A React Native mobile application that evolves through 3 stages to provide intelligent contact management with AI-powered features.
- Inspiration / Source: Inspired by the iOS Contacts experience and modern AI assistants. The idea combines a clean, native-feeling contacts UI with AI capabilities similar to voice memo transcription (Whisper) and semantic organization/search (embeddings), plus suggestions like calendar-based relevance and introductions.
- How it was developed: Built iteratively in three demoable stages within a monorepo. Stage 1 delivered the core contacts app and local SQLite storage. Stage 2 added AI: Whisper transcription, GPT-powered summaries/tags, and hybrid search using embeddings and keyword signals. Stage 3 layers integrations (Calendar), collaboration (export/import demo), sharing, and suggestion features—keeping performance and offline-first behavior via local DB.
- Problem solved / Value: Reduces friction in remembering who to reach out to and why. Conversations become searchable, contacts are auto-tagged, and relevant people surface when planning meetings or drafting introductions. The result is faster recall, smarter discovery, and easier sharing of curated contact sets—without requiring users to manually organize everything.
contacto/
├── packages/
│ ├── shared/ # Shared types and utilities
│ └── database/ # Database layer (SQLite)
├── apps/
│ └── contacto-app/ # Main React Native application
└── README.md
Status: Complete
- ✅ Contact Import: Import contacts from device's contact list
- ✅ Contact Management: Add, edit, delete contacts
- ✅ Contact Display: Clean list and detail views
- ✅ Search Functionality: Search contacts by name, phone, email, or notes
- ✅ Local Storage: SQLite database for persistent storage
- ✅ Clean UI: Modern, intuitive interface with proper navigation
- Name (required)
- Phone number
- Email address
- Notes
- Created/Updated timestamps
- Frontend: React Native with Expo
- Navigation: React Navigation (Stack Navigator)
- Database: SQLite with expo-sqlite
- Contact Access: expo-contacts
- Architecture: Modular monorepo structure
-
Install Dependencies
cd apps/contacto-app npm install -
Configure OpenAI API (Required for Stage 2)
- Get an OpenAI API key from https://platform.openai.com/
- The app will prompt you to enter the API key when using AI features
- Required for: transcription, summarization, tagging, and semantic search
-
Start Development Server
npm start
-
Run on Device/Simulator
- Scan QR code with Expo Go app (iOS/Android)
- Press
ifor iOS Simulator - Press
afor Android Emulator
- OpenAI API Key: Required for AI features
- Audio Permissions: Automatically requested when recording
- Device Storage: For storing audio files and conversation data
- App.tsx: Main app with navigation setup
- ContactsListScreen: Contact list with search and import
- ContactDetailScreen: Individual contact details
- AddContactScreen: Create new contacts
- EditContactScreen: Edit existing contacts
- ContactService: Business logic layer
- ContactRepository: Database operations
The app includes:
- Mock data for development/testing
- Unit tests for core functionality
- Error handling and validation
Status: Complete
- ✅ Audio Recording: High-quality conversation recording with expo-av
- ✅ Whisper Integration: Automatic transcription using OpenAI Whisper API
- ✅ AI Summaries: Intelligent conversation summaries with key points and sentiment
- ✅ Automatic Tagging: AI-powered contact tagging based on conversation content
- ✅ Semantic Search: Advanced search using OpenAI embeddings and cosine similarity
- ✅ Voice Memo History: Complete conversation history per contact with playback
- ✅ Conversation Management: Full CRUD operations for conversations
- Record Conversation Screen: Professional recording interface with real-time duration
- Conversation Detail Screen: View transcriptions, summaries, tags, and audio playback
- Semantic Search Screen: Natural language search across all conversations
- Enhanced Contact Detail: Shows conversation history with summaries and tags
- Transcription: Whisper-powered audio-to-text conversion
- Summarization: GPT-3.5-turbo for intelligent conversation summaries
- Tagging: Automatic extraction of relevant contact tags and topics
- Semantic Search: Vector-based search using OpenAI embeddings
- Sentiment Analysis: Positive/neutral/negative sentiment detection
- Audio Service: Handles recording, playback, and file management
- AI Service: OpenAI integration for transcription, summarization, and embeddings
- Conversation Service: Business logic for conversation processing and management
- Database Layer: Extended SQLite schema for conversation storage
- Vector Search: Cosine similarity for semantic search results
Goal: Make the app collaborative and intelligent across multiple users.
- 🎯 Google Calendar Integration: Suggest contacts for events
- 🎯 Mass Send Contacts: Bulk sharing of filtered contact lists
- 🎯 Connection Suggestions: AI-powered introduction suggestions
- 🎯 Team Mode: Multi-user shared database with real-time sync
- Google Calendar API
- Real-time synchronization
- Team management system
- Advanced AI for connection suggestions
- Modular Architecture: Clear separation between UI, business logic, and data layers
- TypeScript: Full type safety throughout the application
- Error Handling: Comprehensive error handling and user feedback
- Testing: Unit tests for critical functionality
- Update shared types in
packages/shared/src/types.ts - Implement database layer in
packages/database/src/ - Create service layer in
apps/contacto-app/src/services/ - Build UI components in
apps/contacto-app/src/screens/ - Add tests and mock data
- Follow the existing code structure and patterns
- Add tests for new functionality
- Update documentation for new features
- Ensure TypeScript compliance
This project is part of a startup development initiative.