Education · AI tutoring

Uwera.

Uwera gives TVET students an AI tutor grounded in their curriculum, with study conversations, module context, and a library of learning resources. Teachers and academic assistants use a dedicated workspace to create and review assessments, analyze student performance, plan AI-assisted sessions, and tailor coaching.

Visit Uwera

What the product needs to handle

Students need an AI tutor with curriculum context. Teachers and academic assistants also need practical ways to assess progress and plan support. Uwera connects these learning workflows so tutoring and teaching tools share the same student and course context.

Engineering & my role

Students can choose a module, ask questions, attach study material, and use speech tools with an AI tutor grounded in the TVET curriculum. Teachers and academic assistants have a dedicated portal for building assessments, reviewing submissions, analyzing performance, and planning AI-assisted sessions. The platform connects a Next.js interface to Spring Boot services for identity, profiles, and curriculum, with Python services handling AI conversations and generated learning material. I work across the frontend and backend as a full-stack developer.

Inside Uwera.

5 views of the product and its workflows. Open any screenshot to see it at full size.

Study workspace. Students can ask the tutor questions, attach files, or use voice input. Select to open full size.

Curriculum context. Module selection connects the tutoring session to the student's TVET subjects. Select to open full size.

Assessment workflow. The new-assessments list shows the module, issue date, and entry point for each available assessment. Select to open full size.

Learning library. Generated quizzes, flashcards, summaries, and videos stay available for later study, with filters by resource type. Select to open full size.

Public product introduction. Uwera explains its learning tools to students and educators before they sign in. Select to open full size.