Developing Uber Clone App - Ai Gemini integrated

Gemini API
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Uber Clone App Development with AI Gemini Integration – Looking for Technical Guidance

Hey everyone,

I’m currently part of a team at Suffescom Solutions, where we’re working on building a feature-rich UBER CLONE APP with integrated AI capabilities using Gemini (via Vertex AI/Gemini API).

We’re aiming to add intelligent features like:

  • Real-time chat support between drivers and riders

  • Predictive ETA adjustments based on traffic/context

  • Smart route optimization with real-time AI insights

  • Context-aware voice interactions

Our stack includes:

  • Frontend: Flutter

  • Backend: Node.js with Firebase (Auth, Firestore)

  • Maps: Google Maps SDK/API

  • AI: Gemini API (experimental phase)

While we’ve made good progress on the base functionality, we’re running into a few roadblocks on the Gemini AI side:

  1. Structuring prompts for real-time use (like contextual ride queries)

  2. Handling Gemini’s streaming responses efficiently in the app

  3. Aligning AI output with dynamic geo-location data

  4. Cost-performance balance when scaling AI requests across multiple riders/drivers

We’re approaching this from both an R&D and product perspective — trying to make something both smart and scalable. I’d really appreciate it if anyone has:

  • Experience integrating Gemini or similar LLMs into mobile apps

  • Tips on using AI in real-time, latency-sensitive systems

  • Open-source examples or best practices you’ve come across