NotePilot

Turn study PDFs into revision notes and exam questions.

NotePilot is an AI study companion for school and university students who need to convert large PDFs into concise revision material. It generates level-adjusted notes, preserves important diagrams, and predicts likely exam questions so students can study faster and with more confidence.

Business Goals

  • Reach 10,000 registered users within 6 months of launch with at least 35% of users uploading a document in their first session.
  • Convert 18% of free users to paid plans within 90 days by gating export volume, advanced question types, and higher file limits.
  • Maintain a 30-day user retention rate of 25% or higher by making the product useful for repeated exam prep sessions.
  • Reduce average document-to-notes generation time to under 3 minutes for 90% of files up to 150 pages.
  • Achieve a 4.5 out of 5 average user rating on app stores or feedback surveys within the first year.

User Goals

  • Upload a textbook, lecture PDF, or research paper and get usable notes in minutes.
  • Choose the explanation depth that matches the student’s academic level.
  • Keep important diagrams, formulas, and tables in the generated notes.
  • Get a tailored set of exam questions by question type and difficulty.
  • Download a polished PDF package for revision and printing.

Non-Goals

  • Live tutoring or real-time chat with a human teacher.
  • Plagiarism detection or academic integrity enforcement beyond basic content processing.
  • Full office-suite editing for collaborative textbook authoring.
  • Support for non-PDF source formats in the initial release, such as DOCX, PPTX, or handwritten images only.

Aanya, Class 10 Student - Aanya studies from scanned school PDFs and wants simple notes before exams. She needs quick revision content that is easier than her textbook but still accurate.

Aanya, Class 10 Student

  • As a Class 10 student, I want to upload a chapter PDF and get simple notes, so that I can revise faster the night before exams.
  • As a student, I want important diagrams kept with labels, so that I can understand science and geography topics visually.
  • As a student, I want short and one-mark questions, so that I can practice likely exam patterns quickly.

Rohit, Engineering Undergraduate - Rohit reviews lecture notes and textbooks across multiple subjects. He wants structured summaries, formulas, and question banks that match his semester level.

Rohit, Engineering Undergraduate

  • As a bachelor’s student, I want notes generated at university level, so that the output stays technically correct without being too basic.
  • As a student, I want formulas and tables extracted cleanly, so that I can use the notes for exam revision.
  • As a student, I want long-answer and previous-year-style questions, so that I can test deeper understanding.

Priya, Postgraduate Research Student - Priya reads dense academic papers and book chapters. She needs concise but faithful summaries that retain definitions, arguments, and key figures.

Priya, Postgraduate Research Student

  • As a postgraduate student, I want a detailed version of notes, so that I can retain academic nuance while reducing reading time.
  • As a researcher, I want diagrams and charts preserved near the relevant section, so that the summary remains useful.
  • As a user, I want to export a clean PDF, so that I can annotate and print it for offline study.

Authentication and Account Access · High priority

  • Users must sign in with Google before using the app and their session should persist across devices.
  • Support Google Sign-In via OAuth 2.0 with email verification.
  • Block document upload until the user is authenticated.
  • Allow sign-out and account deletion from settings.
  • Persist user sessions securely with refresh tokens or managed auth sessions.
  • Handle first-time and returning-user flows differently.

Academic Profile Setup · High priority

  • Collect the user’s education context so note generation and question difficulty match the intended learning level.
  • Prompt for educational level on first login before upload.
  • For school users, collect class level from Class 6 through Class 12.
  • For bachelor’s or postgraduate users, collect degree, major, year or semester, and optional university name.
  • Allow profile edits later from settings.
  • Use the profile as a default prompt context for all future generations.

Document Upload and Processing · High priority

  • Accept large PDFs and process them reliably into structured text and layout signals.
  • Allow PDF upload by drag-and-drop, file picker, and mobile share sheet.
  • Support files up to at least 150 MB and 500 pages in the MVP architecture.
  • Show upload progress, validation errors, and estimated processing time.
  • Reject password-protected, corrupt, or non-PDF files with clear remediation.
  • Run asynchronous extraction and notify the user when processing is complete.

AI Note Generation and Diagram Preservation · High priority

  • Generate concise, level-appropriate notes that retain key meaning, structure, and relevant diagrams.
  • Let users choose output depth such as simple, detailed, exam revision, class level, or degree level.
  • Generate headings, subheadings, bullets, definitions, formulas, examples, tables, and highlighted key points.
  • Detect diagram-like objects, charts, maps, and flowcharts and place them near the relevant section.
  • If exact recreation is not possible, render a clean image embed or structured placeholder with caption and alt text.
  • Prevent omission of key concepts by using section coverage checks before finalizing output.

