Students learn by video with a real human tutor. From the session transcript, AI drafts a review and family recap; the tutor corrects and approves them before release.
The workflow starts with a transcript of a human-led video lesson. The demo uses a fictional transcript. Video calling, recording, uploads and automatic transcription are planned integrations, not connected demo features.
After the session, AI proposes observations supported by specific exchanges. It separates independent student work from tutor assistance and flags missing evidence for the tutor’s judgment.
Minutes after class, the AI drafts the next-session plan and a bilingual family recap. The educator can edit, correct, approve, or reject the draft before anything is released.
We did not bolt AI onto tutoring. We rebuilt tutoring around it, with multiple AI systems that run on every session and keep working after the tutor logs off.
AI listens to the full session, aligns speech to curriculum objectives, and tags every moment of learning, struggle, and breakthrough.
AI suggests transcript-supported findings and next steps for tutor review. A brief session does not establish lasting mastery.
AI drafts the plan and recap. An educator edits, corrects, approves, or rejects every release.
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