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◆ Solutions · Tutors / EdTech

Tutors that look you in the eye.

Effective tutoring is about turn-taking, pacing, and visible attention. Atlas renders the face while your stack controls the lesson and conversation.

Book a deployment reviewEmail eric@northmodellabs.comRead the docs →

◇ Problem

Why current solutions fall short.

  • Voice-only tutors do not provide visual speaking and idle cues
  • Fixed session limits can interrupt longer lessons
  • Pre-rendered studio video cannot adapt to a live lesson
  • Per-session pricing can be difficult to align with variable lesson length

Stack-level cost: every drop-off mid-lesson is a churned learner. Retention dominates LTV.

◆ How Atlas fits

A persistent tutor identity, sized to the lesson.

  • 1:1 lesson with a specific tutor avatar tied to the learner
  • Cohort / classroom mode: one render stream into many viewers
  • Pronunciation feedback: the tutor visibly mouths the correct phonemes
  • Visible 'thinking' / pause cues so learners know it's their turn
  • Drop-in / drop-out: pause a lesson, resume same identity later

◆ Deployment rationale

Realtime rendering can add visible turn-taking cues to a live tutoring experience.

  • Per-second billing fits drop-in / drop-out lesson patterns
  • No fixed session cap, run a full lesson without re-auth
  • Lip sync follows the audio supplied by your TTS system
  • Single avatar per learner sustains identity continuity across many lessons
  • Multi-viewer mode for live classroom or cohort lessons

◆ Integration shape

What it actually looks like in your codebase.

  1. 01

    Pair with your curriculum

    Your lesson engine drives prompts and pacing; Atlas renders the face.

  2. 02

    Wire STT/LLM/TTS

    Use whatever stack already powers your tutor. Atlas is passthrough.

  3. 03

    Persist tutor identity

    One reference image per tutor; same identity across all sessions for that learner.

  4. 04

    Ship into the app

    WebRTC in the browser or native via WebView, including your own cohort-classroom experience.

◆ What to measure

The metrics that prove this is working.

Session completion rate

Compare against your voice-only or chat-only tutor baseline.

Realtime session quality

Tune your STT and TTS choices to keep turn-taking natural.

Render cost / minute

$7/hr prorated to the second. Drop-in / drop-out lessons charge only for active session time.

We don't publish customer numbers. The right comparison is against your existing baseline, your STT, your LLM, your voice, your traffic.

◇ FAQ for this use case

The questions that actually come up.

Does it work for non-English languages?

Atlas follows the audio you provide, so language coverage and pronunciation quality depend in part on your TTS system. Test the languages and voices required by your product.

Can the same tutor 'remember' the learner?

Memory lives in your stack, not ours. Atlas stays a thin rendering layer; you keep the learner record and feed it into your prompts.

Can we use it in classrooms?

Yes. Multi-viewer sessions let one rendered stream serve many viewers for one GPU's worth of cost. Useful for cohort-based tutoring or live classroom delivery.

What about kids' privacy?

WebRTC frames are not stored. For under-13 deployments, customers handle COPPA-compliant consent on their side. See /safety.

Ready to ship?

Email if you want async, book if you want a structured call. We'll follow up to discuss fit and requirements.

Book 30 min ↗Email eric@northmodellabs.comAll use cases