What we develop
Software designed around educational needs.
From the questions learners answer, to what their answers reveal, to the practice that follows. AI works behind the scenes; educators make the decisions that matter.
01 · Questions and resources
Better questions, with less preparation.
Examination preparation depends on good questions, and writing, organising and adapting them takes educators a great deal of time.
We are developing intelligent question generation that drafts questions for a chosen topic, level and examination style, and organises them into question banks that educators can review, edit and reuse.
The same approach extends to the wider work around teaching: preparing resources, assembling practice papers and keeping educational information in order. Educators check and adjust every result before it reaches a learner.
Areas of development
- Question generation
- Question banks
- Examination preparation
- Resource preparation
- Educational workflows
02 · Learning analytics
How learners approach questions, not only whether they are right.
A mark shows whether an answer was correct. It rarely shows why.
Two learners can give the same wrong answer for entirely different reasons: one has applied the wrong method, the other has misread the question. They need different help.
Our analytics look across many responses and over time: the errors that recur, the methods a learner chooses, where reasoning breaks down and how this changes with practice. Patterns that a single mark hides become visible.
This helps educators identify likely misconceptions and choose a better next step, whether a different explanation, another kind of question or practice on an earlier skill. The analysis suggests; the educator decides.
Areas of development
- Response analysis
- Recurring errors
- Reasoning patterns
- Misconceptions
- Progress over time
03 · Adaptive practice
Practice that meets each learner where they are.
Once the difficulty is known, practice can concentrate on it.
Our adaptive practice selects questions and activities that target each learner’s identified areas of difficulty, returns to them over time and moves on once understanding is secure.
Gamification, through visible progress, achievable challenges and recognition of sustained effort, makes regular practice more engaging without distracting from the learning itself.
Learners work in conventional educational interfaces built around questions, explanations and feedback. AI supports the software behind the scenes rather than conversing with children.
Areas of development
- Adaptive practice
- Targeted questions
- Gamification
- Independent study
Interested in our work?
We’d be glad to hear from you.