Recognitions

Recognitions

DSNai 1
At EqualyzAI, our work has garnered attention beyond the African continent, earning recognition from global research communities, technology leaders, and advocacy groups for our groundbreaking efforts in building inclusive AI. Our commitment to developing models trained on African languages and cultural contexts has positioned us as a leading voice in the global conversation about ethical and equitable AI development.

We have been featured in prominent international forums, academic journals, and AI consortiums focused on low-resource languages and responsible AI. Our partnerships with global institutions, universities, and AI research labs underscore the importance of our mission and validate the impact of our work in pushing the boundaries of multilingual and culturally-aware AI technologies.

Here are some of

Our Recognitions

Global Grand Challenge in 2023 funded by the Gates Foundation

for our work in AI for education delivery, leveraging video diffusion and LLMs to generate curriculum-based and nuanced STEM learning videos for rural students, which are personalized based on learners’ context, spoken language, and learning progress.

DSNai 2

Global Grand Challenge in 2023 funded by the Gates Foundation

for our work in AI for education delivery, leveraging video diffusion and LLMs to generate curriculum-based and nuanced STEM learning videos for rural students, which are personalized based on learners’ context, spoken language, and learning progress.

DSNai 2

Global Grand Challenge in 2023 funded by the Gates Foundation

for our work in AI for education delivery, leveraging video diffusion and LLMs to generate curriculum-based and nuanced STEM learning videos for rural students, which are personalized based on learners’ context, spoken language, and learning progress.

DSNai 2

Global Grand Challenge in 2023 funded by the Gates Foundation

for our work in AI for education delivery, leveraging video diffusion and LLMs to generate curriculum-based and nuanced STEM learning videos for rural students, which are personalized based on learners’ context, spoken language, and learning progress.

DSNai 2