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Good practice Imported

Terp 360 — Signvrse's AI Sign-Language Avatar for Kenya's Deaf Community

Kenya · Nairobi · See the Kenya profile · See the Nairobi profile

Evidence: Descriptive / self-reported Top 32% 80/100 · Ask Evidence Copilot about this practice

Nairobi startup Signvrse built Terp 360, an AI-driven 3D avatar that translates English speech and text into Kenyan Sign Language in real time, trained on 20,000+ motion-captured signs validated by Deaf Kenyans and tested with over 2,000 Deaf users across Kenya and Uganda.

2,000+
Deaf/hard-of-hearing users engaged for testing (2025 beta)
20,000+
Sign sequences in the training dataset
~35 %
Reduction in processing time from pre-computed sign combinations
2.7 million
Estimated Deaf/hard-of-hearing people in Kenya
Terp 360 — Signvrse's AI Sign-Language Avatar for Kenya's Deaf Community

Details

Maturity
Pilot
Promoter
Signvrse
Period
{'end': '', 'start': '2023-01-01'}
Keywords
assistive technology, artificial intelligence, sign language, disability inclusion, edtech

Context

Kenya has an estimated 2.7 million Deaf and hard-of-hearing people, yet African countries have as few as 40-700 certified sign-language interpreters between them. Founded in Nairobi in 2023 by engineer Elly Savatia, Signvrse built Terp 360, which uses motion-captured Kenyan Sign Language (KSL) recordings layered with a generative-AI translation model to render spoken or typed English as a photorealistic 3D avatar signing in real time.

Activities

The training dataset -- more than 20,000 professionally captured sign sequences from signers in both urban and rural Kenya -- was built and validated in direct collaboration with Deaf community members, sign linguists and AI engineers; pre-computed sign combinations cut processing time by roughly 35%. Early prototypes built on basic Unity animation produced stiff, robotic motion that Deaf testers found hard to read, so the team rebuilt the animation pipeline for more natural, fluid signing.

Results

As of its 2025 beta, the web-based platform had engaged more than 2,000 Deaf and hard-of-hearing users for testing across Kenya and Uganda, and the company opened a second office in Rwanda to pilot classroom and public-service deployments. Signvrse has been backed by $10,000 grants each from UNICEF and the We Are Family Foundation, and was one of 21 organisations selected for Google.org's 2024 Generative AI Accelerator.

Conclusions

Independent, peer-reviewed evaluation of translation accuracy has not yet been published, and Terp 360 remains one-directional (spoken/written language to sign, not sign to speech), so it does not yet replace two-way human interpretation.

Implementation

Indicative cost
Medium (€50k–€500k) — Backed by $10,000 grants each from UNICEF and the We Are Family Foundation, plus Google.org Generative AI Accelerator support; plans a B2B SaaS licensing model from Q4 2025.
Time to results
Medium (1–3 years) — Founded 2023 in Nairobi; 2025 beta tested with 2,000+ users; a Rwanda office opened for further piloting.
Staffing & skills
Founding engineer Elly Savatia and technical team, Kenyan Sign Language (KSL) motion-capture signers, Deaf community members and sign linguists as design/validation partners

Conditions for success

  • Direct collaboration with Deaf community members and sign linguists in building and validating the training dataset
  • Iterating the animation pipeline based on Deaf-tester feedback
  • External grant/accelerator funding to sustain development (UNICEF, We Are Family Foundation, Google.org)

Common failure modes

  • Early Unity-based animation prototypes were too stiff and robotic for Deaf testers to read
  • Currently one-directional only (spoken/written to sign, not sign to speech), so it does not replace two-way human interpretation

Where it fits

Governance type
private startup
Scale
pilot/beta, multi-country (Kenya, Uganda, expanding to Rwanda)
Income level
lower-middle-income

Commonly funded by

Philanthropic / foundation funding

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Data sources

Where this practice's information was retrieved from, and when.

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