StudyMate AI is an AI-powered study assistant built as part of the Decoding Data Science (DDS) – Building AI Applications Challenge 2026.
The project focuses on helping students understand academic concepts more clearly through simple explanations, structured learning points, and study guidance.
Students often struggle with:
- Understanding complex or abstract topics
- Lack of structured study guidance
- Feeling overwhelmed or demotivated during self-study
StudyMate AI provides:
- Simple, beginner-friendly explanations
- Key learning points in a clear, structured format
- Practical study tips and learning strategies
- Motivational support to encourage consistent studying
- Users enter a study-related question via a chat interface
- The AI processes the input using a prompt-driven workflow
- Responses are generated with clear explanations and supportive guidance suitable for beginners
- AIRIA – No-Code AI Platform (Chat Widget & Prompt Workflow)
- Prompt Engineering – Core application logic
- GitHub – Documentation and proof-of-work
- AIRIA environment configured successfully
- Chat-based AI workflow implemented and tested
- Core prompt logic (“brain” of the app) created
- Initial baseline testing completed using sample study questions
- Project documentation updated
- “Explain recursion like I’m a beginner”
- “Give me study tips for computer science exams”
- “Summarize photosynthesis in simple words”
- “How can I study effectively with limited time?”
- "What is the difference between hardware and software in simple terms?"
- "Explain what an operating system does using an easy example."
- "What is an exam revision plan for one week?"
- "Explain the concept of variables as if I have never coded before."
- "How can I stay focused while studying at home?"
- "What are effective note-taking methods for students?"
- Improve prompt quality and response consistency
- Add a structured study-planning feature
- Enhance output formatting and user experience
- Prepare demo video and final submission assets
- Refined the system prompt based on testing results
- Evaluated AI responses for clarity, structure, and beginner-friendliness
- Added safety and validation rules within the no-code workflow
- Improved response consistency through prompt iteration
- Integrated the AI logic with a user-facing chat interface using AIRIA
- Verified end-to-end interaction from user input to AI response
- Improved system prompt for better UX, clarity, and validation handling
- Tested the interface with multiple user scenarios and edge cases
- Reviewed input handling and clarified accepted question formats
- Added safety and validation logic through system prompt constraints
- Verified API keys are securely managed within the platform (no secrets in repo)
- Improved response consistency and clarity
- Cleaned documentation and usage notes
- Accepts open-ended study-related questions
- Provides clear, beginner-friendly explanations with simple examples
- Offers practical study tips and motivational support
- Designed for non-technical users with a chat-based interface
- Platform: AIRIA (No-Code AI Agent)
- Interface: Chat Widget + API
- Status: Published and live (v2.0.0)
- Demo URL: https://fsafva13-coder.github.io/studymate-ai/
- Screenshots of the working agent and interface included in the repository
- Explainer video recorded describing the workflow, interface, and functionality
- GitHub used as a central hub for documentation and proof-of-work
This project prioritizes clarity, usability, and responsible AI behavior. The focus was on delivering a stable, supportive learning experience rather than implementing complex engineering features.
All screenshot evidence supporting Day 2–7 progress is available in the screenshots/ directory.
This project is being developed as part of the Building AI Applications Challenge 2026, organized by Decoding Data Science (DDS).