AI and software for universities and schools
We build AI in education that supports students and staff around teaching: answering questions from course material and regulations, handling exam board paperwork and joining up student and learning systems. Teachers, study advisers and exam boards keep every assessment and decision in their own hands.
Where the work gets stuck.
Student questions flood service desks
Enrolment, timetables, resits and exemptions generate the same questions every block. Answers sit in education and examination regulations that students rarely read.
Staff workload around teaching
Lecturers and support staff handle course questions, exemption requests and administration next to their teaching. Much of it repeats each year with small variations.
Learning and student data do not connect
Osiris, the learning environment, the testing platform and Microsoft 365 each hold part of a student's record. Study advisers piece the picture together by hand.
How we improve education.
Each one is scoped around your systems and rules, and each one keeps a person in charge of the decisions that matter.
Course assistant for students
Students ask questions about a course and get answers drawn only from the material the lecturer has approved, with links to the slides or readings. Lecturers see which topics cause confusion.
Student service agent
Questions about enrolment, resits and rules are answered from the education and examination regulations and current schedules. Personal or complex cases go to the student desk with a summary.
Exam board request handling
Exemption and extension requests are checked for completeness, matched to the relevant rules and prepared with earlier comparable decisions. The exam board reviews each file and decides.
Student progress data for study advisers
Credits, attendance and submission data from Osiris and the LMS come together in one view with rule-based signals, such as falling behind on credits. Study advisers decide who to contact and how.
Accreditation and quality document search
Self-evaluations, panel reports, course evaluations and programme documents become searchable across programmes and years. Quality staff prepare accreditation visits with less digging.
Edtech platforms
For edtech companies we build learning platforms, teacher dashboards and integrations with LMS standards such as LTI. The product meets the privacy and accessibility expectations schools set in procurement.
Built around the rules.
What we design for from the first week. Your legal and compliance people keep the final word.
EU AI Act high-risk uses in education
AI used for admission, evaluating learning outcomes or monitoring students during tests is high-risk under the AI Act. We flag these uses early, design for human oversight and documentation, and keep grading with teachers.
GDPR and student data
Student records often include minors and sensitive information such as support needs. We limit data per purpose, keep processing in the EU and align processing agreements with the privacy frameworks Dutch education institutions use.
Examination rules
Decisions on exemptions, extensions and fraud belong to the exam board under the institution's education and examination regulations. Our tools prepare files and record the board's decision alongside the source documents.
Digital accessibility
Student-facing tools are built to WCAG 2.1 AA through EN 301 549, and tested with screen readers and keyboard navigation. We deliver the test results as input for your accessibility statement.
Works with what you run.
If a system has an API, a database, an export or an inbox, we can build on it. These are the ones we meet most.
- Osiris
- Canvas
- Brightspace
- Moodle
- SURFconext
- Studielink
- Eduarte
- Ans
- TestVision
- Microsoft 365 and Teams
Where to start.
Course assistant for one programme
An assistant for the courses in a single programme, answering from lecturer-approved material and the programme's regulations. It is visible to students, easy to evaluate and a sound base for wider use.
Talk it throughWhat it includes
- Connection to Canvas, Brightspace or Moodle
- Answers limited to approved sources
- SURFconext login and access per course
- Eval set built with lecturers
Guides.
AI readiness checklist: what to answer before your first agent goes live
The questions to answer before your first AI agent handles real work, from process and data to approvals, monitoring and ownership.
10 min read
Build vs buy software: a decision guide for operations and product teams
A practical guide to choosing between off-the-shelf and custom software, with a cost comparison, a decision matrix and a checklist for your team.
10 min read
Further reading.
How to build a production RAG chatbot: a practical guide
What it takes to turn a promising RAG experiment into a chatbot people trust: ingestion, hybrid search, citations, permissions and evals.
5 min read
Embeddings and semantic search: a practical guide for product teams
How embeddings power semantic search, how to choose a model and a vector store, and how to measure whether your results actually improved.
5 min read
RAG vs fine-tuning: which does your business actually need?
RAG gives a model your knowledge at answer time; fine-tuning shapes its behaviour. How to choose, when to combine them and what each costs.
4 min read
Common questions.
The assistant is restricted to sources the lecturer approves and says so when an answer is outside them. We test this with eval sets built from real student questions before the assistant goes live.
Yes. We connect through the APIs and standards these systems support, such as LTI for learning environments, and use SURFconext for login. Access is agreed with your IT department and application managers.
Grading and evaluating learning outcomes is a high-risk use under the AI Act and a sensitive one for students. We do not build tools that grade on their own, and any feedback support leaves the assessment with the teacher.
In the EU, in your own cloud tenant or with a hosting party you choose. Models run through EU-hosted providers under terms that exclude training on your data.