FinSight 💰

Privacy-first investment intelligence powered by local AI.

FinSight is a production-grade, full-stack portfolio management platform that delivers institutional-level financial insights — without ever sending your data to the cloud. By running LLMs locally via Ollama and a Retrieval-Augmented Generation (RAG) pipeline, FinSight guarantees 100% data sovereignty.

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✨ Features

• 🧠 Local RAG Pipeline — AI-powered portfolio analysis using locally hosted LLMs (Llama 3 / Mistral)
• 🔒 Full Data Sovereignty — No data sent to OpenAI, Anthropic, or any third-party AI service
• 🔐 JWT Authentication — Secure, stateless sessions for all API calls
• 🔑 Password Hashing — Bcrypt encoding for user credentials
• 📊 Portfolio Intelligence — Personalized financial insights from your own investment data
• 🌑 Dark Mode UI — Sleek, responsive interface built with Tailwind CSS and Framer Motion

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🏗️ Project Structure

FinSight/
├── backend/                   # Spring Boot (Java 21)
│   ├── src/main/java/         # Controller → Service → Repository layers
│   ├── src/main/resources/    # application.yml (config)
│   └── pom.xml                # Maven deps (Spring AI, JPA, Security)
├── frontend/                  # React + Vite
│   ├── src/                   # Components, Pages, Hooks
│   ├── tailwind.config.js     # Design tokens & dark mode
│   └── package.json           # Frontend deps (Framer Motion, Lucide)
├── docker-compose.yml
└── README.md

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🛠️ Tech Stack

Layer	Technology
Frontend	React.js, Vite, Tailwind CSS, Framer Motion, Lucide React
Backend	Spring Boot 3.4+, Spring AI, Spring Security (JWT)
Database	PostgreSQL + pgvector extension
AI Engine	Ollama (Llama 3 / Mistral) — runs fully locally

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🚀 Getting Started

Prerequisites

• Java 21 and Maven
• Node.js v18+ and npm
• PostgreSQL installed and running
• Ollama installed — get it here

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Step 1 — Set up the AI model

Pull your preferred local model:

ollama pull llama3
# or
ollama pull mistral

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Step 2 — Set up the Database

Create the database and enable the vector extension:

CREATE DATABASE wealthai_db;

\c wealthai_db

CREATE EXTENSION IF NOT EXISTS vector;

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Step 3 — Configure and Run the Backend

1. Update your database credentials in:

   backend/src/main/resources/application.yml
   

2. Start the backend server:

   cd backend
   mvn spring-boot:run

The API will be available at http://localhost:8080.

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Step 4 — Run the Frontend

cd frontend
npm install
npm run dev

Open the app at http://localhost:5173.

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🛡️ Security

• Local-only AI processing — your portfolio data never leaves your machine
• JWT-based authentication — stateless, secure API sessions
• Bcrypt password hashing — industry-standard credential protection

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📈 Roadmap

• Real-time Market Sync — live pricing via financial market APIs
• Advanced Analytics — asset correlation heatmaps and sector-wise risk breakdown
• AI Report Export — generate downloadable PDF investment summaries

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👤 Author

Rithik V Kumar Computer Science Engineering Student | Aspiring SDE & AI Engineer