Automated Document Tagging & Indexing System

We designed a cutting-edge AI-powered document tagging and indexing system with the following capabilities: 

1. Intelligent Tag Extraction: 
   – Used Azure AI and NLP techniques to extract key topics, entities, and categories from documents.
   
   – Automatically assigned relevant metadata and keywords for improved classification.
   
   
2. Advanced Indexing with Elasticsearch:
   – Implemented Elasticsearch to store and index documents efficiently.
   
   – Enabled fast retrieval and ranking of results based on contextual relevance.
   
   
3. Enhanced Search with Generative AI (RAG Framework): 
   – Integrated OpenAI GPT-4 with Retrieval-Augmented Generation (RAG) to generate accurate, context-aware answers. 
   
   – Ensured hybrid search capabilities, combining keyword and semantic queries for precise information discovery. 
   
   
4. Trend Analysis & Knowledge Discovery:
   – Identified emerging trends in large datasets by analyzing frequently searched topics. 
   
   – Provided actionable insights for decision-making using AI-driven trend forecasting. 
   
   
5. User-Friendly Natural Language Querying:
   – Allowed users to search in natural language instead of relying on rigid keyword searches. 
   
   – Delivered precise responses with summarized insights, reducing time spent searching for relevant documents.