Contact person: Business Client

Phone:Show

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Location: Lahore, Pakistan

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I need a lean but functional mobile prototype that showcases how AI-driven product recommendations can personalize the user journey.

Here’s what I’m after:
• A minimal cross-platform build that runs on both iOS and Android—React Native, Flutter, or another lightweight framework is fine as long as it compiles cleanly for each store.
• A simple onboarding screen to collect a few preference signals (or pull demo data).
• A small, embedded machine-learning model—cloud or on-device—that returns tailored product suggestions in real time. Off-the-shelf libraries such as TensorFlow Lite, Core ML, or scikit-learn converted models are acceptable; the goal is to prove the recommendation flow works.
• A basic feed or carousel UI that lists the recommended items and updates when the user changes their inputs or browsing behavior.
• Clear setup instructions and commented code so I can run, retrain, or extend the model later.

Keep this scoped as a proof-of-concept: no deep analytics dashboards or full checkout process at this stage, just the core recommendation experience running smoothly on both platforms." (client-provided description)