Case Study|Cloud Application Development

Cloud-Based Learning Platform for a Higher Education Network

Caystard developed a scalable cloud learning platform for a university network, supporting 50,000+ concurrent students and cutting IT support tickets by 55%.

Overview

A network of universities sharing a consortium-based online learning platform needed to replace an aging, unstable system that struggled during exam periods and enrollment spikes. Caystard built a new cloud-native learning management platform from the ground up.

Challenge

The existing learning platform frequently slowed or crashed during high-demand periods like exam weeks and course registration, generating a flood of IT support tickets and frustrating students and faculty across the university network. The system also lacked modern accessibility features required under updated education standards.

Solution

Caystard designed and built a cloud-native learning management platform with elastic scaling for peak periods, a redesigned accessible user interface, and integrated analytics for faculty to track student engagement in real time.

Caystard began with extensive input from faculty, students, and IT staff across the university network to understand pain points with the existing system, then designed a new platform architecture built to scale elastically rather than on fixed capacity.

Accessibility was built in from the start, with the interface designed to meet current web accessibility standards, including full screen-reader compatibility and keyboard navigation — addressing a persistent complaint about the previous system.

The platform included real-time engagement analytics for faculty, showing which students were falling behind based on login patterns, assignment submissions, and video lecture viewing — enabling earlier intervention than the old system allowed. Following launch, the platform handled a full exam period and a new-semester registration surge without the slowdowns that had plagued the previous system, and IT support ticket volume dropped sharply.

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