The personalized teaching layer for AI
It doesn’t just answer.
It learns how you learn — and how to teach you next.
General models solved knowing the answer. Aptiz AI builds the personalized teaching layer on top — it works out who the student is, where they’re stuck, and what to teach next.
| 01 | Knowledge Knowing the answer | Solved by LLMs |
| 02 | Teaching adaptation How to teach this student | Our layer |
| 03 | Learning state What to teach right now | Our layer |
01 · The problem
General AI waits for a good question — then stops at one answer.
Not the bottleneck
Generating knowledge
The real bottleneck
Deciding how to teach it
02 · What makes Aptiz AI different
Against a general chatbot. The same comparison against adaptive question banks and human tutors is on the method page.
| Ordinary AI tutor | Aptiz AI |
|---|---|
| Waits for the student to ask precisely | Infers the next step from work, errors & behavior |
| Generates one explanation | Generates several teaching moves and ranks them |
| Personalization stops at tone & examples | Personalizes the move, order, difficulty & hints |
| Chat ends = done | Must be verified by a new, delayed task |
| Logs the conversation | Maintains a correctable student state |
| Optimizes satisfaction / time-on-app | Optimizes mastery, transfer, memory, confidence |
03 · Live demo — try it
IllustrativeSame student, same error. Pick a teaching move — or let the system choose — then see why, verify it, and watch the model update. Switch students to see the same error get a different move.
Three candidate teaching moves
Why this method?
Verify → update
Watching an explanation isn’t learning. Confirm mastery on a brand-new task.
New task
New task · (3x − 6) / 4 = 3
✓ Solved with no hints — mastery confirmed. Watching an explanation would not have counted.
Model update
Counter-example weight ↑ for stable slips · next: a delayed retrieval task in 3 days.
04 · Why we can optimize teaching
Recording every learning trace is where AI beats any human — so we spend all our effort on teaching well.
A pile of chat logs isn’t an advantage. Structured cause-and-effect — state → move → result → mastery — is. It compounds across students, subjects and regions: the more it’s used, the better it gets.
The full method — the six-step loop, the two student models, and the six teaching moves →
05 · What counts as learning here
Step 1
Initial error
Step 2
Intervention
Step 3
Mastery on a new task
We accept one definition of success: unprompted transfer, still remembered later.
Not evidence of learning:
06 · Vision
For the first time, scale and personalization can happen together.
Scaling education used to mean standardizing it. AI breaks that trade-off — which reorganizes not a software category, but how every student understands, practices, gets feedback, and plans what’s next.
i · Who decides where learning goes
Bus
Traditional school
Fixed route, time and group pace. Fall off the group’s speed and you’re left behind.
Carpool
Human tutor
More flexible, but bound by price, time and teacher supply — never everyone’s infrastructure.
Private car
Personal AI tutor
The learner sets the destination and leaves anytime; the system adapts the route to them.
ii · How much the system drives — our roadmap
Phase 1 · Manual
Today’s general AI
Powerful — but the student must judge what they don’t know and what to do next.
Phase 2 · Automatic
Decides within a frame
The system chooses inside a human-designed teaching framework.
Phase 3 · Self-driving
Finds new methods
The system discovers teaching combinations no human wrote down.
iii · Equity = the market-expansion flywheel
Not a slogan bolted to the end — it comes straight from the cost structure. Lower marginal cost makes people who could never afford a tutor into users. Equity means the whole market gets bigger.
Cost falls
More students reachable
More learning evidence
Better adaptation
iv · The market, bottom-up
Entry
Paid personalized help
High-intent, well-defined tutoring & exam prep.
Expansion
A subscription product
High-frequency practice, explanation & planning.
Endgame
Every student’s learning layer
The core interaction layer of next-gen education.
Mission
The help a child gets shouldn’t depend on income, postcode, or luck with a teacher.
We don’t promise to erase every gap. We aim to lower how much high-quality, personalized teaching depends on family income, region and teacher supply.
Early customers
Work with us
A limited Founding Pilot — a personalized AI learning agent with human quality calibration.
Explore the pilot →07 · Questions
What is Aptiz AI?
Aptiz AI is an education-technology company building a personalized teaching layer that sits on top of general AI models. Instead of only answering questions, it works out who the student is, where they are stuck, and what to teach next — then checks that the teaching actually worked.
How is Aptiz AI different from ChatGPT or an ordinary AI tutor?
A general chatbot waits for a well-formed question and stops at one answer. Aptiz AI infers the next step from the student’s work, errors and behavior, generates several candidate teaching moves and ranks them, personalizes the move, order, difficulty and hints rather than just tone, and treats a lesson as unfinished until mastery is confirmed on a new, delayed task. It keeps a correctable student state instead of a chat log. How it decides what to teach next →
Does Aptiz AI replace human teachers?
No. In the Founding Pilot the AI makes the day-to-day teaching calls, while people handle cold-start setup, weekly calibration and exceptions. The aim is to reduce how much personalized teaching depends on family income, region and teacher supply — not to remove teachers.
How does Aptiz AI know a student has actually learned something?
By requiring unprompted transfer that is still remembered later: the student must succeed on a new task, delayed in time, that they were not walked through. Watch time, cards completed, clicks and satisfaction are explicitly not accepted as evidence of learning.
Who is Aptiz AI for?
Students who need personalized help and the parents arranging it, starting with high-intent, well-defined tutoring and exam preparation. The pilot is set up around one learner’s syllabus, goals and pace.
Can I use Aptiz AI today?
Not as a general subscription. Aptiz AI is pre-launch, and access is through the Founding Pilot — a limited cohort taken by application.
What does the Founding Pilot cost, and what is the commitment?
The pilot is by application rather than purchase, and it is not a subscription. Each application is reviewed, and an interview and needs assessment happen before any commitment is agreed. A cycle runs four weeks and ends with a learning-evidence report and a joint decision about what comes next.
Where is Aptiz AI based, and what happens to data submitted through the site?
Aptiz AI is based in Australia. The website’s two forms collect only what is typed plus basic submission context; details are never sold or shared for third-party purposes, are kept no more than 24 months after last contact, and can be deleted on request to foraptiz.ai@gmail.com. The full notice is in the privacy notice.
08 · Investors
Leave your details — we’ll message you.
Deck, pilot data, unit economics and milestones on request. Tell us how you prefer to be reached and we’ll come to you there, usually within two business days.
Prefer email? Write to foraptiz.ai@gmail.com directly.