Sheet 3.2 — node assembly drawing Online education · under NDA

Sales ×2.5 after rolling out an AI tutor

Tutors at a large online school were drowning in chats while students walked away without answers. An AI tutor, trained on the courses' own content, took over 86% of routine questions and gave the team back time for real work with students.

Sheet3.2  ·  "Cases" series
ProjectAI tutor for an online school
IndustryOnline education
ByEDEMIUM
StatusLive · evolving
TABLE 1 Baseline data

Where the client started

Table 1 — baseline data Measured: before rollout
01 Client A large online school. Name withheld under NDA.
02 Product Education courses: video lessons, homework assignments, tutor chats
03 Channels Student chats, lesson questions, homework grading
04 Team Tutors overwhelmed by chat volume; busywork ate the time meant for real teaching
05 Pain point Students left without answers: churn, rising refunds, a hit to the school's reputation
NODE 2 Failure diagnosis

Where the school lost students

Chat volume grew faster than the tutoring team. Every new cohort of students added hundreds of repetitive lesson questions and stacks of homework to grade — tutors simply could no longer keep up.

A student who asked a question and got no answer quickly lost motivation and left. From there the chain unwound on its own: churn, rising course refunds, a hit to the school's reputation — in a niche where reviews decide everything.

Meanwhile the team spent most of its time on busywork: the same questions over and over, mechanical grading. There was barely any time left for the deep work with students that tutors were hired to do in the first place.

Chart 1 · tutor workload before rollout
NODE 3 Solution assembly schematic

What we built

SCHEMATIC 3.2 VIDEO LESSONS TRANSCRIPTS STUDENT PROFILES AI TUTOR RESOLVES 86% IN-LESSON WIDGET HUMAN TUTOR COMPLEX A B C OUTPUT: THE ANSWER RIGHT WHERE THE QUESTION AROSE
  1. 01 · KNOWLEDGE BASE

    Transcription and model training

    Every video lesson is transcribed into text — the course content becomes a knowledge base. An AI model is trained on it: the AI tutor answers from the school's own curriculum, not in generic terms.

  2. 02 · CONTEXT

    Student profiles and an in-lesson widget

    Each student has a profile: specialization, level, completed lessons, past questions. A chat widget is built right into the lessons: the question is asked where it arises, and the answer factors in the context.

  3. 03 · ESCALATION

    Auto-graded homework and new tutor roles

    Homework is graded automatically, and complex cases escalate to a human tutor. The team's roles are reorganized: instead of clearing busywork, tutors do deep work with students.

TABLE 2 Results schedule

Results in numbers

Sales
×2.5
after rolling out the AI tutor
Routine questions
86%
resolved without a tutor
Homework grading
×2
twice as fast
Tutor busywork
−42%
time spent on repetitive tasks
Chart 2 · sales index
Chart 3 · student questions
Table 2 — full metrics schedule Measured: before / after
MetricBeforeAfter
Sales×1.0×2.5
Routine student questionswaited on a tutor86% resolved without a tutor
Homework gradingmanual2× faster
Tutor time on busywork−42%
Answering a studentleft without answersa chat widget right in the lesson
Complex questionslost in the chat streamescalated to a human tutor
Tutor rolesclearing busyworkdeep work with students
TABLE 3 Timeline and status

Timeline and status

The solution is live: the AI tutor answers inside lessons, grades homework, and hands complex cases to human tutors. The team works on deep tasks instead of clearing repetitive questions.

The system evolves along with the school: new courses are transcribed and added to the knowledge base, and the model learns from new materials and student questions.

Implementation record
StatusLive · solution evolving
Coverage86% of routine questions — without a tutor
TeamTutors moved to deep-work tasks
Exit pointPilot KPI measured: target met → scale
NODE 9 Connection point

I want the same in online education

Start with an automation roadmap: in 14 days we'll show where your school loses students and what eats up your team's time.