WORLDWISE LEARNING
A defined data model, scheduled reconciliation, human review and visible failure.
The founder's own reference system, built for his teaching. Not a university deployment.
Spoken in English. Subtitles: English, Vietnamese and Chinese together, or any of 11 languages.
Animated diagram by WorldWise Learning, derived from the system's own schema and scheduling. The presenter, Minh, is an AI avatar with an AI voice, made with Google Vids. No live records, student data or metrics are shown. The data-centre background is an AI-generated image.
How it is built
One data model
A secure web application over one relational database, behind sign-in, with ten tables covering the whole teaching operation.
Scheduled and recorded
Two daily jobs an hour apart reconcile the calendar into lessons and mirror records into Notion. Every run is recorded; a missed run is surfaced.
Human review first
Source files are tracked by content and changes go to a human review queue. No language model is called, by design.
What transfers to a university
- A defined data model
- A scheduled reconciliation pipeline
- Grounded assistance under human review, with observability
How to start
- Read the architecture page.
- Send a short enquiry about one challenge.
- We discuss the scope and what your team can provide.
- You receive a written proposal.
The founder's own reference system, built for his teaching. Not a university deployment.
About this film
A short film on the reference production system WorldWise Learning's founder designed, built and runs for his own teaching: a secure web application over one relational database, a ten-table data model, two scheduled daily jobs with recorded runs, source files tracked by content with a human review queue, and no language model by design. Not a university deployment.
Transcript
- Hi, I'm Minh, from WorldWise Learning. Before AI goes anywhere near your university, the system underneath has to be right.
- Here is one our founder built and runs for his own teaching.
- It's a secure web application over one relational database, behind sign-in, deployed continuously.
- Ten tables hold the whole teaching operation: students, lessons, assessments and more.
- Every day, two scheduled jobs run an hour apart. The calendar becomes lessons, and teaching records sync to Notion.
- Every run is recorded, and a missed run is surfaced, not assumed.
- Source files are tracked by their content, and changes go to a human review queue.
- No language model is called yet, by design: the data and the oversight come first.
- The same pattern moves to your university: a clear data model, reconciliation, human review, and visibility when things fail.
- Let's discuss your project.