Gap Tutor

For

Parents of 4th to 8th graders who already pay for tutoring but see no progress

Solves

A student gets stuck on a math problem because of one earlier concept they never fully grasped, and traditional tutoring is too expensive and too slow to find that hidden gap.

Delivers

Root-cause diagnosis, short voice-led lesson, adaptive practice set, and a scheduled retention check

Built in

about 3 weeks of creation time, MVP in 3 days

Investment

$7,000 for the MVP, $24,500 for the full product

Run it

Inside your business, or as part of your offer to clients

For parents of 4th to 8th graders who already pay for tutoring but see no progress, turn photos of handwritten work and spoken confusion into a root-cause diagnosis, a short spoken lesson and adaptive practice that sticks.

1. Read a photo of handwritten work and extract the problem and attempt.
2. Diagnose the exact missing sub-skill from a curated skill map.
3. Generate a short voice-led lesson with visual aids for that sub-skill.
4. Create adaptive practice problems that increase in difficulty.
5. Ask the student to teach the concept back and assess their explanation.
6. Schedule and run a follow-up quick check three days later.

What goes in, what comes out

The workflow

1. In
   Start with

   Photos of wrong answers, spoken confusion, and grade level

2. 1

   Upload a photo or voice note

3. 2

   Receive a diagnosis

4. 3

   Watch a short lesson

5. 4

   Complete adaptive practice

6. 5

   Teach the concept back

7. 6

   Receive a scheduled follow-up check

8. Out
   Finish with

   Root-cause diagnosis, short voice-led lesson, adaptive practice set, and a scheduled retention check

AI does the heavy lifting, people stay in charge

Use vision models to read handwritten work and language models to diagnose the missing sub-skill against a curated skill map. Generate lesson scripts and practice problems with language models, and use voice synthesis for narration. A human curriculum expert reviews the skill map and a sample of generated lessons and problems before release, and a teacher checks flagged diagnoses before they are shown to the student.

What your team sees

Key screens: Upload, Diagnosis, Lesson, Practice, Review. Use a simple upload screen for photos or voice notes, a diagnosis screen showing the identified sub-skill with evidence, a lesson screen with a short voice-led explainer and visuals, a practice screen with adaptive problems, and a review screen showing progress and scheduled check-ins. In this product, the first view is upload, followed by diagnosis, lesson, practice and review.

Accounts and administration

Student profiles, parent accounts, lesson history, practice results, diagnosis flags, review queue for teachers, and an audit trail of all AI-generated content and student responses.

Integrations and data access

Photo upload from device, voice recording from device, a learning management system for schools, and a simple payment provider.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   3 days

   One buyer segment, one recurring use case; first modules: photo upload and diagnosis, and lesson generation. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   4 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   8 days

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will parents of 4th to 8th graders who already pay for tutoring but see no progress use it to solve "A student gets stuck on a math problem because of one earlier concept they never fully grasped, and traditional tutoring is too expensive and too slow to find that hidden gap"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Run a paid pilot with 20 families for 4 weeks.
4. Measure, then decide. Track number of remediations completed per student per month and and parent-reported confidence improvement after 4 weeks. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One buyer: parents of 4th to 8th graders. One use case: fractions for grades 4 to 8. First two modules: photo upload and diagnosis, and lesson generation. Manual review: a teacher reviews every diagnosis and lesson before it is sent to the student.

After the MVP. After the paid pilot, automate the teacher review for high-confidence diagnoses, expand the skill map to all math topics for grades 4 to 8, add voice note input, and automate the retention check scheduling and reporting.

What the build depends on. A reliable vision model for handwriting recognition, a curated skill map for grades 4 to 8, a voice synthesis service, and a secure student data store.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test pricing: free for 5 remediations a month, unlimited for $9 per month per family, and $500 per year per grade level for schools.

Message to test

Find the exact gap in your child's math understanding and close it with a patient AI tutor that checks back until it sticks.

Where to find buyers

Parent Facebook groups, homeschooling forums, school parent newsletters, and search ads for tutoring and math help.

Lead magnet

A free diagnosis of one photo of a wrong answer, showing the exact missing sub-skill and a sample lesson.

The first 30 days

1. Week 1: Build the photo upload and diagnosis pipeline with a curated skill map for fractions.
2. Week 2: Build the lesson generation and voice synthesis flow.
3. Week 3: Build adaptive practice generation and the teach-back assessment.
4. Week 4: Build the retention check scheduler, run a small pilot with 10 families, and gather feedback.

Paid pilot

Run a paid pilot with 20 families for 4 weeks. Baseline: current tutoring spend and reported progress. Measure: number of remediations completed and parent-reported confidence. Decision: continue if at least 70% of families complete 5 remediations and report improved confidence.

Success metrics

Number of remediations completed per student per month, and parent-reported confidence improvement after 4 weeks.

Retention and expansion

The scheduled retention check brings students back three days after each remediation, and the subscription renews monthly as long as the student keeps making progress.

Why clients would pick it

The curated skill map and the corpus of diagnosed student work become more accurate and comprehensive over time, making the diagnosis faster and more reliable than any generic tutor.

Alternatives and positioning

Human tutors, tutoring centres, and generic AI chatbots. This differs by pinpointing the exact missing sub-skill from a photo, teaching it in a short voice-led lesson, and scheduling a retention check.

Main delivery costs

Cloud compute for vision and language models, voice synthesis, curriculum expert review time, and teacher review time during the pilot.

Age-appropriate content only, no collection of personal data beyond a student profile, teacher review of all diagnoses and lessons before delivery, a limit on practice session length, and a clear statement that the AI must not provide medical or psychological advice. It must not generate content outside the curated math skill map.