Exam Question Prediction and Export · Medium priority

  • Create exam-style questions from the source content and package everything into a polished exportable PDF.
  • Allow question modes such as important, FAQ, long answer, short answer, MCQ, one-mark, two-mark, five-mark, and previous-year-style.
  • Tailor question difficulty to the selected academic level and topic complexity.
  • Generate a cover page, table of contents, notes, diagrams, summary, and question section in one export.
  • Support PDF download and optional cloud save for later re-download.
  • Provide a basic answer key or answer hints for MCQs and short questions in later phases.

First-Time Onboarding to First Notes

  • Sign in with Google in under 15 seconds.
  • Choose academic level and profile details in a two-step form.
  • Upload a PDF or select a sample chapter to test the app.
  • Choose note depth and question type preferences.
  • Wait for processing with a progress indicator and estimated completion time.
  • Review the generated notes and export a PDF within 5 minutes of first sign-in.

1. Secure sign-in

  • The user lands on a clean sign-in screen and authenticates with Google before entering the product.
  • If sign-in fails, show a retry option and a support message.
  • Remember the user on trusted devices but require re-authentication for sensitive actions like account deletion.

2. Academic profile capture

  • The app asks for the student’s education level and relevant academic metadata before any upload.
  • Use conditional fields for school versus bachelor’s versus postgraduate paths.
  • Validate required fields inline and prevent progression until complete.

3. Upload and process PDF

  • The user uploads one PDF and the system extracts text, layout, tables, and figure references asynchronously.
  • Show file size, page count, and processing status.
  • If extraction quality is low, warn the user that some figures or scanned pages may be incomplete.

4. Choose output preferences

  • The user selects explanation level and question categories before generation begins.
  • Persist the last-used preferences per user.
  • Allow switching between simple, detailed, and exam revision modes without re-uploading the file.

5. Review and export

  • The user reviews the output, makes lightweight refinements, and downloads the final PDF package.
  • Include section-level previews so users can spot missing topics quickly.
  • If the export exceeds limits, split into multiple PDFs or offer compression.

Advanced Study Tools

  • Batch upload multiple PDFs and merge them into one topic set.
  • Regenerate only a selected chapter or section without reprocessing the entire file.
  • Generate separate question sets by difficulty and exam mark value.
  • Support OCR cleanup for scanned PDFs with mixed text and images.
  • Save study history, past exports, and favorite topics for quick reuse.

Readable, Fast, Exam-Friendly UI

  • Use a simple three-panel layout: upload, generation settings, and output preview.
  • Prioritize large type, strong headings, and high contrast for long study sessions.
  • Show progress states for upload, extraction, generation, and export to reduce anxiety.
  • Design for mobile-first usage with responsive PDF preview and one-hand controls.
  • Provide keyboard navigation, screen-reader labels, and accessible color contrast throughout.
  • Optimize for speed with skeleton loaders and incremental content rendering.

Aanya has a Class 10 science chapter due tomorrow and a 90-page PDF that feels impossible to revise. She signs in with Google, enters her school level, uploads the file, and selects simple notes plus one-mark and short-answer questions.

Within minutes, NotePilot turns the chapter into clean headings, bullet points, definitions, and a small set of labeled diagrams near the relevant concepts. Aanya downloads a polished PDF and studies the exact topics most likely to appear in her exam, without manually rewriting the chapter.

For the business, that means the product delivers immediate value in the first session and creates a repeat habit around every exam cycle. Students return with new chapters, new subjects, and higher willingness to pay for faster exports and more advanced question sets.

User-Centric Metrics

  • At least 70% of uploaded PDFs produce a usable first draft without manual correction.
  • Average time from upload to completed notes under 3 minutes for files up to 150 pages.
  • At least 60% of users download or save the generated PDF in the first session.
  • At least 40% of users generate a second output variant such as a different depth or question set.
  • Average post-task satisfaction score of 4.5 out of 5 or higher.

Business Metrics

  • 30-day retention of 25% or higher.
  • Free-to-paid conversion rate of 18% or higher within 90 days.
  • Monthly active user growth of 20% quarter over quarter in the first year.
  • At least 35% of new users complete an upload during onboarding.
  • Customer support tickets below 3% of active users per month.

Technical Metrics

  • Platform uptime of 99.9% monthly.
  • Median generation latency under 90 seconds for files up to 50 pages and under 3 minutes for files up to 150 pages.
  • 95% of exports generated without corruption or missing sections.
  • Zero critical security incidents and encrypted data at rest and in transit.

