# Grayhat Project: MegaLecture Mobile App

> Expanded LLM context for the public project detail page.

## Page

- [Project Detail](https://grayhat.studio/projects/megalecture-mobile-app)
- [Projects Index](https://grayhat.studio/projects)
- [Project LLM Context](https://grayhat.studio/projects/megalecture-mobile-app/llms.txt)
- [Projects Full LLM Context](https://grayhat.studio/projects/llms-full.txt)
- [Project API](https://grayhat.studio/api/public/v1/projects/megalecture-mobile-app)
- [Projects API](https://grayhat.studio/api/public/v1/projects)

## Current Page Content

### [MegaLecture Mobile App](https://grayhat.studio/projects/megalecture-mobile-app)

- ID: `PROJ-0035`
- Slug: megalecture-mobile-app
- Client: MegaLecture
- Type: Not provided
- Start date: Not provided
- End date: Not provided
- Duration: Not provided
- Year: 2026
- Status: Completed
- Gallery attachments: 0
- Links: Visit their website (Website link): https://megalecture.com/
- Resources: Not provided
- Created at: 2026-06-04 20:01:01.987087

The MegaLecture Mobile Application is an EdTech platform developed for MegaLecture, an educator-led client focused on helping college students prepare more effectively for board examinations through structured digital learning.In close collaboration with the MegaLecture team, we developed the mobile application using Flutter and Firebase, with support for both iOS and Android. The platform was designed around a clear academic goal: to help students organize, learn, and practise for their college papers across Cambridge International O & A Levels, IGCSE, Pakistan Matric, and FSC.The application brings together handwritten notes, video lectures, complete examination past papers, MCQ papers, and theory papers from well-reputed tutors and instructors for each supported board. Students can filter papers and resources by board, year, session, topic, and paper type, making it easier to focus on the exact material relevant to their syllabus and exam preparation.A core part of the product is its interactive practice experience. Students can attempt MCQ questionnaires with real-time answer feedback or switch into a paper simulation mode with no feedback, creating a more realistic exam environment. For theory papers, students can submit image-based answers for tutor review. Each question is supported with relevant notes, video lectures, and resource links, allowing students to learn directly from the material connected to their practice.


## Notes For Agents

- This route is a leaf node in the current public projects tree, so its `llms.txt` and `llms-full.txt` surfaces intentionally expose the same full project body.

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