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07[Archived]

ETA+

Conversational AI pipeline and safety check-in system.

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Summary

A safety check-in app that tracks a trip's ETA in real time and automatically alerts a trusted contact if you don't check in, using voice and facial verification instead of a simple "I'm safe" button.

Problem you're solving

Location-sharing safety apps rely on the at-risk person remembering to tap "I'm safe," which fails exactly when it matters most โ€” and text-based check-ins are easy to fake under duress.

Target user

People commuting or traveling alone who want a trusted contact to know they arrived safely, without manually managing check-ins.

Competitors

Life360 and bSafe offer real-time location sharing, but their check-ins are manual and don't verify it's actually the user confirming safety.

Insight

A check-in is only reassuring if you can trust who sent it โ€” voice and face verification turn a simple tap into an actual identity confirmation.

Solution

Combines Google Maps ETA tracking with automated voice check-in calls and facial recognition for identity verification, alerting a trusted contact automatically if a check-in is missed.

  • Next.js
  • Python
  • Supabase
  • Retell AI
  • Google Maps API

Distribution

Built as a hackathon project โ€” a conversational AI pipeline and safety system; now archived, without further public distribution.

Adapting to user feedback

Feedback came from judges and teammates during the event rather than live users โ€” the biometric-verification layer was added specifically in response to judges asking how the system would know it was really the trusted person checking in.