AI Business Analyst 📊

An AI-powered Business Intelligence platform that allows business users to upload datasets, automatically generate insights, analyze trends, forecast future performance, detect anomalies, and ask natural language questions about their data.

Features

• 🔐 Authentication — Register, login, JWT-based auth
• 📁 Multiple Projects — Organize analyses by project
• 📤 Dataset Upload — CSV and XLSX file support
• 📊 Data Profiling — Auto-detect data types, missing values, duplicates
• 🏥 Data Quality — Health score and quality metrics
• 📈 KPI Detection — Auto-identify revenue, profit, orders, CTR, etc.
• 📉 Analytics Dashboard — Trends, segments, top/bottom performers
• 🤖 AI Insights — Ask business questions in natural language
• 🔮 Forecasting — Predict future metrics using Linear Regression
• ⚠️ Anomaly Detection — IQR-based outlier detection
• 📄 Executive Reports — PDF generation with AI-written content

Architecture

graph TD
    %% Nodes
    User((Business User))
    
    subgraph "Frontend (React + Vite)"
        UI[UI Components & Dashboards]
        APIClient[Axios API Client]
    end
    
    subgraph "Backend (Node.js + Express)"
        Router[API Routes]
        Controllers[Controllers]
        Services[Business Logic Services]
    end
    
    subgraph "Machine Learning (Python)"
        Forecast[Forecast Engine]
        Anomaly[Anomaly Detection]
    end
    
    subgraph "Database (MongoDB)"
        DB[(ai-business-analyst DB)]
    end
    
    subgraph "External Services"
        LLM[NVIDIA: Nemotron 3 Ultra via OpenRouter]
    end

    %% Interactions
    User -->|Uploads Data & Asks Questions| UI
    UI <-->|HTTP REST| APIClient
    
    APIClient <-->|API Calls| Router
    Router --> Controllers
    Controllers --> Services
    
    Services <-->|CRUD Operations| DB
    
    Services -->|Spawn Process| Forecast
    Services -->|Spawn Process| Anomaly
    
    Services <-->|Generate Insights & Reports| LLM

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Tech Stack

Layer	Technologies
Frontend	React, Vite, Ant Design, Recharts, Axios
Backend	Node.js, Express.js
Database	MongoDB
Auth	JWT, bcrypt
AI	NVIDIA: Nemotron 3 Ultra (via OpenRouter)
ML	Python, scikit-learn, pandas, numpy
Reports	PDFKit

Quick Start

Prerequisites

• Node.js 18+
• MongoDB (local or Atlas)
• Python 3.8+ (for ML features)

1. Clone and Install

# Install backend dependencies
cd backend
npm install

# Install frontend dependencies
cd ../frontend
npm install

# Install Python ML dependencies
cd ../backend
pip install -r ml/requirements.txt

2. Configure Environment

Edit backend/.env:

MONGO_URI=mongodb://localhost:27017/ai-business-analyst
JWT_SECRET=your_secret_key_here
PORT=5001
OPENROUTER_API_KEY=your_openrouter_api_key_here

3. Run the App

# Terminal 1: Start backend
cd backend
npm run dev

# Terminal 2: Start frontend
cd frontend
npm run dev

Open http://localhost:5173 in your browser.

4. Sample Data

Sample CSV files are available in backend/sample-data/:

• sales_data.csv — Sales by region, product, category
• marketing_data.csv — Campaign performance metrics
• customer_data.csv — Customer segments and retention
• inventory_data.csv — Stock levels and unit sales
• finance_data.csv — Department revenue, expenses, budget

API Endpoints

Method	Endpoint	Description
POST	/api/auth/register	Register new user
POST	/api/auth/login	Login
GET	/api/auth/me	Current user
POST	/api/projects	Create project
GET	/api/projects	List projects
DELETE	/api/projects/:id	Delete project
POST	/api/projects/:id/upload	Upload dataset
GET	/api/projects/:id/datasets	List datasets
GET	/api/projects/:id/analytics	Full analytics
GET	/api/projects/:id/kpis	KPI detection
GET	/api/projects/:id/segments	Segment analysis
GET	/api/projects/:id/forecast	Forecasting
POST	/api/projects/:id/ask	Ask AI question
POST	/api/projects/:id/generate-insights	Auto insights
POST	/api/projects/:id/report	Generate report
GET	/api/projects/:id/report	List reports

Project Structure

ai-business-analyst/
├── backend/
│   ├── config/db.js
│   ├── controllers/
│   ├── middleware/authMiddleware.js
│   ├── ml/forecast.py, anomalyDetection.py
│   ├── models/User, Project, Dataset, Report
│   ├── routes/
│   ├── services/
│   ├── sample-data/
│   └── server.js
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   ├── context/AuthContext.jsx
│   │   ├── pages/
│   │   ├── services/api.js
│   │   └── App.jsx
│   └── index.html
└── README.md

Screenshots