Engageli AI

Engageli AI is the tutoring and assistance toolkit inside Engageli's virtual classroom. It generates knowledge checks from class materials, summarizes chat, records structured notes, and supports learners between live sessions, with engagement analytics attached to every interaction.

Engageli AI is the tutoring and assistance layer inside Engageli, a virtual classroom platform built for live and asynchronous teaching rather than for meetings. The environment is organized around collaborative tables where small groups work together, and the AI runs alongside that structure: it produces knowledge checks from shared materials and class discussion in real time, condenses fast-moving chat into themes that need attention, and captures structured notes instructors can review later. Adaptive tutoring extends support to learners between sessions, so the classroom stays active after the live hour ends. The product is aimed at institutions and training teams: K-12 schools that need structured classroom controls, universities looking for engagement analytics and LMS integration, and corporate learning departments tracking speed to proficiency. In practice an instructor opens a session, shares source material, and lets the toolkit propose polls and quizzes tied to that content. Students answer at their tables, the AI surfaces where understanding is thin, and the tutor can step in with practice questions and guided feedback. Engageli positions itself against general video conferencing. The comparison is fair on the substance: persistent tables replace one-off breakout rooms, playable recorded rooms replace flat recordings, and engagement data covers speak time, camera state, poll responses, chat and hand raises. Published figures from an active learning study cite 13x more learner talk time and a 14 percent lift in tutoring test scores when tutoring happens inside the live classroom. The tradeoff is scope. This is a full teaching platform, not a plug-in study aid, so adoption means running classes on Engageli rather than adding a tutor to an existing stack. Pricing is quote based and a demo is the entry point. Buyers evaluating a standalone AI study companion will find this heavier; institutions already committed to a virtual classroom will find the tutoring native to the workflow.