evidoria

← Back to browse

Good practice Imported

Wasel — Egypt's Arabic Sign-Language AI Chatbot for Deaf and Hard-of-Hearing Citizens

Egypt · Cairo · See the Egypt profile · See the Cairo profile

Evidence: Descriptive / self-reported Top 68% 56/100 · Ask Evidence Copilot about this practice

An AI chatbot converting spoken/written Arabic into Arabic Sign Language video, letting deaf and hard-of-hearing Egyptians access health and government information hands-free. Billed as the first such chatbot in Africa/MENA; UNDP reports over 25,000 users.

25,000+ beneficiaries
Beneficiaries reached (cumulative, as of reporting)
Wasel — Egypt's Arabic Sign-Language AI Chatbot for Deaf and Hard-of-Hearing Citizens

Details

Maturity
Established
Promoter
UNDP Egypt & Egypt's Ministry of Communications and Information Technology (MCIT), with Avaya
Period
2019–present
Keywords
assistive technology, sign language AI, disability inclusion, e-government accessibility

Context

Egypt is home to an estimated 7 million people with disabilities, and deaf and hard-of-hearing citizens have historically faced barriers to accessing public health guidance and government information, a gap made acute during the COVID-19 pandemic.

Objectives

Wasel ('connected' in Arabic) is an AI-driven chatbot developed by UNDP Egypt together with the Ministry of Communications and Information Technology (MCIT) and technology partner Avaya, converting spoken or typed Arabic into video-based Arabic Sign Language delivered by an on-screen presenter, with subtitles so hearing users can follow along too.

Activities

It launched first as a COVID-19 symptom-checking tool aligned with WHO and Ministry of Health protocols, then broadened to general accessible-service queries; it is hosted on Egypt's official accessible-services platform, Tamkeen, and distributed as apps on Google Play and the Apple App Store.

Results

UNDP Egypt reports the chatbot has reached over 25,000 beneficiaries, and both UNDP and independent tech press describe it as the first Arabic sign-language chatbot technology deployed in Africa and the Middle East.

Conclusions

The reach figure and 'first in region' claim currently rest on UNDP's own reporting rather than an independent third-party audit, and UNDP's own materials give inconsistent launch dates (2019–2021) — the underlying service and its continued availability are well documented, but precise metrics should be read as UNDP's self-reported figures.

Implementation
Indicative cost
Medium (€50k–€500k) — Development combined UNDP programme funding, government platform integration (Tamkeen) and a private technology partner (Avaya) providing the underlying AI/chatbot infrastructure.
Time to results
Long (> 3 years) — UNDP's own materials place the launch inconsistently between 2019 and 2021, initially as a COVID-19 symptom checker before broadening to general accessible-service queries; the service remains live as of the most recent reporting.
Staffing & skills
UNDP Egypt, Egypt's Ministry of Communications and Information Technology (MCIT), Avaya (technology partner)

Conditions for success

  • Multi-partner collaboration between a UN development agency, a national ministry and a technology vendor
  • Integration with Egypt's official accessible-services platform (Tamkeen) and native apps on Google Play and the App Store
  • Alignment with WHO and Ministry of Health protocols for the initial COVID-19 symptom-checking use case, giving it an early, high-relevance entry point

Common failure modes

  • Reach figure and 'first in region' claim rest on UNDP's own reporting without independent third-party audit
  • UNDP's own materials give inconsistent launch dates (2019–2021), indicating documentation gaps

Where it fits

Governance type
UN agency and national government ministry partnership with a private technology vendor
Scale
national
Income level
lower-middle-income

Do you run this practice? Claim it — verified implementers get a public contact pathway and can propose corrections.

Data sources

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

Attachments

Similar practices you may find useful