Communication is a human right. We're engineering it.
Fahan is a real-time AI voice interpreter built to eliminate language barriers for the Somali diaspora — starting with healthcare, education, and the moments where miscommunication has real consequences.
While legacy translation software focuses on dominant languages, Fahan was engineered from the ground up with a Somali-first approach. Millions of Somali speakers across the global diaspora are systematically underserved by mainstream technology — Fahan exists to directly close that communication gap.
Our core philosophy is simple: clear communication should be unhindered by the language someone speaks. Whether navigating an emergency room, a parent-teacher conference, a customer service interaction, or a deep intergenerational conversation within a multilingual household, Fahan removes friction, isolation, and anxiety through contextually aware voice translation technology.
Mohamud Abdi
Founder & Software Developer
The story behind Fahan
Growing up deeply connected to immigrant communities, Mohamud witnessed firsthand the daily challenges born from language exclusion. Families navigating vital civic infrastructure were routinely forced to rely on bilingual relatives — and often young children — to translate complex, highly confidential medical conversations or legal documents.
In school districts, non-English speaking parents found themselves locked out of conversations about their children's development. Everyday interactions, from retail checkouts to leasing offices, turned into points of profound stress and social isolation.
Fahan was born from this reality — not from a market analysis, but from years of personal experience navigating the gap between two languages, two cultures, and two worlds.
Education & Experience
Academic Foundation
B.A. Computer Science
University of Missouri–Kansas City, School of Computing and Engineering
Advanced software engineering, systems architecture, algorithm optimization, scalable infrastructure
A.S. Internet & Web Technologies
Ranken Technical College
Web deployment, database management, network engineering, UI/UX design
Enterprise Experience
Accenture
Technology Architecture Analyst & Business Analyst
- Translating client requirements into development roadmaps
- Optimizing enterprise system workflows and data pipelines
- Managing end-to-end QA and testing frameworks
- Bridging communication between architects and end-users
The Low-Resource Language Bias
Despite massive breakthroughs in artificial intelligence, mainstream corporations continue to relegate Somali to "low-resource" status. The result is technology that fails the communities that need it most.
Inaccurate context matching and frequent AI hallucinations
Robotic, unnatural speech synthesis
High latency and failure rates in live speech recognition
Systematic misclassification of Somali as Arabic
Fahan was engineered to break this cycle.
How Fahan Works Under the Hood
Users tap a single button, place their device between both parties, and speak naturally. Fahan handles language detection, converts speech to text, processes semantic intent, and plays translated audio in fractions of a second.
Where Fahan Makes a Difference
Ready to break the language barrier?
Download Fahan and start communicating — in real time, in your language.