GnosisLens

GnosisLens helps travelers spot overpriced goods by combining price data and AI-driven review analysis, making trips safer, smarter, and building trust with fair local businesses

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Inspiration

  • Tourists often get overcharged abroad, causing stress and distrust.
  • We wanted a tool that helps travelers feel safe while supporting honest local businesses.

What it does

  • Detects scams by comparing item/service prices to local averages.
  • Uses AI sentiment analysis of reviews to generate a scam score.
  • Provides travelers with instant, trustworthy guidance.

How we built it

  • Frontend: Next.js and React
  • Backend: Node.js and Gemini API
  • AI: Gemini AI
  • Database/Auth: MongoDB

Challenges we ran into

  • Training sentiment models to understand short, casual reviews.
  • Tight hackathon timeline for integrating AI + UI.
  • Debugging database connectivity when making requests to MongoDB

Accomplishments that we're proud of

  • Built a functional MVP with real-time scam detection.
  • Integrated price + sentiment data into a single score.
  • Created a concept that protects tourists while uplifting fair businesses.

What we learned

  • Fast AI integration into a usable app.
  • How to merge structured (prices) and unstructured (reviews) data.
  • The value of trust-focused UX in travel apps.
  • Rapid prototyping under hackathon constraints.

What's next for GnosisLens

  • Improve AI to handle slang and regional nuances in reviews.
  • Build mobile-first, offline-ready version for travelers.
  • Containerize + deploy our application in order to be used by travelers around the world!
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