SHADECODESTUDENT
Study smarter. Live sharper.

A learning system that learns how you learn.

Lessons, questions, mistakes, exams, projects and study behaviour become one evolving learning experience, with Cortex helping decide what should happen next.

Responsive PWAAI-assistedLocal-firstBuilt for learning
SHADECODE
CORTEX OS
Learning state
Today
Learn
Focus
3 tasks
State
Updating
Next action
Practise mechanics

Chosen from the learner's recent evidence, not a random prompt.

Evidence-backedStart
Cortex

Observe → understand → act → measure → learn.

The Cortex loop

Not just an AI tutor. A learning system.

The goal is not to make a chatbot sound clever. It is to make the next learning action more useful because the system remembers real evidence.

01

Observe

Capture meaningful study actions, attempts and evidence.

02

Understand

Turn those signals into a clearer learning state.

03

Predict

Identify what may need attention, with confidence grounded in evidence.

04

Act

Give the learner a concrete next action.

05

Evaluate

Check what happened after the intervention.

06

Learn

Feed the measured result back into the learning state.

The toolkit

Many tools. One learning system.

Cortex

Learning intelligence

Learning activity becomes structured evidence for better next steps, without pretending that guesses are facts.

Learn

Curriculum-aware study

Learn concepts, practise them, and keep the important context around the work you are doing.

Exam Simulation

Practice that tells you something

Timed exam practice turns attempts, marks and mistakes into useful revision signals.

Math Checker

Work through the reasoning

Use handwritten-work feedback to understand methods and identify where your solution changed direction.

Project Studio

Build real projects

Move from problem to investigation, evidence, development, presentation and reflection with your work kept learner-owned.

Offline

Built for imperfect internet

Shadecode is being engineered local-first so useful study state can survive unreliable connectivity.

One foundation. Different experiences.

Shadecode grows with the learner.

The intelligence layer stays connected while the experience changes with age, curriculum and the kind of learning work being done.

Primary

Shadecode Discovery

Curiosity, play, foundations, stories, reading, maths, science and safe exploration.

Secondary + exams

Shadecode Student

Subject mastery, revision, assignments, Cambridge/ZIMSEC preparation, past papers and projects.

University + Polytechnic / TVET

Shadecode Campus

Courses, modules, coursework, research, labs, projects, portfolios, skills and careers.

Underneath them: Cortex OS with curriculum, learning evidence, mastery, memory, interventions and local-first intelligence.
Product direction

Build the learning state first. Then make it smarter.

Reliable evidence and local-first state come first. Stronger curriculum coverage and assessment intelligence follow. Then increasingly adaptive interventions and efficient local models.

Research path
01Learning State Engine
02Adaptive Intervention Engine
03Curriculum + Learning Graph
04Offline / local intelligence
05Model routing and compression
FAQ

Useful answers.