Page 632 - AI for Good Innovate for Impact

AI for Good Innovate for Impact

2 Use Case Description

2�1 Description

Educational inequity remains a major challenge globally, worsened by limited teacher access
and uneven technological adoption. This threatens progress on enhancing quality education,
reduced inequalities, and decent work and economic growth. QANDA aims to democratize
quality education by offering an affordable, AI-driven personal tutor, improving access, learning
efficiency, and motivation for all students. Combining OCR, large language models (LLMs),
and a RAG pipeline, QANDA provides real-time question-solving, adaptive feedback, and
personalized study plans through a mobile-first platform. QANDA empowers students with
self-directed learning tools, narrowing educational gaps and enabling broader economic and
social inclusion.

Partners

• Technology and Research Partners: Technology partners and investors (Samsung, Google,
Bytedance, Meta) and research institutes (Yonsei University, Arizona State University)
support AI infrastructure, model development, and educational impact research.
• Government and Content Partners: Collaborations with Korean government ministries and
leading publishers drive public school deployments and localized content development.

2�2 Benefits of use case

QANDA provides affordable, AI-powered personalized tutoring, ensuring inclusive and
equitable education opportunities for students regardless of their background.

The platform addresses educational disparities both across countries and within societies,
particularly benefiting underserved and low-income communities

By enhancing access to education, especially in emerging economies, QANDA helps more
students acquire the skills necessary for decent work and sustainable economic growth.

2�3 Future Work

• Expansion of AI Tutor Capabilities Across Learning Behaviours

QANDA is expanding its AI Tutor’s role beyond question-and-answer interactions to cover
the full learning journey. The AI Tutor will actively assist students in notetaking, summarizing
study materials, memorizing key concepts, conducting self-evaluation, and reinforcing mastery
through continuous personalized feedback and guidance.

• Geographic Expansion with Hyperlocal Content Strategy

As education systems differ greatly across regions, QANDA is strengthening its localization
efforts by implementing a hyperlocal content acquisition strategy. Content will be adapted
not only through partnerships with local educational institutions and publishers, but also
dynamically sourced from student and teacher feedback behaviors within the app. This ensures
that QANDA’s AI Tutor delivers culturally relevant, curriculum-aligned support optimized for
each market’s unique educational needs.

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