AcePrep AI
Building a comprehensive AI-powered exam study companion. Supporting image-based question solving, dynamic custom quiz generating, and curriculum-grounded academic intelligence.
The Challenge
Students preparing for standardized testing face three major problems: getting reliable, instant answers to complex questions, practicing with custom structures that adapt, and recognizing conceptual weaknesses early. Standard study solutions are linear and passive, and don't provide step-by-step guidance tailored to the exam syllabus criteria.
Core Project Objectives
- Build a fast, OCR-powered Q&A engine that extracts and solves questions from image uploads.
- Engineer a dynamic quiz session generator configurable by subject, difficulty, and length.
- Implement an academic intelligence layer that aligns output solutions with syllabus mark schemes.
- Develop a Flutter-based dashboard for content moderation, analytics tracking, and flagged response review.
Solution Architecture
We designed an integrated student and administrator ecosystem:
OCR Q&A Engine
Processes uploaded textbook images or typed questions. Generates a structured response featuring the final answer, step-by-step logic deductions, and automatic subject categorization.
Dynamic Quiz Engine
Generates custom practice sessions on the fly, providing performance summaries (score, correct vs incorrect counts) and allowing student bookmarking.
Flutter-Based Admin Dashboard
Provides administrative moderation workflows to configure categories, review usage metrics, audit AI answers, and approve/flag content pipelines.
Academic & AI Customization
Answers are grounded in actual exam context, avoiding generic LLM hallucinations:
- Past Paper Ingestion: Syllabus codes, marking guides, and historical questions are parsed and stored in Pinecone to verify guidelines.
- Handwritten Answer Evaluation: Vision endpoints grade handwritten answer papers uploaded by students against target mark schemes, providing clear improvements.
Business Outcomes
2x Faster Learning Velocity
Dynamic target practice and structured explanations reduced concept blockages, increasing readiness speeds.
Flutter Cross-Platform Operations
Admin moderation workflows compiled natively for web and desktop, cutting support response overhead.
Technology Stack
System Architecture Flow
Extracts handwritten equations, text, or figures from uploaded images or user prompts.
Queries syllabus indices, marking schemes, and past paper logs to ground the answer context.
AI structures detailed logic pathways, final answers, and concept explanations.
Flags inappropriate or low-confidence outcomes to the Flutter administrator feed for review.
AcePrep AI Q&A Engine
Simulated view of the image submission step and syllabus-aligned evaluation.
• Dynamic Sessions: 12 Completed
• Bookmarks: 4 Questions Saved
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