Education Intelligence (SEIP)
A privacy-conscious, teacher-controlled education system concept — designed around teacher ownership, local-first workflows, deterministic processing before any AI, and controlled review of student information.
Problem addressed
Education tools often move student data into systems teachers do not control, with AI applied to raw records. The intent here is the opposite: keep the teacher in control, process deterministically first, and treat student privacy as a design constraint rather than an afterthought.
Intended users
Teachers who need to manage records and reporting while retaining ownership of their students' data.
Technologies
- Next.js
- TypeScript
- Local-first data
Key capabilities
- 01
Teacher ownership of data and workflow, with local-first processing.
- 02
Deterministic processing before any AI step.
- 03
Optional AI assistance, applied only after masking and with teacher approval.
- 04
Masking and controlled review of student information.
Currently working
The concept, data-handling principles, and workflow design.
Early prototyping of deterministic processing and masking.
Under development
A working teacher-facing prototype.
Optional, masked AI assistance behind explicit approval.
Honest note
This is an ongoing concept and prototype. It is not deployed at any school, district, or national level.
Next system
Operational Analytics