Fambai CV: Using Gemma 4 to Help African Job Seekers Beat ATS Systems

Priviledge Kurura — Sat, 16 May 2026 01:32:22 +0000

This is a submission for the Gemma 4 Challenge: Build with
Gemma 4

What I Built

Fambai CV — an AI-powered, ATS-optimized CV builder and
job platform built for African job seekers.

The African job market is brutal. Most CVs never make it past
automated screening systems. Job seekers in Zimbabwe and across
Africa don't have access to expensive career coaches or
professional CV writers. I built Fambai CV to close that gap.

With Gemma 4 integrated at the core, Fambai CV now offers:

Real-time ATS keyword analysis — paste a job description, get instant feedback on how well your CV matches
Auto-generated professional summaries — tailored to the role, not generic filler
Smart CV scoring — identifies weak sections before you apply
Job listings — real opportunities via JSearch API with intelligent matching

1,000+ downloads on Google Play. 4.4-star rating. Built by one
person, for millions who need it.

Demo

Google Play Store

Live Web App / Landing Page

Code

GitHub Repository

The ATS analyzer backend is built with FastAPI + Python, deployed
on Railway via Docker. The Flutter mobile app handles the frontend
with Firebase for auth and storage.

How I Used Gemma 4

I chose Gemma 4 E4B — the efficient 4-billion parameter model
— for a specific reason: I needed powerful language understanding
that could run fast enough to give users real-time feedback without
burning through API costs that would price out my African user base.

Gemma 4 E4B powers the ATS Keyword Analyzer feature. When a user
pastes a job description, the model:

Extracts the key skills, qualifications, and action verbs the employer is screening for
Compares them against the user's CV content
Returns a match score with specific, actionable suggestions

The model's instruction-following capability is sharp enough to
return structured JSON that maps directly into the Flutter UI —
no post-processing hacks needed.

For a solo founder building for users who can't afford to waste
a single application on a bad CV, Gemma 4 E4B was the right
balance of intelligence and efficiency. It's fast, it's accurate,
and it respects the constraints of building for emerging markets.

This is what AI should do — level the playing field.

What are you using to create a CV