MATHLAPLATFORM
The Arabic sign language platform

Together, we build a world thatsigns.

Mathla is the home for Arabic and English sign language — collect, review, learn, and grow the community dictionary that powers real-time tools.

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Platform impact in numbers

16,813Sign recordings
577Registered users
15,230Recordings approved by reviewers
41Hours of signing recorded
Partners SwaedUAE Association for Culture and Community Empowerment
The Mathla app

Sign to the camera. Mathla turns it into text and speech.

We are building a model that learns Arabic sign language from real people — every sign the community records makes it better.

  • Live translation from sign to Arabic text and voice
  • Learn everyday signs from a verified dictionary
  • Recorded only with your consent — your data stays yours
An everyday conversation with a phone on the table
Our values

What guides our work

01

Collaborate with Purpose

Build meaningful partnerships that create lasting impact.

02

Advance Education

Expand access to quality sign language education worldwide.

03

Drive Research

Support data-driven research that informs policy and practice.

04

Empower Communities

Strengthen communities through inclusion and shared knowledge.

Our Strategic Framework

The Three Pillars of Mathla

Combining community-driven documentation, professional accessibility services, and cutting-edge sign language AI research.

01
Available Today

Pillar 1: Community & Language

Documentation, Deaf-led validation, and regional governance preserving living Arab sign languages.

  • Deaf-led regional sign collection across Arab states.
  • Expert teacher and community verification workflows.
  • Regional variety preservation & dialect governance.
02
Pilot Phase

Pillar 2: Accessibility Services

Signed content production, custom dataset generation, and institutional accessibility reviews.

  • High-quality signed video production & translation.
  • Tailored dataset collection for organizations & schools.
  • Comprehensive accessibility & sign accuracy audits.
03
Research Lab

Pillar 3: Research & AI

Continuous sign-to-speech models, bounded landmark recognition, and ethical safety fallbacks.

  • Real-time continuous sign-to-text and speech pipelines.
  • Privacy-preserving 3D hand and pose landmark tracking.
  • Safety fallbacks & open signer-disjoint benchmarks.
Sign of the day

2 فبراير

Learn one featured sign from the Mathla dictionary every day.

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Featured campaign

Daily Signs

315/10000 · 3%

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Join us

Every sign you record teaches Mathla to understand more