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AI and software engineering for education

Education software has a usage pattern almost nothing else shares: near-zero load for weeks, then every user arriving within the same hour on results day. It also frequently involves minors, which changes what you may collect and how content must be filtered. We build learning platforms and assessment tooling around both realities.

Discuss a education projectAll sectors

What makes it hard here

  • Load is seasonal and extremely peaky
  • Younger users change the rules
  • AI feedback assists, it does not grade alone

Services this involves

Different constraint?Tell us about it
What is different here

Where education projects actually go wrong

The load pattern is the technical headline. An education platform can be comfortably idle for a month and then face its entire user base simultaneously, and systems sized for the average fall over exactly when they matter most.

The other constraint is who the users are. Where a platform touches minors, data collection, content filtering, and moderation stop being product decisions and become obligations — and they are far cheaper to design in than to retrofit.

Load is seasonal and extremely peaky

Enrolment, submission deadlines, and results days concentrate the entire user base into short windows. Capacity is planned for those hours, not for the monthly average.

Younger users change the rules

Where minors are involved, data minimisation, content filtering, and moderation are requirements rather than features, and they shape the schema and the model choices.

AI feedback assists, it does not grade alone

Model-generated feedback is useful and fast; unreviewed automated grading of consequential assessment is not defensible to a student who challenges it. A human stays in the loop where the result counts.

What we build

Systems we build for education & edtech

Learning platforms

Course delivery, progress tracking, and cohort management built to hold up during the enrolment and deadline peaks.

Assessment and feedback tooling

Draft feedback generated at speed and surfaced for an educator to review, edit, and approve — reducing marking time without removing judgement.

Content generation and adaptation

Producing practice material and reformatting existing content for different levels, with subject-matter review before it reaches learners.

Institutional integration

Connecting to student information systems and single sign-on so the platform fits the institution rather than duplicating its records.

Related services

The services this usually involves

Questions

Education & EdTech: common questions

Can AI grade student work?

It can produce useful draft feedback quickly, and that saves genuine time. Grading consequential assessment without human review is a different matter — it is difficult to defend when a student challenges a mark, and the appeal is where the system gets tested. We build it as assistance with an educator approving the result.

How do you handle platforms used by children?

By collecting as little as the product genuinely needs, filtering generated content before it reaches a learner, and building moderation in from the start. The specific obligations vary by jurisdiction and age group, so those are settled at scoping rather than assumed.

Can the platform handle enrolment and results-day traffic?

That is the main thing worth engineering for in education. It means load testing against the peak rather than the average, and infrastructure that scales for a few hours without being paid for year-round.
Other sectors

Building something in this sector?

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