From quiet
submission to
active mastery.
Most students can produce the work. Far fewer can explain it. AURA makes that conversation happen - across assignments, case studies, and interview preparation - building the verbal fluency they'll need long after graduation.
"You don't truly know it
until you can explain it."
- Michal Bobula, Founder
Three steps. One conversation.
Set up
Upload the materials for the conversation. AURA reads everything and prepares.
Feedback
AURA generates written feedback linking what the student said to the learning outcomes.
Converse
The student has a short voice conversation with AURA. Questions are drawn directly from their own submission. No trick questions. No marks at stake.
The gap between writing and understanding
In higher education, students submit work and receive a grade. But the ability to produce a polished document does not always mean the learning has stuck.
Passive recall
Traditional assessment often measures recognition rather than understanding. Students can synthesise information without internalising its logic, leading to rapid knowledge decay.
Active articulation
When students explain their own work out loud, gaps in understanding surface immediately. AURA makes that conversation happen, structured, recorded, and tied directly to your learning outcomes.
This is not just a good idea
AURA's approach is grounded in well-established cognitive science. The research is clear: articulating knowledge out loud is one of the most powerful ways to consolidate it.
Grounded in peer-reviewed cognitive science research.
Deeper learning
A meta-analysis of over 6,000 participants confirms that prompting learners to explain their reasoning significantly improves learning outcomes.
Bisra et al. (2018), Educational Psychology Review
Better retention
Students who practised retrieval recalled twice as much on delayed tests compared to those who simply restudied the material.
Smith & Karpicke (2014); Roediger & Karpicke (2006)
Is all it takes
Each AURA session is short, focused, and designed to fit around existing teaching - not replace it.
One mechanism, many possibilities
AURA works with any educational material a student submits: essays, reports, case studies, CVs, lab write-ups, portfolios. The core is always the same. Here are three examples.
Assignment Conversation
After submitting written work, students have a short conversation with AURA about what they wrote. Questions come from their own submission, not a generic prompt bank.
This is where learning consolidation happens. Explaining your own arguments out loud forces a level of engagement that re-reading never achieves.
Interview Preparation
Students practise articulating their knowledge, skills, and experience in an interview-style format. AURA draws from their submitted materials to ask realistic, targeted questions.
The goal is not to rehearse scripted answers. It is to build verbal fluency and confidence under light pressure.
Case Study Discussion
Students engage with case study material through guided discussion. AURA probes their analysis, asks them to justify reasoning, and explores alternative perspectives.
This builds the analytical verbal skills that seminars aim for, but available to every student, not just those who speak up in class.
Built for the realities of higher education
Grounded in source material
Whether it's a student submission, a case study, or a presentation topic - every question is drawn directly from the work itself. No generic prompts. Every conversation is authentic.
Every student, stronger
Knowledge sticks when students say it out loud. AURA anchors every conversation to your module's learning outcomes, so each session builds genuine understanding, not just familiarity.
Private by design
EU-hosted. Zero data retention on AI calls. Built to meet institutional requirements before you even ask.
Fits your VLE
Integrates with Blackboard and other virtual learning environments. No new platform to learn.
Born in the classroom
AURA grew from a practical observation in higher education: students who could produce polished written work often struggled to explain that same work verbally. The disconnect mattered, both for their learning and for the employability skills they would need after graduation.
Rather than adding another layer of assessment, AURA provides a space for students to practise articulating what they know. The AI asks questions based on their own submitted work, and the conversation itself becomes the learning moment.
We are actively working with universities to pilot and refine the tool in real teaching contexts, and we are always looking for collaborators.
Learning, not surveillance
AURA strengthens understanding. It does not police it. The focus is always on helping students learn.
The teacher decides
Quality assessment remains the lecturer's responsibility. AURA supports the process; it does not replace professional judgement.
Simple and bounded
AURA helps students talk through their own work. That focused scope is a deliberate strength.
Run a pilot. Shape what comes next.
We are looking for collaborators: lecturers, learning technologists, and institutions interested in piloting AURA with their students. Pilot partners get:
- Co-authorship on published research
- Direct input into product development
- Free access during the pilot period