Tracking Plan

  • track sign_up_completed with education level and acquisition source.
  • track profile_setup_completed with selected level, class, degree, and semester fields.
  • track pdf_upload_started and pdf_upload_completed with file size and page count.
  • track extraction_completed with OCR success rate and figure detection count.
  • track generation_requested with note depth and question type selections.
  • track generation_completed with processing time, success status, and output length.
  • track export_downloaded with PDF format, page count, and retry count.

Technical Needs

  • Frontend built with Next.js and TypeScript for a responsive web app.
  • Backend API in Node.js with a queue-based worker system for long-running document jobs.
  • PostgreSQL for user profiles, document metadata, generation history, and exports.
  • Object storage such as Amazon S3 or Google Cloud Storage for original PDFs and generated files.
  • Background job processing using BullMQ, Cloud Tasks, or AWS SQS with worker autoscaling.
  • OCR and document parsing pipeline using a combination of pdf.js, Tesseract OCR, and layout-aware extraction.
  • LLM orchestration layer with prompt templates, safety filters, and citation-aware sectioning.

Integration Points

  • Google OAuth for authentication.
  • OpenAI or Anthropic APIs for note and question generation.
  • Cloud storage such as Amazon S3 for PDF and export storage.
  • Email or notification service such as SendGrid for completion alerts.
  • Analytics stack such as PostHog or Amplitude for product instrumentation.

Data Storage & Privacy

  • Store uploaded files and generated outputs encrypted at rest.
  • Use HTTPS everywhere and encrypt sensitive session data in transit.
  • Provide user controls for deleting uploaded documents, generated outputs, and account data.
  • Minimize retained content by setting configurable retention windows for source PDFs and intermediate OCR artifacts.
  • Design data handling to support GDPR and CCPA requests, including export and deletion workflows.

Scalability & Performance

  • Use asynchronous processing so uploads do not block the UI.
  • Cache extracted text and generation metadata to avoid duplicate processing on retries.
  • Partition workers by document size and OCR complexity to prevent large files from starving the queue.
  • Set per-user and per-plan rate limits to control inference cost and abuse.

Potential Challenges

  • OCR quality may be poor for scanned or low-resolution PDFs; mitigate with image preprocessing, quality warnings, and fallback OCR.
  • LLM output may omit important concepts; mitigate with section coverage checks, structured prompts, and post-generation validation.
  • Diagram preservation can be inconsistent; mitigate by detecting figure references and storing image crops separately for reinsertion.
  • Generation costs may rise quickly with long PDFs; mitigate with page limits, usage-based billing, and chunked processing.
  • Users may upload copyrighted or sensitive material; mitigate with clear terms, deletion controls, and access restrictions.

Team & resourcing - Small product team - 2 full-stack engineers, 1 designer, 1 part-time PM, and shared ML/infra support.

Phase 1: MVP Authentication and Upload · Weeks 1-4

  • Google Sign-In
  • Academic profile onboarding
  • PDF upload with validation
  • Basic job queue and storage
  • Simple processing status UI

Phase 2: Notes Generation · Weeks 5-8

  • Level-based note generation
  • Structured headings, bullets, definitions, formulas, and tables
  • Basic diagram detection and reinsertion
  • Notes preview screen
  • PDF export with cover page and summary

Phase 3: Exam Questions and Refinement · Weeks 9-12

  • Question type selector
  • MCQ, short-answer, long-answer, and mark-based question generation
  • Quality checks for coverage and readability
  • Re-generation controls for selected sections
  • Usage analytics and feedback collection

Phase 4: Scale and Monetization · Weeks 13-16

  • Paid plan limits and billing
  • Batch upload and history
  • Performance optimizations for large PDFs
  • Retention workflows and document deletion controls
  • Admin dashboard for monitoring jobs, costs, and failures

Paste this into Cursor, Bolt, Lovable, or v0 to start building.

Build a web app called NotePilot that helps students turn PDF study materials into concise, level-adjusted notes and predicted exam questions.

Use Next.js 14, TypeScript, Tailwind CSS, PostgreSQL, Prisma, and a queue-based worker setup for long-running AI jobs. Add Google Sign-In with Supabase Auth or Clerk. Store PDFs and generated exports in S3-compatible object storage. Use OpenAI or Anthropic for generation, and OCR/layout extraction for scanned PDFs.

