Otter and Fireflies do not fail at African languages. They discard them. Unknown languages get filtered out as noise or approximated to the nearest English word. Tobiloba Sulaimon, a self-taught developer from Lagos, built AuTrans to transcribe Pidgin, Yoruba, Hausa and Igbo as they were actually spoken. It started as a fix for a meeting the tools could not handle.
Tangible things were said and their machine did not capture that. And I thought that since I am a software developer, maybe I could build something that would solve this problem.
— Tobiloba Sulaimon
Mainstream tools filter unrecognised languages out, or map them onto the nearest English word. The output looks like a transcription failure. It is closer to a design choice, and it is the kind of choice a large company can make for years without anyone internally noticing.
That is the general lesson worth taking from this episode even if you never touch transcription. Find the thing your category's incumbents have classified as an acceptable failure.
We are African first. We are focusing on ourselves first, so I’m trying to solve this problem within Africa first before we move on.
— Tobiloba Sulaimon
This is not positioning. Limited funding cannot cover the continent's language count, so attempting breadth would mean doing all of it badly. The narrowness is what makes the quality possible, and the quality is the entire product.
Everything I know today I learnt on my own. I am a self-taught software developer.
— Tobiloba Sulaimon
HTML, CSS and JavaScript from YouTube after high school. A first paid client build. Then a front-end role at a game studio where being the only developer meant learning fast or shipping nothing. The first version of AuTrans took about a week.
With a team and outside consulting, he now rolls features out step by step and turns down most requests, so AuTrans does not become a jack of all trades. Jeremy anchors the same lesson in Raven Tools, which expanded horizontally until it was competing with everyone and beating no one.
Around one hundred users and the first paying customers at the time of recording, with mobile apps, more languages and API access on the roadmap.
| Time | What happens |
|---|---|
| 00:22 | Transcription that understands Yoruba and Igbo |
| 02:07 | The engine that keeps every language as spoken |
| 03:39 | Why so much of the ML world flows through English |
| 05:54 | The origin story: a meeting the tools could not transcribe |
| 08:00 | From personal tool to public SaaS, African first |
| 10:49 | The scope-creep trap |
| 12:15 | Jeremy's Raven Tools cautionary tale |
| 14:37 | Self-taught from Lagos |
| 23:39 | Building the first version in a weekend |
| Entity | What it is |
|---|---|
| AuTrans | AI transcription optimised for African voices, keeping Pidgin, Yoruba, Hausa and Igbo as spoken |
| Otter, Fireflies | Named incumbents that treat non-English African-language audio as noise |
| Immanuel Abraham | His mentor, a backend engineer with ten years of experience |
| Raven Tools | Jeremy's counterexample of a product that over-expanded horizontally |
| Vertical versus horizontal scoping | The through-line: depth in one market against breadth across many |
Every link above goes somewhere different. These are the ones not already mentioned above.
Sulaimon, Tobiloba. Interviewed by Jeremy Rivera. “Africa First.” Unscripted SaaS, 2026. https://unscriptedsaas.com/africa-first-tobiloba-sulaimon-on-focus/
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