Marking Assist was not designed in a startup. It was designed in a staffroom — by academics who mark, who supervise, who know what it means to write the fortieth version of the same feedback comment at 11pm before a deadline.
Who we are
Marking Assist is the educational technology product of our academic development division — a team of practising higher education professionals who identify problems in assessment and feedback practice and build technology solutions to address them.
We are not an AI company that discovered education. We are educators who know what responsible AI integration looks like — because we have read the research, lived the workflows, and sat on the quality assurance panels that set the standards we design to meet.
Every decision in Marking Assist — from the colour of the feedback zones to the order in which information is presented to the marker — is grounded in educational research and validated by practising lecturers.
Research-grounded
Every design decision traces back to published research in assessment, feedback literacy, and automation bias.
Lecturer-tested
Beta tested by practising HE lecturers from v0.1. Real marking scenarios. Real student submissions. Real feedback.
Ofqual-aligned
The five Ofqual principles for AI in marking are embedded in the architecture, not added as a compliance checkbox.
Continuously improved
Structured feedback from beta testers drove every major feature — the comment bank, batch upload, and zone system all came from lecturer input.
Development history
Two years from the first whiteboard sketch to the platform you see today.
Concept
Lead developer identifies the marking burden problem and begins research into hybrid AI-marking approaches. Initial literature review of automation bias and Ofqual guidance.
Design
Team of lecturers assembled. First design sessions held to map the three-zone colour system and Grader Note safeguard. Ofqual principles reviewed and embedded into the architecture.
Alpha
First working prototype developed and tested internally by the academic team. Workflow validated against real marking scenarios across humanities, STEM, and postgraduate programmes.
Iteration
Major improvements based on internal testing: comment bank expanded, batch upload introduced, calibration settings refined, automation bias safeguard strengthened. Zone colour system finalised.
v1.0 Launch
First public release. Pay-as-you-go pricing introduced. GDPR-compliant infrastructure deployed. Ofqual alignment documentation published.
v2.0
Full platform redesign informed by the 2026 systematic review of AI in HE assessment. Cohort analytics, multi-disciplinary modes, and institutional tier added. Academic Ledger design language introduced.
Free to start. No card required. Built by people who understand what you do.