Intelligent Document Management & AI Assistant for Automotive Manufacturing

About the Project

Industry: Automotive Manufacturing

Solution Type: Document AI Assistant

AI Technology: OpenAI GPT-4, LangChain, AWS Rekognition

Other Technologies: NodeJS, ReactJS, AWS, Qdrant

Integrations: Document Processing, Image Analysis, Access Management

Problem Statement

Challenge Description

A major automotive parts manufacturer needed to secure proprietary production documents while enabling efficient knowledge sharing across engineering teams. Traditional file-sharing methods posed risks, and knowledge retrieval was time-consuming, often requiring senior staff involvement.

Key Pain Points

Risk of intellectual property leakage through direct file downloads.
Excessive time spent by senior engineers on routine queries.
Difficulty tracking document access and usage.
Challenges in transferring knowledge to new team members.
Managing complex visual technical documentation.

Solution Overview

We developed an AI-powered document assistant for automotive manufacturing that combines advanced document processing, security, and knowledge retrieval, ensuring secure and efficient access to technical documentation and knowledge sharing across teams.

High-Level Architecture

Document Processing Layer: Multi-format document ingestion, Image extraction and analysis, Text and image vectorization, Metadata extraction.
Security Layer: Role-based access control, Query logging and monitoring, Usage analytics and activity tracking.
Knowledge Retrieval: Contextual answers with image and diagram support, Source attribution for verification, Relevance ranking.

Key Features

Document Management: Multi-format support (PDF, DOC, PPT), Automated image processing, version control, and metadata management.
AI Assistant: Natural language queries, context-aware responses, visual content inclusion, and source referencing.
Security & Analytics: Granular access control, usage tracking, query analytics, and performance monitoring.