The problem we solve
- 70%
- of global maternal deaths occur in sub-Saharan Africa (WHO, 2023)
- 218M
- women in LMICs with unmet need for modern contraception (Bearak et al., 2020)
- 35%+
- 12-month contraceptive discontinuation rate in Kenya (KDHS, 2022)
Health literacy gaps and circulating misinformation shape method choice long before a clinical conversation happens. Women arrive with fears about fertility, bleeding, and side effects that no leaflet has addressed, and often abandon a method rather than ask.
Community health workers carry the counselling load with no decision support at the point of contact. Eligibility screening against WHO criteria is done from memory, under time pressure, with paper registers and no way to check an edge case in the moment.
Digital family planning tools assume a smartphone and a data bundle. The women with the highest unmet need are reachable on basic handsets, in local languages, on channels that work offline. Most platforms simply do not reach them.
Why now
Mobile reach in Kenya is high, but reliable contraceptive counselling at the point of contact is not. Health workers need decision support that works on basic phones, respects WHO criteria under time pressure, and keeps a clinician in the loop. ChaguoAI is a field-ready prototype built on local data — ready to instrument with county partners.
Trust & safety
- Not a prescribing tool. ChaguoAI supports counselling; community health workers confirm every client choice.
- WHO MEC first. Eligibility rules are deterministic and always run before generated language.
- Privacy. Programme data is handled under partner agreements; we publish aggregate methods, not identifiable client records.
- Human oversight. Machine learning annotates risk in advisory mode only during piloting — it does not override clinical rules.