Africa’s languages carry distinct accents, idioms and cultural references. Even within one country, these vary between communities. Speech models often miss those differences, leaving customers to repeat a name, explain an expression or switch languages to be understood.
Ekogenie brings together speech recognition, voice generation and conversational models, grounded in data and evaluation from the communities each model serves. Our founders combine machine learning and production engineering.
Our first focus is Nigerian English and Pidgin, Yorùbá and Igbo, including how speakers move between them. We aim to extend that work across the continent, building for each language and community on its own terms.
Co-founder & CEO
Munachi brings engineering experience across Microsoft, LinkedIn, DoorDash and Brex, alongside building commercial software products. His work connects machine learning with the infrastructure and reliability needed to put it into everyday use.
Co-founder & CTO
Ibukun combines graduate training in Electrical and Computer Engineering at the University of Waterloo with machine learning engineering experience at BFN.
Discuss outbound sales, customer support and intake in the languages your customers speak.
Talk to our team