Personalised Adaptive Learning Pathway

For

Parents seeking alternative education for children

Solves

Alternative online schools still serve the same fixed curriculum to every child.

Delivers

Personalised daily learning plan, parent progress dashboard, learning companion interactions

Built in

about 4 weeks of creation time, MVP in 5 days

Investment

$8,500 for the MVP, $33,000 for the full product

Run it

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

For parents seeking alternative education for children, turn daily check-ins and alternative education materials into a personalised learning pathway and progress dashboard.

1. Analyse multi-modal inputs like voice and drawing.
2. Map strengths and gaps in understanding.
3. Aggregate materials from alternative education frameworks.
4. Generate a unique daily plan.
5. Provide a plain-language parent summary.
6. Offer a gentle learning companion interaction.

What goes in, what comes out

The workflow

1. In
   Start with

   Daily check-ins, alternative education materials, child's current level

2. 1

   Complete a daily check-in

3. 2

   Map understanding

4. 3

   Generate a personalised plan

5. 4

   Review the plan

6. 5

   Deliver activities

7. 6

   View progress

8. Out
   Finish with

   Personalised daily learning plan, parent progress dashboard, learning companion interactions

AI does the heavy lifting, people stay in charge

Use multimodal models to read spoken answers and hand-drawn diagrams to map understanding. Generate unique daily plans from a library of alternative education sources. A human checks the safety and appropriateness of the generated content before delivery.

What your team sees

Key screens: Child check-in, Curriculum agent, Parent dashboard. Use a central check-in interface for voice and drawing inputs, a curriculum agent view showing the next day's plan, and a parent dashboard displaying growth maps without grades. In this product, the first view is the child check-in, followed by the curriculum agent and parent dashboard.

Accounts and administration

Child profiles, activity history, safety flags, subscription management, audit trails for data privacy

Integrations and data access

Voice input APIs, drawing recognition APIs, payment gateways

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. 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

   10 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 seeking alternative education for children use it to solve "alternative online schools still serve the same fixed curriculum to every child"?
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. A paid pilot with 20 families proves whether the system generates effective daily plans that improve engagement and understanding compared to a fixed curriculum
4. Measure, then decide. Track daily active users, time spent on tasks and parent satisfaction scores. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. First cut: one buyer (parents of 7-10 year olds), one use case (daily check-in and plan generation), first two modules (strength mapping and basic curriculum sequencing), manual review of safety

After the MVP. Automated learning companion, advanced analytics, integration with external tutors

What the build depends on. Multimodal AI models, secure cloud infrastructure

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

$25 per child per month

Message to test

An online school built around your child, not a curriculum

Where to find buyers

Alternative education forums, homeschooling groups, parenting blogs

Lead magnet

A free 30-day personalised learning experience

The first 30 days

1. Week 1: Ingest three alternative education frameworks.
2. Week 2: Run daily check-ins via voice and drawing.
3. Week 3: Generate each child's next day.
4. Week 4: Show a simple strength and gap map

Paid pilot

A paid pilot with 20 families proves whether the system generates effective daily plans that improve engagement and understanding compared to a fixed curriculum

Success metrics

Daily active users, time spent on tasks, parent satisfaction scores

Retention and expansion

Monthly subscription renewals based on the perceived value of the daily personalised plans

Why clients would pick it

Data accumulation over time creates a deep profile of the child's learning style and interests, making the system harder to replicate

Alternatives and positioning

Mainstream online schools, content-only libraries, and manual lesson planning

Main delivery costs

AI inference costs, content licensing, data storage and security infrastructure

Strict data privacy protocols, content filtering for age appropriateness, limits on screen time