Personal AI Tutor

For

Parents of primary school children in English-speaking countries

Solves

A child in a classroom of 40 students waits days for a teacher to notice she cannot read a paragraph.

Delivers

Personalised daily tutoring session and weekly progress report

Built in

about 4 weeks of creation time, MVP in 5 days

Investment

$9,500 for the MVP, $37,000 for the full product

Run it

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

For parents of primary school children, turn a child's spoken reading, answers and progress data into a personalised daily tutoring session and weekly progress report.

1. Assess reading level through a short game-like conversation.
2. Listen to the child read aloud and correct mispronunciations in real time.
3. Generate adaptive math and reading content based on the child's interests.
4. Switch between languages as the child progresses.
5. Record session data and produce a weekly parent report.
6. Suggest offline practice activities.

What goes in, what comes out

The workflow

1. In
   Start with

   Child's spoken reading, answers, interests and language preferences

2. 1

   Onboard the child

3. 2

   Run an initial assessment

4. 3

   Generate a daily session

5. 4

   Deliver the session with real-time feedback

6. 5

   Record progress

7. 6

   Compile a weekly report

8. 7

   Suggest offline practice

9. Out
   Finish with

   Personalised daily tutoring session and weekly progress report

AI does the heavy lifting, people stay in charge

Use speech recognition to hear the child read and detect errors, and language models to generate adaptive content and feedback. A human tutor reviews a sample of sessions for quality and safety before any content is used broadly.

What your team sees

Key screens: Home, session player, progress dashboard. Use a child-friendly home screen with a start button and character. The session player shows a large reading area with a voice prompt and a record button. The progress dashboard shows weekly gains in reading accuracy, fluency and comprehension. Display session history and next steps. Provide a parent view with a simple weekly report and offline practice suggestions. In this product, the first view is home, followed by session player and progress dashboard.

Accounts and administration

Parent accounts, child profiles, session logs, progress records, content versioning, approval of new content, audit trail of all AI interactions and data privacy controls.

Integrations and data access

Parent email for reports, payment gateway for subscriptions, and a simple learning record store for progress data.

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

   5 days

   One buyer segment, one recurring use case; first modules: reading assessment and real-time reading correction. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   6 days

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

4. 4

   Full product

   2 weeks

   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 primary school children in English-speaking countries use it to solve "A child in a classroom of 40 students waits days for a teacher to notice she cannot read a paragraph"?
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 8 weeks.
4. Measure, then decide. Track two measurable outcomes: average reading accuracy improvement per child per month and and parent retention rate after the first month. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. One buyer: parents of 6-year-olds. One use case: reading tutoring in English. First two modules: reading assessment and real-time reading correction. Manual review of session transcripts by a tutor before weekly reports are sent.

After the MVP. Automate content generation for math and second-language learning, add adaptive difficulty curves, and introduce school or NGO bulk accounts with teacher dashboards.

What the build depends on. Reliable low-latency speech recognition, a child-safe language model, and a secure data storage layer compliant with child privacy regulations.

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 at USD 19 per child per month, with a free tier of three sessions a week. Schools pay a flat fee of USD 1,000 per year for bulk access.

Message to test

A personal tutor that hears your child, corrects gently, and adapts to her pace and interests, for less than the cost of one hour of private tutoring.

Where to find buyers

Parenting forums, school parent associations, and social media ads targeting parents of primary school children.

Lead magnet

A free 20-minute demo session where parents hear their child read and see a sample progress report.

The first 30 days

1. Week 1: Build the reading assessment module and integrate speech recognition.
2. Week 2: Develop the real-time correction loop and session player.
3. Week 3: Create the parent dashboard and weekly report generator.
4. Week 4: Run a pilot with 10 families and collect feedback on usability and learning gains.

Paid pilot

Run a paid pilot with 20 families for 8 weeks. Baseline: each child's reading level at start. Measure weekly progress and parent satisfaction. Decision: proceed if 70% of children show measurable reading improvement and 80% of parents renew.

Success metrics

Two measurable outcomes: average reading accuracy improvement per child per month, and parent retention rate after the first month.

Retention and expansion

The subscription renews monthly, and the weekly report keeps parents engaged. As the child progresses, the tutor introduces new subjects and languages, increasing the perceived value and reducing churn.

Why clients would pick it

The more children use it, the more speech and learning data improves the accuracy of error detection and the quality of adaptive content, making the tutor harder to replicate.

Alternatives and positioning

Private tutoring, after-school centres and generic educational apps. This differs by offering real-time spoken correction and adaptive generation at a fraction of the cost.

Main delivery costs

Speech recognition API usage, language model inference, content moderation review, and cloud storage for session recordings.

Limit sessions to 20 minutes per day. Require parent consent for data collection. Never record audio without clear indication. Must not provide medical or psychological diagnoses. Must not replace professional educational support. All AI interactions are logged and reviewed for safety.