I have mapped out a mobile MVP that turns any high-school Biology or Chemistry syllabus into a personalised, evidence-based study schedule. A student snaps a photo of the hand-out or drops in the original PDF—both formats must work seamlessly—then the app extracts the key learning objectives, test dates and other cues and converts them into a day-by-day plan laid out as an intuitive visual timeline. Core flow 1. Scan / upload → run on-device OCR (Tesseract, VisionKit or similar). 2. Parse text with lightweight NLP to isolate learning objectives first, then dates, topics and assessments. 3. Feed the parsed data into a scheduling engine that applies retrieval practice, spacing and interleaving rules. 4. Serve the output as swipeable, colour-coded timeline cards (React Native, Flutter or similar) that adjust when the user edits availability. Scope of this MVP • End-to-end mobile build (iOS + Android) with camera, file-picker and timeline UI. • Cloudless first cut: all processing can be local or in a lightweight serverless function; whichever expedites delivery. • Basic settings screen for study hours per weekday and push-notification window. • Export of the generated plan to .ics and simple share link. Acceptance criteria • A student can import a syllabus photo or PDF and reach a generated timeline in under one minute on a mid-range device. • Extraction accuracy for learning objectives ≥ 85 % on a test set of five sample syllabi. • Timeline adapts instantly when the user toggles an available day. • Codebase delivered in a clean, documented repo with setup instructions. If you already have experience combining OCR and NLP in a mobile context and can demonstrate a crisp UI for timeline visualisation, this build should feel straightforward. Let me know your proposed tech stack and delivery milestones and we can get started.