Running Paper provides a web‑based platform that uses AI to automatically recognise, mark and generate detailed feedback for handwritten assessments at scale, handling bulk uploads of up to 1,500 pages per batch. The system integrates with over 25 MIS platforms, delivering question‑level analytics, personalised comments and exportable data to help UK secondary schools and multi‑academy trusts reduce marking time and improve feedback quality.
Funding
Funding not disclosed
Founders
Product
Problem
Secondary schools spend significant staff time manually marking handwritten assessments, which delays feedback to students and limits the amount of work teachers can review, especially for large cohorts and high‑stakes exams.
Solution
Running Paper offers a web‑based platform that uses artificial intelligence to automatically recognise, mark, and generate detailed feedback for pen‑and‑paper assessments at scale. Teachers upload batches of up to 1,500 pages; the system allocates each page to the correct student, applies AI‑driven marking criteria, and produces question‑level analysis and personalised comments within seconds. Integrated analytics highlight learning gaps, misconceptions, and demographic trends, while the dashboard lets staff view individual results, class reports, and export data to Excel or BI tools. The service connects directly to over 25 MIS systems, keeping student records synchronised without manual data entry.
Target Audience
Primary customers are secondary schools and multi‑academy trusts in the UK that need to mark large volumes of handwritten assessments for KS3–KS5 and IB curricula.
Features
- High‑accuracy handwriting recognition (>95% out‑of‑the‑box) combined with large language model post‑processing for precise marking
- Bulk upload of up to 1,500 pages per batch with automatic student allocation and cross‑validation using multiple AI models
- Granular, adjustable‑reading‑level feedback for each question, delivered as PDF/Word and optionally emailed to students and parents
- MIS integration via Wonde supporting over 25 systems (e.g., SIMS, Bromcom, Arbor) to keep student data up to date
- Worksheet builder that supports images, tables, LaTeX, and code blocks, plus AI‑generated assessment creation
- Class‑level analytics with question‑level performance, exportable to Excel, and demographic filters (Pupil Premium, FSM, SEND)
- Enterprise APIs for pulling data into external platforms such as Power BI or Google BigQuery
- Dedicated onboarding, training, and SLA‑backed support, including a dedicated account manager for multi‑school trusts