTech · Bangladesh
- Engagement
- Build and support · fixed scope
- Status
- Paid clientLive
- Stack
- Python · Flask · React · OpenAI · scikit-learn
The problem
LEAD Academy teaches thousands of learners moving into new careers. Guidance did not scale with them: counselors answered the same questions daily, learners waited for replies, and course selection ran on guesswork.
The team wanted guidance inside their own platform, available at any hour, grounded in their actual catalog rather than generic career advice.
What we built
A career guidance system built on retrieval over LEAD's own course and career data. It runs structured assessments, maps a learner's skill gaps against target roles, and recommends specific learning paths from the live catalog.
Answers cite their sources. Questions outside the catalog route to humans instead of producing confident nonsense.
How it deployed
Shipped as a production API with an admin dashboard, integrated into the platform LEAD already runs rather than replacing it. No migration. No new tool for staff to learn.
Thirty days of post-launch support closed the gaps that only real users find.
Results
- Live in production at lead.academy/aicheckable right now
- Paid, fixed-scope engagement delivered on schedulebuild plus 30-day support window
- Handles assessments, skill-gap mapping, and recommendations end to end, at any hourcounselors handle exceptions, not volume
Bring us one workflow.
A diagnostic sprint maps it end to end and tells you what is worth automating. Fixed fee. You keep the map either way.
Book a sprint call