> ## Documentation Index
> Fetch the complete documentation index at: https://afri-health-ai.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# About ETH-1713-AI, the Team Behind AfriHealth AI

> Meet ETH-1713-AI, the Ethiopian company building AfriHealth AI, a clinician-reviewed voice documentation suite, and the team leading its clinical and AI work.

AfriHealth AI is built by **ETH-1713-AI**, a company focused on making clinical speech easier to document for multilingual care teams in Africa. Our first product turns Amharic-English code-switched conversations into draft clinical records that clinicians review and approve.

## Our mission

Make clinical speech easier to document, never harder to verify. Every output AfriHealth AI produces is a draft for a qualified clinician, so care teams save time without giving up control.

<CardGroup cols={3}>
  <Card title="Local languages" icon="language">
    Built for Amharic-English today, with Afaan Oromoo and Tigrinya on the roadmap.
  </Card>

  <Card title="Clinician first" icon="user-doctor">
    Human review and sign-off are built into every workflow.
  </Card>

  <Card title="Transparent evidence" icon="chart-line">
    We publish measured accuracy results and their limitations.
  </Card>
</CardGroup>

## Leadership and team

<CardGroup cols={2}>
  <Card title="Ermias Amare" icon="user-tie">
    Co-founder and CEO. Project Manager and Architecture Lead.
  </Card>

  <Card title="Melaku Bayu" icon="brain">
    AI and ML Research.
  </Card>

  <Card title="Hiwot Shiwangezaw" icon="stethoscope">
    Clinical Team.
  </Card>

  <Card title="Rahel Tamiru" icon="stethoscope">
    Clinical Team.
  </Card>

  <Card title="Fasil Bazazew" icon="code">
    Software Engineer.
  </Card>
</CardGroup>

## Get in touch

Interested in a pilot, partnership, or research collaboration? See [Contact](/company/contact).


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