Inspiration
Getting ready to leave involves several small decisions: checking the weather, planning travel, remembering what to bring, and preparing for the visit. That inspired ReadyFor, an AI pre-departure assistant that brings those decisions into one simple experience.
What it does
ReadyFor turns an activity and trip details into a practical plan: when to leave, how to get there, what to wear, what to bring, and what to do beforehand. It supports driving, transit, and walking, with checkable packing lists, calendar reminders, email drafts, and searchable local history. Government-service visits can include official-source research, with unresolved details clearly labeled.
How it was built
ReadyFor uses Strands Agents and Amazon Nova through Amazon Bedrock for everyday preparation advice. A Python FastAPI backend coordinates Amazon Location Service routing, Open-Meteo weather, and departure calculations. A separate Nova research flow uses Tavily to discover and read relevant websites. The frontend uses React Native, Expo, and TypeScript.
Challenges encountered
Key challenges included model access and quotas, reliable departure timing, incomplete source information, and presenting detailed plans clearly. Source review, partial-result handling, and expandable sections helped address these challenges.
Accomplishments
ReadyFor brings travel, weather, and preparation together in a working local web application. The project uses an Expo starter, open-source dependencies, and AI coding assistance.
What was learned
Useful agents need reliable tools and clear responsibilities: AI for contextual advice, services for real-world data, and code for calculations.
What’s next for ReadyFor
Next steps include mobile testing, public hosting, synced history, improved research coverage, and proactive calendar integration.
Before you walk out the door, ReadyFor helps you feel prepared.
Built With
- amazon
- bedrock
- expo.io
- fastapi
- open-meteo-forecast
- poetry
- python
- react-native
- strands
- tavily
- typescript
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