AI-Powered Bookkeeping & Demand Forecasting

A smart bookkeeping system leveraging AI to extract financial insights and forecast demand dynamically.

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🔍 Overview

This project is an AI-powered bookkeeping and demand forecasting system designed to automate financial record-keeping and optimize inventory management. It extracts key financial entities from transactions and predicts product demand based on historical sales data.

✨ Key Functionalities:

• Automatic entity extraction from transaction statements
• Demand forecasting based on sales trends
• Real-time alerts for low stock levels
• Simple API endpoints for seamless integration

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🖼️ Preview

Here are some images related to the project:

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🚀 Features

• Transaction Data Extraction
  Extracts key details like customer names, item quantities, and prices from financial records.

  curl -X POST http://127.0.0.1:5000/extract -H "Content-Type: application/json" -d "{\"text\": \"John Doe bought 2 apples for $5\"}"

  {"CustomerName":"John Doe","ItemName":"apples","ItemQuantity":"2","Price":"5"}

• Natural Language Processing for Entity Recognition
  Recognizes actionable insights from textual inputs.

  curl -X POST "http://127.0.0.1:5000/extract_entities" -H "Content-Type: application/json" -d "{\"text\":\"apples less than 50 rs\"}"

  {"action":"less","object":"apples","range":"50"}

• Demand Forecasting
  Uses historical data to predict when stock levels are running low and suggests reorder points.

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🛠️ Installation

Prerequisites

• Docker installed on your system

Run the Project

docker-compose up --build 
docker-compose up 

API Execution

# Replace with actual endpoint and input data
curl -X POST <api_endpoint> -H "Content-Type: application/json" -d '<input_data>'

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👨‍💻 Contributors

Souvik Mahanta

Made with ❤ by GDSC-VIT

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