Skip to content
System build

An end-to-end mentorship platform connecting women across Africa's investment industry, live in multiple markets.

Client
Mastercard Africa Growth Fund, AFIG Funds
Industry
Development finance
Location
Pan-African
Problem

The Mastercard Foundation wanted to connect women across Africa's investment industry with mentors, and no off-the-shelf platform could match, manage, and measure those relationships across multiple markets. Run with AFIG Funds as the Mastercard Africa Growth Fund, the programme needed a platform built for its own mechanics rather than adapted to them.

What was built

The system.

  1. 01

    Matching engine

    AI-driven mentor-mentee matching, with goal frameworks that structure each relationship.

  2. 02

    Programme operations

    Relationship lifecycle management, in-platform messaging, and calendar integration.

  3. 03

    Programme analytics

    Programme-wide analytics and audit trails for administrators measuring outcomes across markets.

In the product
The programme team’s console
Programme analytics: users per country and per type across markets, with mentorship filters and AI-match export.
Matching, the part that had to be defensible: every candidate mentor carries two scores — an automatic one and an AI one — and the reasoning is written out in full before an administrator confirms or declines. The mentee's contact details are masked here.
What a participant sees
A mentee’s home. The passed session asks to be confirmed, its tasks are split into before, during and after, and the plan runs alongside with the next session already scheduled.
A training session after the fact — speaker and bio, the agenda, and the recording — with attendance confirmed by the participant rather than assumed.
Mentor and mentee message inside the platform, attachments included, so the relationship and its record stay in the programme rather than moving to private email.
The community feed, where participants post opportunities and resources to the wider cohort — the part of the programme that outlives any one pairing.
1 / 6
The Womentor programme-analytics dashboard: users per country and per type, with mentorship filters and AI-match export

Programme analytics: users per country and per type across markets, with mentorship filters and AI-match export.

Outcome

What changed.

In production across multiple African markets
LIVEIn production across multiple African markets

deployed and running for the programme rather than held as a pilot build.

Person team in Ethiopia (avg. age 29), ideation through launch
12Person team in Ethiopia (avg. age 29), ideation through launch

one accountable vendor carrying the platform from first wireframe to production.

Active users in the pilot phase
100+Active users in the pilot phase

within the first 2 months.

Over the past six months, the Zare team has demonstrated exceptional commitment, quality, and thoughtfulness. The final product received overwhelmingly positive feedback, with very few change requests — a true reflection of the team's excellence and hard work. I'm incredibly proud of what we've built together and excited to carry this momentum forward.
Mastercard Africa Growth FundWomentor AfricaClient feedback, six months into the engagement
Related workAll work →