Core product requirements:
1. Auth-first flow with Google sign-in.
2. Academic profile setup before upload: education level, and conditional fields for school class or bachelor/postgraduate degree, major, semester/year, optional university.
3. PDF upload with progress, validation, and asynchronous processing. Support large PDFs, show file size/page count, and reject invalid or password-protected files.
4. Generation settings screen where the user selects output level: class level, bachelor level, postgraduate level, simple, detailed, or exam revision.
5. Generate structured notes with headings, subheadings, bullets, definitions, formulas, tables, examples, and highlighted key points.
6. Preserve important diagrams, charts, flowcharts, graphs, and maps by detecting figure regions and inserting them near relevant sections with labels and captions.
7. Exam question generation with modes: important questions, FAQs, long answer, short answer, MCQs, one-mark, two-mark, five-mark, and previous-year-style questions.
8. Export a polished PDF containing cover page, table of contents, notes, diagrams, summary, and questions.
9. Add a document history page so users can reopen past generations and re-download outputs.

Recommended screens:
Sign in, profile setup, upload document, generation preferences, processing status, notes preview, questions preview, export/download, history, settings.

Data model:
User, AcademicProfile, Document, DocumentPage, ExtractionJob, GenerationJob, NotesSection, FigureAsset, QuestionSet, ExportFile, UsageEvent.
Include fields for file metadata, page count, status, selected level, note style, question mode, processing timings, storage URLs, and retention timestamps.

Implementation details:
Create API routes or server actions for auth callback, profile save, upload init, job polling, generation request, notes fetch, question fetch, export creation, and deletion. Build background workers for OCR, text extraction, sectioning, figure detection, generation, and PDF assembly. Include loading, empty, error, and retry states. Add analytics events for sign-up, profile completion, upload start/completion, extraction completion, generation start/completion, and export download.

Non-functional requirements:
Fast first-session value, responsive mobile-first UI, accessible color contrast and keyboard navigation, encrypted file storage, rate limiting, and audit-friendly deletion of user content. Optimize for PDFs up to 150 pages in the MVP and design the architecture to scale to much larger files later.

Generate the full app scaffold, database schema, key server actions, UI pages, and reusable components with realistic placeholder AI prompts and sample data.

Business Idea

# AI Study Notes App Idea ## App Concept I want to create an AI-powered study application that helps students convert lengthy study materials into concise, easy-to-understand notes while also predicting potential examination questions. ### Core Features #### 1. User Authentication * Enable **Google Sign-In** as the primary authentication method. * New users should sign in before accessing the app. #### 2. Student Profile Setup Before uploading any document, the app should ask the user to complete their academic profile by selecting: * Their current educational level: * School * Bachelor's Degree * Master's Degree / Postgraduate * Other * If they select **School**, they should choose their class (e.g., Class 6–12). * If they select **Bachelor's** or **Postgraduate**, they should choose: * Degree * Stream/Major * Year/Semester * University (optional) This information will allow the AI to generate notes appropriate for the student's academic level. #### 3. PDF Upload * Allow users to upload large PDF documents, including textbooks, lecture notes, research papers, and study materials. * The app should support large files and process them efficiently. #### 4. AI Note Generation Once the PDF has been uploaded, the app should ask the user what level of explanation they want. For example: * Class 10 level * Class 12 level * Bachelor's level * Postgraduate level * Simple/Easy-to-understand version * Detailed version * Exam Revision version The AI should then generate concise, well-structured notes based on the selected level. The generated notes should include: * Proper headings and subheadings * Bullet points * Key concepts * Definitions * Important formulas (if applicable) * Tables wherever useful * Examples for better understanding * Highlighted important points #### 5. Important Diagrams If the uploaded document contains important diagrams, flowcharts, graphs, maps, or illustrations that are relevant for understanding the topic, the AI should include them in the generated notes instead of removing them. These diagrams should be: * Clear * Properly labelled * Positioned near the relevant topic * Optimized for readability #### 6. Exam Question Prediction The app should analyze the uploaded document and generate likely examination questions based on the content. Users should be able to choose between: * Important Questions * Frequently Asked Questions * Long Answer Questions * Short Answer Questions * Multiple Choice Questions (MCQs) * One-mark Questions * Two-mark Questions * Five-mark Questions * Previous-year-style Questions (AI-generated) The questions should match the user's selected academic level and examination pattern. #### 7. Export Notes The generated notes should be downloadable as a professionally formatted PDF containing: * Cover page * Table of contents * Concise notes * Important diagrams * Highlighted key points * Summary section * Predicted examination questions #### 8. AI Quality The AI should ensure that: * The notes remain accurate. * No important concepts are omitted. * Complex topics are simplified according to the user's academic level. * The output is suitable for quick revision before examinations. ## Goal The goal of the application is to save students time by transforming lengthy study materials into concise, high-quality revision notes while also providing AI-generated examination questions and preserving important diagrams. The app should deliver personalized study material tailored to each student's educational level, making learning faster, easier, and more effective.

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