LifeClone

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  Introduction

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  Authentication

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  Onboarding

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  Dashboard

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  Profile

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  Insights

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  Decisions

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  Results

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  Chat

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  Achievements

Inspiration

This project was inspired by the idea of creating a digital version of yourself that understands how you think, behave, and make decisions. We wanted to go beyond simple productivity tools and build something that reflects human habits and helps users improve through self-awareness. The concept of a clone that learns from your behavior became the core idea behind LifeClone.

What it does

LifeClone creates a digital clone of the user based on onboarding questions and behavior data. The app helps users plan their day, predict outcomes of decisions, and understand their habits. It includes a dashboard for tasks, an insights page with productive and unproductive paths, a chat feature to talk to the clone, and an achievements system to track progress and streaks. The clone uses AI to simulate how the user would think and respond in different situations.

How we built it

We built the app using Dart and structured it as a multi-page mobile application. Firebase was used for backend services, including authentication and data storage. We also integrated Firebase AI logic to access Gemini models, which power the clone’s predictions, insights, and chat responses. The onboarding system feeds user responses into this AI layer, allowing the clone to generate personalized outputs. Each feature was designed as a separate module and connected through shared user data. We also used AI tools during development to brainstorm feature ideas, refine the app’s design, and debug code efficiently, which helped speed up the overall development process.

Challenges we ran into

We faced challenges with Firebase AI logic, especially when integrating and properly configuring access to Gemini models. Ensuring that the AI responses were consistent and aligned with user behavior required careful structuring of prompts and data. We also struggled with configuring the Firebase database and making sure data flowed correctly between onboarding, tasks, and the clone system. Debugging these connections and maintaining smooth communication between the frontend and backend took significant effort.

Accomplishments that we're proud of

We are proud that we successfully built a working prototype of a digital clone system that adapts to user input and uses AI to simulate behavior. Integrating Gemini models through Firebase AI logic allowed us to create a more realistic and interactive clone experience. We also combined multiple complex features like predictions, task tracking, and conversational AI into one unified app.

What we learned

We learned how to structure a full-stack mobile application using Dart and Firebase, along with how to integrate AI models into a real product. Working with Gemini through Firebase AI logic taught us how to design prompts, manage responses, and personalize outputs. We also gained experience in handling user data, building behavior-based systems, and debugging complex integrations.

What's next for LifeClone

Next, we plan to improve the intelligence of the clone by refining how it uses Gemini models to generate more accurate and personalized predictions. We also want to enhance the AI chat system, add deeper analytics, and improve the visual representation of the clone. Future updates could include voice interaction, stronger real-time adaptation, and more advanced behavioral modeling to make the clone feel even more like the user.

Built With

• dart
• firebase
• gemini