# Project export: Future Rescue, The Forgetfulness Eliminating Learning Helper

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## Project metadata

- Hackathon: OpenAI Build Week
- Tagline: Future Rescue is an AI learning companion that analyses study notes, predicts what students are likely to forget, and creates personalised rescue missions before knowledge disappears.
- Devpost: https://devpost.com/software/future-rescue-the-learning-companoion
- GitHub: not linked
- Demo: https://future-rescue1.vercel.app/
- Video: https://www.youtube.com/embed/7pCmfr0f51U?enablejsapi=1&hl=en_US&rel=0&start=&version=3&wmode=transparent
- Team: contributor stats unavailable

## Devpost submission (written by the team)

### Overview

Students today have access to endless information, but having information available does not mean they will remember it when it matters. Many students spend hours studying yet still struggle because they forget key concepts before exams. We wanted to build an AI learning companion that moves beyond summarising notes. Future Rescue was inspired by the idea that AI should not only answer questions after a student is stuck, but proactively identify what they are likely to forget and help them reinforce it before it disappears. Future Rescue is an AI-powered learning companion that predicts what students are likely to forget and creates personalised rescue missions to strengthen their memory. Students provide their study notes, and Future Rescue: Extracts the key concepts from learning material Builds an understanding of the topics being studied Predicts which concepts are most likely to be forgotten Explains why those concepts are at higher risk Generates personalised rescue missions using learning techniques such as active recall and spaced repetition Instead of simply telling students what they studied, Future Rescue helps them understand what they need to remember next. Future Rescue was built using: Next.js with App Router TypeScript Tailwind CSS shadcn/ui components OpenAI models for the AI intelligence layer The application uses AI-powered workflows for: Concept extraction — turning unstructured study notes into structured learning concepts. Forgetting prediction — analysing concept difficulty, complexity, and relationships to estimate memory risk. Rescue mission generation — creating personalised learning actions designed to reinforce weak areas. Codex was used throughout development to accelerate implementation, create reusable components, debug issues, and iterate on the product architecture. One of the biggest challenges was deciding what information was actually useful for a student. A simple notes summariser was not enough — we needed to create something that could reason about learning and memory. Another challenge was designing AI outputs that felt trustworthy. Instead of making absolute predictions, we focused on explaining why a concept may be difficult and providing actionable recommendations. Building a complete AI workflow while keeping the experience simple and intuitive was also a major design challenge. We are proud that Future Rescue demonstrates a complete AI learning loop: Study notes → Concept understanding → Forgetting prediction → Personalised intervention The most important achievement is that the AI does not stop at analysis. It takes action by generating rescue missions that help students improve their retention. We also built a complete demo experience that allows users to see the value of the product within seconds. We learned that effective AI products are not just about generating responses — they are about understanding the user's goal and creating meaningful next steps. Throughout development, we learned how to combine AI reasoning with thoughtful product design, build reliable structured outputs, and use AI as both a development tool and the foundation of the product itself. Future Rescue has many opportunities to grow. Next steps include: Supporting more learning formats such as PDFs and lecture materials Creating long-term memory tracking for students Adapting predictions based on individual learning behaviour Adding calendar integration for timed rescue missions Building richer progress insights over time The long-term vision is for Future Rescue to become a proactive AI learning companion that helps every student remember what matters, exactly when they need it.

## README (from the GitHub repository)

No README available.

## Detected evidence (automated analysis)

No repository was indexed for this project. Claimed technologies below could not be checked against code.
- Next.js (technology) — claimed on Devpost, not found in the code
- Tailwind CSS (technology) — claimed on Devpost, not found in the code

## Codebase structure

No repository index available.

## Key source files

No repository index available; no source files included.