INFENGINE — AI Decision Intelligence Platform

Transform complex decisions into confident actions with explainable AI. Evaluates choices across 14 categories with multi-model reasoning, interactive flowcharts, risk audits, and multi-page PDF consulting briefs.

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🌟 Overview

INFENGINE is an enterprise-grade dark-themed Decision Intelligence platform. Instead of asking AI "What should I do?", INFENGINE evaluates "Why is one decision objectively stronger than another?" through systematic scoring, timeline forecasting, scenario simulations, and cognitive bias detection.

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📖 Example Decision Queries & Scenarios

To help you get started, here are real-world scenarios you can input into INFENGINE:

Domain	Example Query	Options Evaluated	Sensitivity Focus
Career Pivot	"Should I transition to a machine learning engineering role or stay as a backend developer?"	Machine Learning Specialist vs. Senior Backend Engineer	Time Investment vs. Future Stability
Startup / Business	"Should we build our database scaling architecture on-prem or migrate to cloud serverless?"	AWS Aurora Serverless vs. Self-hosted PostgreSQL Cluster	Budget Range vs. Scalability
Education	"Should I pursue an MBA from a top-tier school or double down on self-directed entrepreneurship?"	Top-Tier MBA vs. Launching Bootstrap Startup	Opportunity Cost vs. Learning Curve
Real Estate / Life	"Is it financially and personally sound to buy a house now or keep renting and invest the savings?"	Purchasing Real Estate vs. Renting & Stock Investment	Risk Tolerance vs. Lifestyle Impact

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💡 Key Features

🧠 1. Multi-Model AI Reasoner

• Select between OpenAI (GPT-4o), Claude (3.5 Sonnet), and Google (Gemini).
• Automatic Demo Mode fallback: works out-of-the-box with simulated evaluations if keys are missing.

📊 2. Interactive Results Dashboard

• Winner Card & Confidence Gauge: Instant visualization of the recommended choice with score differentials.
• Spider/Radar Matrix: Multi-dimensional radar comparison mapping options across all 14 criteria.
• Decision Tree Flow: Interactive node-based flowchart (powered by React Flow) illustrating decision path outcomes.
• Timeline Projections: 10-year forecasts comparing option evolution.

🎛️ 3. Sensitivity & Scenario Playground

• Variable Sliders: Dynamically change weights (Budget, Risk, Time) and watch option scores recalculate live.
• Scenario Simulations: Model external shocks (Market Downturns, Competitor Shifts) and gauge immediate impact.

📄 4. Consultant-Grade PDF Exporter

• Generate a beautiful, multi-page 6-page PDF Report featuring:
  • Executive Summary with highlighted recommendations.
  • Side-by-side options comparison columns.
  • Multi-dimensional Radar Chart & vector scoring bar charts.
  • Timeline forecasts, risk mitigations, bias audits, and evidence chains.

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⚙️ 14 Evaluation Dimensions

Decisions are mathematically evaluated across:

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📂 Repository Structure

├── public/                 # Static assets and icons
├── src/
│   ├── app/                # Pages, API endpoints, global styles
│   │   ├── api/analyze     # Model serverless call routers
│   │   ├── results         # Dashboard components and page
│   │   ├── methodology     # AI reasoning description
│   │   └── about           # Project details page
│   ├── components/
│   │   ├── dashboard       # Visualizers (Charts, Sliders, React Flow Tree)
│   │   └── layout          # Header Navbar & Footer layouts
│   └── lib/                # PDF Exports, Mock Engines, and Zustand Store
├── render.yaml             # Render Blueprint configuration
└── package.json            # Module dependencies

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🚀 Getting Started

Prerequisites

• Node.js (v18.0.0 or higher)

1. Install Dependencies

npm install

2. Configure Environment Variables

Create a .env.local file in the root directory:

# Google (Free tier key available via Google AI Studio)
GOOGLE_GENERATIVE_AI_API_KEY=your_gemini_key

# OpenAI
OPENAI_API_KEY=your_openai_key

# Anthropic Claude
ANTHROPIC_API_KEY=your_claude_key

💡 No Keys? The app runs automatically in fully-featured Demo Mode using custom mock engines.

3. Run Development Server

npm run dev

Open http://localhost:3000 in your browser to view the platform.

4. Build for Production

npm run build
npm run start

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📄 License

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