"Incredibly easy to work with"
Working with TopFlight has been an exceptional experience. They quickly understood our vision and built exactly what we needed. They are now partnering with us to scale our product in schools and they've really given us the firepower to innovate.
The team were proactive, thoughtful, and incredibly easy to work with always finding smart, pragmatic solutions without ever compromising on quality or compliance. Our platform has already helped us demonstrate the potential of Learning DNA to partners and investors, and it's given us a strong foundation to build on as we grow.
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Case study learning-dna
Enabling faster, smarter educational support through cutting-edge tech and AI
250+
Schools now using the platform
65%
Increase in turnover
100+
hours of manual effort eliminated
Technologies
The tech stack we used to build this project
Supabase
TypeScript
Vue
Node.js
Docker
Digital Ocean
Project summary
We partnered with Learning DNA to rapidly launch an MVP platform designed to modernise how schools support children with special educational needs. Built as a real-world experiment, the platform digitised assessment workflows traditionally reliant on paper and offline processes. By testing demand, usability, and operational fit at scale, the MVP quickly demonstrated strong market traction and validated the case for wider rollout. Today, the AI platform is transforming how schools support children with special educational needs across the UK.
The problem
Schools supporting children with special educational needs are often held back by manual, paper-based assessment processes. These outdated systems create unnecessary operational overhead and struggle to meet growing expectations for digital accessibility. Learning DNA needed to test a modern, compliant digital approach, one that could handle sensitive data, serve multiple user types, and adapt as regulatory requirements evolved.
The challenge
The challenge was to deliver an MVP (framed as an experiment) at speed while treating it as a learning exercise rather than a final product. Requirements evolved as the platform took shape, and the solution needed to balance simplicity with strict compliance and data sensitivity. The MVP had to digitise complex, paper-based workflows, support multiple user roles, and prove its value quickly, all while remaining flexible enough to support future phases, integrations, and live service delivery. Just as importantly, the MVP needed to generate real-world learning quickly to inform whether and how the platform should scale.
The services
We took an agile, experiment-led approach focused on rapid validation. Working closely with stakeholders through weekly huddles and fast prototyping, we prioritised learning and usability over unnecessary complexity. The MVP was delivered using a Vue.js frontend, a Node.js backend with Open AI integrations, and a custom PDF generation engine, hosted on secure cloud infrastructure via Digital Ocean. The architecture was intentionally designed to evolve, supporting future integrations, video-based services, and configurable digital offerings aligned with regulatory frameworks.
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