NeoPIP — an AI-powered wellness iOS app that integrates psychological, behavioral, and physical data to deliver personalized insights through a PIP Score.

한국어

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Table of Contents

• Background & Motivation
• Key Features
• Architecture
• Installation
• Usage
• Project Structure
• Related Projects
• Current Status
• Roadmap
• Contributing
• License

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Background & Motivation

Most wellness apps track a single dimension — steps, sleep, or mood — in isolation. NeoPIP takes a holistic approach: it combines psychological state, behavioral patterns, and physical metrics into a single PIP Score that reflects overall well-being.

The platform is designed as the user-facing layer of the neomakes agent ecosystem. Sensor data from NeoSense feeds into behavioral models from human-wm, which in turn powers NeoPIP's personalized wellness intelligence.

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Key Features

• PIP Score — Unified wellness metric combining psychological, behavioral, and physical data
• AI Deep Insight Journaling — Structured journaling with AI-powered pattern recognition
• MVVM Architecture — Clean separation with 9 ViewModels (Login, Onboarding, Home, Write, Insight, InsightStory, Goal, Status, ProgramStory)
• Design System — Black & Platinum base with accent colors (Amber Flame, Tiger Flame, French Blue)
• Firebase Backend — Firestore for data persistence, Cloud Functions for analysis
• Privacy-First Analytics — On-device processing where possible, anonymized data collection
• Goal Tracking — Set, track, and reflect on personal wellness goals
• Insight Visualization — Interactive orb visualization and dashboard for data exploration

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Architecture

graph TD
    subgraph UI ["UI Layer (SwiftUI)"]
        A[Views] -- user actions --> B[ViewModels]
    end

    subgraph Logic ["Business Logic"]
        B -- data requests --> C[Services]
        C -- data models --> D[Models]
    end

    subgraph Backend ["Backend (Firebase)"]
        C -- CRUD / Functions --> E[Firestore + Cloud Functions]
        E -- data / results --> C
    end

    subgraph State ["State Management"]
        C -- updated models --> B
        B -- "@Published" --> A
    end

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View Structure

Screen	ViewModel	Description
LaunchView	—	App launch and authentication gate
OnboardingView	OnboardingViewModel	First-run user setup flow
HomeView	HomeViewModel	Main dashboard with PIP Score and gems
WriteView	WriteViewModel	Journal entry creation with cards
InsightView	InsightViewModel	Data visualization and orb display
InsightStoryView	InsightStoryViewModel	AI-generated insight narratives
GoalView	GoalViewModel	Goal setting and progress tracking
StatusView	StatusViewModel	Profile, stats, achievements, values
SettingsView	—	App configuration

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Installation

Prerequisites

• macOS with Xcode 15.0+
• iOS 17.0+ device or simulator
• Firebase project (you provide your own credentials)

Setup

1. Clone the repository:

   git clone https://github.com/neomakes/neopip.git
   cd neopip

2. Set up Firebase:

   • Create a Firebase project at console.firebase.google.com
   • Enable Firestore and Authentication
   • Download GoogleService-Info.plist
   • Place it in PIP_Project/PIP_Project/

   Important: GoogleService-Info.plist is gitignored. Never commit Firebase credentials.

3. Open PIP_Project/PIP_Project.xcodeproj in Xcode.

4. Select your Development Team under Signing & Capabilities.

5. Build and run (Cmd+R) on a simulator or connected device.

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Usage

First Run

1. Launch the app — you'll see the onboarding flow
2. Complete the initial questionnaire to establish your baseline PIP Score
3. Navigate the main tabs: Home, Write, Insight, Goal, Status

Journaling

1. Tap Write to create a new journal entry
2. Select your activity type and mindset (including custom inputs)
3. The app processes your entry against historical patterns

Insights

1. Tap Insight to view your data visualization
2. The orb visualization reflects your current wellness state
3. Tap into stories for AI-generated behavioral insights

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Project Structure

neopip/
├── 01_Planning/               # Product requirements, research, user stories
│   ├── PRD/
│   ├── Research/
│   └── User_Stories/
├── 02_Design_Assets/          # Brand guide, icons, Figma exports
│   ├── App_Icons/
│   ├── Branding/
│   └── Figma_Exports/
├── 03_Development/            # ML model development and experiments
├── 04_Distribution/           # App Store metadata, release notes, screenshots
│   ├── AppStore_Metadata/
│   ├── Release_Notes/
│   └── Screenshots/
├── PIP_Project/               # iOS app source code (Xcode project)
│   └── PIP_Project/
│       ├── App/               # App entry point
│       ├── Models/            # Data models
│       ├── ViewModels/        # MVVM view models (9 total)
│       ├── Views/             # SwiftUI views
│       │   ├── Home/
│       │   ├── Insights/
│       │   ├── Status/
│       │   └── Shared/
│       ├── Services/          # Firebase and business logic services
│       └── Resources/         # Assets, fonts
├── assets/                    # Repository assets (banner, etc.)
├── LICENSE
├── CONTRIBUTING.md
├── CODE_OF_CONDUCT.md
└── README.md

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Related Projects

• human-wm — VRAE-based human behavior world model. Serves as the ML backbone for NeoPIP's wellness intelligence, generating personalized behavioral predictions.
• NeoSense — Multi-modal sensor logging. Provides raw physical data that feeds into the NeoPIP data pipeline.
• neocog — On-device agentic inference kernel. Future integration point for local AI processing.

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Current Status

On Hold — Frontend is approximately 80% complete. Development paused to focus on the neocog/NeoTOC ecosystem.

What's Built

• SwiftUI frontend: onboarding, home dashboard, journal (write), insight visualization, goal tracking, status/profile
• Firebase integration: basic Firestore setup, authentication flow
• Design system: Black & Platinum theme with accent colors, custom components
• Privacy-first analytics notebook and guide

What's Not Connected

• ML integration: human-wm is the research backend but is not yet wired to the app
• PIP Score calculation: designed but not fully implemented with real ML inference
• Cloud Functions: planned but not deployed

Why Paused

The wellness app market became increasingly crowded. Development focus shifted to the neocog agent kernel and NeoTOC platform, which represent a more differentiated technical contribution. NeoPIP remains valuable as a demonstration of end-to-end iOS + AI + wellness domain capability.

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Roadmap

• Connect human-wm for real behavioral predictions
• Implement PIP Score calculation with ML inference
• Deploy Firebase Cloud Functions for backend analysis
• Complete remaining UI screens (~20%)
• Beta testing with real user data

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Contributing

See CONTRIBUTING.md for guidelines.

This project follows the Code of Conduct.

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License

This project is licensed under the MIT License — see LICENSE for details.