AI Inventory Intelligence Agent

An intelligent AI-driven assistant designed to revolutionize how businesses manage and interact with their inventory data. This system leverages Large Language Models (LLMs) to transform complex, unorganized inventory files into a conversational knowledge base.

This project is currently in its MVP (Minimum Viable Product) stage, focusing on the core RAG architecture and autonomous data retrieval.

Key Features & Architecture:

- RAG Pipeline: Implemented a robust Retrieval-Augmented Generation system using LangChain to bridge the gap between private inventory data and LLMs.

- Autonomous Agent: Built an intelligent agent capable of interpreting queries and retrieving specific data points from structured/unstructured files.

- Interactive Dashboard: Developed a clean, user-friendly interface using Streamlit to facilitate seamless interaction between the user and the AI agent.

- Intelligent Analysis: Automates the process of extracting, summarizing, and presenting inventory metrics without the need for manual database querying.

Technologies Used:

- Python

- LangChain / LangGraph

- Large Language Models (LLMs)

- Streamlit

- Vector Databases