KLCI's Rafiki AI is a free WhatsApp generative-AI career advisor built on Amazon Bedrock; it grew from 1,200 users in its first 3 days to 9,339 users in 60 countries within 9 months, delivering ~40,000 career guidance queries to underserved and displaced youth.
1,200
Users, first 3 days (April 2025)
9,339
Users, 9 months after launch (9 months post-launch)
60+
Countries reached
~40,000
Career guidance queries delivered
82,500+
Messages exchanged
51,000 USD
AWS cloud credits received
767,300 USD
Self-estimated monetary value created
Details
Maturity
Scaling
Promoter
Kayode Alabi Leadership and Career Initiative (KLCI)
Period
April 2025 – present
Keywords
career guidance, youth employment, digital inclusion, generative AI
Context
Youth unemployment and underemployment are acute across much of Africa, and formal career-guidance counsellors are scarce in low-income and displaced communities. The Kayode Alabi Leadership and Career Initiative (KLCI), a Lagos-based nonprofit founded in 2017, built Rafiki AI to put career guidance directly into a channel young people already use: WhatsApp.
Objectives
Launched in April 2025, Rafiki AI walks each user through KLCI's Interest, Strength, Limitation and Purpose (ISLP) framework in a WhatsApp conversation, producing a personalised career pathway in under two minutes, and remains free to use.
Activities
Rafiki AI runs on Amazon Bedrock, with Amazon Transcribe and Polly for voice input/output. Development was supported by roughly $51,000 in AWS Education Equity Initiative cloud credits. In February 2026 KLCI launched 'Rafiki X', a web extension adding CV feedback, application-story generation and conversation memory.
Results
Reach scaled quickly: 1,200 users across 22 countries within 3 days of launch, growing to 9,339 users across 60+ countries nine months later, with close to 40,000 career queries and over 82,500 messages exchanged. About 90% of users are in Nigeria, but the service has also reached refugee settlements and rural communities in Kenya, Zimbabwe, Yemen and beyond, in more than 50 languages.
Conclusions
The available public evidence is usage and engagement data, not an independent outcomes evaluation: there is no published data yet on whether Rafiki AI users go on to secure jobs, training or income gains at higher rates than non-users, and KLCI's own estimates of monetary value created are self-reported modelled projections rather than measured results.
Implementation
Indicative cost
Low (< €50k)
Time to results
Short (< 1 year)
Staffing & skills
KLCI (Kayode Alabi Leadership and Career Initiative) team, AWS technical partnership (Bedrock, Transcribe, Polly)
Conditions for success
Delivery via WhatsApp, a channel young people already use, minimising adoption friction
AWS Education Equity Initiative cloud credits (~$51,000) lowering development cost
Free core service with an optional $2/month subscription for premium features
Common failure modes
No published data yet on whether users secure jobs, training or income gains at higher rates than non-users
KLCI's monetary-value estimates are self-reported modelled projections, not measured results
No disclosed data-retention, consent or model-safety policy for personal career and life-circumstance data
Commonly funded by
Philanthropic / foundation funding
Indicative funding routes for practices of this type — always check each programme's current calls and eligibility rules.
Do you run this practice?
Claim it —
verified implementers get a public contact pathway and can propose corrections.
Data sources
Where this practice's information was retrieved from, and when.