Inspiration

Haven was born from the realization that people experiencing housing insecurity face not just a shortage of resources, but a shortage of clarity confusing forms, language barriers, and fragmented systems that are hardest to navigate for those who need them most. We wanted to build the knowledgeable, patient, multilingual guide that no one experiencing homelessness currently has access to.

What it does

Haven is an iOS app that combines an AI assistant (powered by Claude) with a live resource map, a secure document vault, a housing pathway tracker, and multilingual support across 7 languages — giving users everything they need to find shelter, understand paperwork, generate case summaries, and connect with support groups, all in one place.

How we built it

We built Haven using SwiftUI for the iOS frontend, Claude (Anthropic API) for all AI features including document summarization, translation, case generation, and free-form housing Q&A, Apple MapKit for location and resource mapping, and local on-device storage via FileManager as a privacy-first alternative to Firebase while the app scales.

Challenges we ran into

  • Attempting interactive learning track but our idea failed costing us 4-5 hours. -Starting building this app with less than 3 hours ## Accomplishments that we're proud of -We achieved an app we didn't think was possible in a time 5 hours less than the competition. We are proud of coming back from nearly leaving the hackathon because we thought we would fail. ## What we learned We learnt that giving up is not an option if you want to succeed. Even with only three hours left we put our eyes on the prize and worked continuously. Hard work is is a must for success. ## What's next for Haven We plan to integrate live shelter availability data via the 211 API, add Firebase Authentication for cross-device sync, and build an OCR pipeline so users can photograph any document and get an instant plain-language AI summary — making Haven the most complete mobile safety net for people navigating housing insecurity.

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