AI-Driven Behavioral Analysis App Development
Budget: $30 – $250 NZD
AI Behavioral System Development (Flutter / FlutterFlow + OpenAI + API Integration)
Project Overview:
We are developing an AI-powered behavioral analysis and prediction application that works like a human decision/navigation system.
The system is built around two core API endpoints:
Ask Endpoint → Handles user queries and returns AI-generated responses
Analyze Endpoint → Processes user data and returns behavioral insights, patterns, and predictions
The goal is to first fully stabilize and optimize these endpoints and then use their outputs to build multiple intelligent, user-facing features within the same system.
Scope of Work (Complete Project):
1. Core API Integration & Debugging
Fix and optimize Ask & Analyze endpoints
Resolve OpenAI (GPT) API issues (no response, failed calls, incorrect configuration)
Ensure proper request/response flow
Structure and clean API outputs for further use
2. System Understanding & Data Flow Mapping
Analyze how the system behaves end-to-end
Understand what inputs are being sent and what outputs are generated
Identify how outputs can be reused and categorized for features
3. Feature Development (Built on Endpoint Outputs)
All features will be developed using outputs from Ask & Analyze endpoints and implemented as clickable UI options or predefined logic flows.
Key features include:
Daily Reality Report
Emotional forecast, risk alerts, opportunity timing
Future Self Simulation
Predict user outcomes based on current behavior
Pattern Exposure Mode
Detect and display behavioral/self-sabotage patterns
AI Therapist Mode
Conversational AI with emotional analysis
Relationship Analyzer
Compare two users → compatibility & conflict insights
Timing Engine
Best/worst timing for decisions and actions
Habit Reprogramming System
Detect → break → replace behavioral loops
Gamification System
Clarity score, streaks, progress tracking
Shadow Mode (Dark Mode Insight Feature)
Hidden traits, ego patterns, risk behaviors
Viral Sharing Features
Shareable outputs like predictions and personality insights
4. Custom Output Handling & Logic
Categorize and customize outputs based on feature selection
Modify prompts / backend logic if needed
Ensure each feature produces meaningful and structured responses
5. Backend & Deployment
Work with Railway for backend configuration
Update environment variables, API settings, and integrations
Ensure stable deployment and performance
Tech Requirements:
Strong experience in Flutter / FlutterFlow
API integration (REST APIs)
OpenAI API (GPT-4 or latest)
Backend handling (Railway or similar)
Experience with AI-based systems is a plus
Access:
Full backend access (Railway) will be provided
OpenAI API keys will be shared
Confidentiality:
This project involves a unique algorithm and concept.
Strict confidentiality is required. No sharing or reuse of any part of this system.
Final Goal:
Deliver a fully functional AI behavioral platform where:
Ask & Analyze endpoints work perfectly
Outputs are structured and reliable
Multiple intelligent features are built on top of these outputs
System is scalable and production-ready.
Budget: $70 NZD
Project Overview:
We are developing an AI-powered behavioral analysis and prediction application that works like a human decision/navigation system.
The system is built around two core API endpoints:
Ask Endpoint → Handles user queries and returns AI-generated responses
Analyze Endpoint → Processes user data and returns behavioral insights, patterns, and predictions
The goal is to first fully stabilize and optimize these endpoints and then use their outputs to build multiple intelligent, user-facing features within the same system.
Scope of Work (Complete Project):
1. Core API Integration & Debugging
Fix and optimize Ask & Analyze endpoints
Resolve OpenAI (GPT) API issues (no response, failed calls, incorrect configuration)
Ensure proper request/response flow
Structure and clean API outputs for further use
2. System Understanding & Data Flow Mapping
Analyze how the system behaves end-to-end
Understand what inputs are being sent and what outputs are generated
Identify how outputs can be reused and categorized for features
3. Feature Development (Built on Endpoint Outputs)
All features will be developed using outputs from Ask & Analyze endpoints and implemented as clickable UI options or predefined logic flows.
Key features include:
Daily Reality Report
Emotional forecast, risk alerts, opportunity timing
Future Self Simulation
Predict user outcomes based on current behavior
Pattern Exposure Mode
Detect and display behavioral/self-sabotage patterns
AI Therapist Mode
Conversational AI with emotional analysis
Relationship Analyzer
Compare two users → compatibility & conflict insights
Timing Engine
Best/worst timing for decisions and actions
Habit Reprogramming System
Detect → break → replace behavioral loops
Gamification System
Clarity score, streaks, progress tracking
Shadow Mode (Dark Mode Insight Feature)
Hidden traits, ego patterns, risk behaviors
Viral Sharing Features
Shareable outputs like predictions and personality insights
4. Custom Output Handling & Logic
Categorize and customize outputs based on feature selection
Modify prompts / backend logic if needed
Ensure each feature produces meaningful and structured responses
5. Backend & Deployment
Work with Railway for backend configuration
Update environment variables, API settings, and integrations
Ensure stable deployment and performance
Tech Requirements:
Strong experience in Flutter / FlutterFlow
API integration (REST APIs)
OpenAI API (GPT-4 or latest)
Backend handling (Railway or similar)
Experience with AI-based systems is a plus
Access:
Full backend access (Railway) will be provided
OpenAI API keys will be shared
Confidentiality:
This project involves a unique algorithm and concept.
Strict confidentiality is required. No sharing or reuse of any part of this system.
Final Goal:
Deliver a fully functional AI behavioral platform where:
Ask & Analyze endpoints work perfectly
Outputs are structured and reliable
Multiple intelligent features are built on top of these outputs
System is scalable and production-ready.
Budget: $70 NZD