GradeNext – AI Learning Platform Development
GradeNext set out to reimagine after‑school learning for grades 1–8 with an AI‑aware platform that combines self‑paced practice, live tutoring, and coding classes. They needed a partner who could design and build a secure, cloud‑native SaaS platform that feels playful for students, yet reliable and data‑driven for parents, tutors, and administrators.
Client Challenge
Day‑to‑day operations were spread across multiple tools: one app for practice, separate tools for live classes, shared sheets for attendance, and WhatsApp/ email for updates. The team was spending hours every week just reconciling who did what.
Parents and tutors received mixed, sometimes conflicting views of a student’s progress because data lived in different places and was updated manually. It was hard to answer a simple question like “Is this learner on track this month?” with confidence.
Scheduling and rescheduling sessions depended on manual coordination between centres, tutors, and families. Last‑minute changes often got lost, causing missed classes and frustration for everyone involved.
Launching a new subject, city, or offer meant copying the same workflows in yet another set of tools. Nothing was reusable, and every growth step increased operational risk instead of reducing it.
Platform design & delivery approach
Designed and delivered a cloud‑native SaaS platform with AI‑powered practice, student and parent dashboards, Nexus multi‑role portal, and integrated scheduling for live tutors.
Platform & Experience Design
- Ran collaborative workshops to map learner, parent, and tutor journeys across the main GradeNext app and the Nexus portal.
- Defined a clear IA: Learning Wonderland dashboard for students, Nexus hub for parents/tutors, and shared services for scheduling, progress, and billing.
- Created a component library for cards, dashboards, and progress tiles so new modules could be added without redesigning the entire UI.
AI‑Powered Practice & Progress
- Implemented topic‑wise practice flows that combine difficulty levels, accuracy history, and exposure tracking to decide what a student should see next.
- Designed data models for attempts, streaks, and topic mastery so AI/ML models can evolve without breaking the core experience.
- Surfaced insights in plain language on dashboards (badges, accuracy bands, weekly trends) instead of raw analytics charts.
Cloud‑Native SaaS & Nexus Portal
- Built the core platform as a multi‑tenant SaaS on AWS using React/Next.js on the front‑end and Node.js/MongoDB on the back‑end.
- Implemented secure role‑based access so students, parents, tutors, and admins share the same platform while seeing only what they need.
- Delivered the Nexus portal where parents and tutors can manage schedules, reschedule requests, see performance, and coordinate 1:1 sessions.
Secure Platform Engineering & DevOps
- Applied secure‑by‑design patterns for authentication, data segregation, and audit logging from the first release.
- Set up CI/CD pipelines, environment‑specific configuration, and automated checks so new features can be shipped frequently with confidence.
- Introduced observability (logs and basic metrics) so the team can see how the platform behaves under real classroom usage.
Results & Impact
Delivery flow
Discover
Workshops with stakeholders to map users, goals, and success criteria for the platform.
Design
Experience maps and architecture that balance product ambition with delivery reality.
Build
Incremental releases with secure defaults, tests, and clear ownership across teams.
Operate
Ongoing improvements, monitoring, and roadmap iteration after launch.