Education · AI
An educational application that validates student answers with OpenAI and Gemini and recommends practice based on past performance.
Project profile
The challenge
Students need timely feedback and practice that responds to what they understand, while teachers need technology that supports rather than obscures the learning process. Answer checking also needed more resilience than depending on a single model response.
The solution
The learning application combines model-assisted answer validation with a recommendation layer that considers each student’s previous performance. OpenAI and Gemini are used in the validation workflow, while the product adapts practice as the learner progresses.
What was delivered
Business outcome
Students receive immediate, contextual feedback and a practice path shaped by their progress. Tutors retain an educational product designed around learning activity rather than a generic chatbot experience.
Related capability
End-to-end development of custom AI-enabled web and SaaS products, including product design, AI integration, cloud deployment and iteration.
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