For NGOs, foundations & development programs
AI-powered coaching for youth-development, workforce development, women's empowerment, workforce-readiness, community-leadership, and reintegration programs.
17% / 7%
Increase in job formality for men / increase in monthly earnings — Juventud y Empleo RCT, Dominican Republic.
Ibarrarán et al., IZA Journal 2014
~50% higher
Earnings vs. control group — Entra 21 program, Argentina. Effects driven by employment persistence, not entry rate.
Card et al., J. Labor Economics 2011
Why iLeader is different
A Jordan RCT found no impact from a 45-hour stand-alone soft-skills workshop. Soft-skills training works best integrated with ongoing practice, goal-tracking, and the broader program — which is exactly how iLeader deploys.
Groh et al., IZA Journal 2016
iLeader outputs designed to fit MEAL frameworks. Skill acquisition, application in context, with indicators donors expect (DFID/FCDO, IDB, EU, World Bank, major foundation templates).
Every deployment is tailored: language, cultural frames, scenarios relevant to the population — agricultural cooperatives, girls in STEM, refugee entrepreneurs, returning migrants.
Per-seat pricing drops as cohort size grows. Budgetable in proposal-writing. Justifiable in implementation.
Identify participants at risk of disengagement before dropout. Spot which cohort elements are working — while you still have time to adjust.
01
Skill acquisition, behavior change, self-efficacy, employment, income, entrepreneurship — measured over time, disaggregated by the dimensions your donors require.
02
Cost per beneficiary, reach, completion rates, engagement — benchmarked against program design targets.
03
Cohort-level patterns, community-level shifts, longitudinal follow-up data — the evidence that attracts the next funding cycle.
We are currently partnered with an international NGO working with returning migrant workers in Nepal. The deployment tests every hard question about AI coaching for development programs at once: does the platform function in Nepali? Does it adapt to Eastern philosophical frames? Does the scenario library reflect what migrant returnees actually face? Can the measurement architecture produce MEAL-compatible outputs?
The deployment is live. Outcome data is being gathered. We'll publish results as they come in.
Read about the Nepal deploymentWe'll size iLeader to your next program cycle, your donor requirements, and your cost targets.