The RaG App is an AI-powered system I developed to help organizations turn both internal data and external web content into useful business knowledge.
Using a Retrieval-Augmented Generation (RaG) approach, it combines AI-driven search, natural language understanding, and automated data collection to deliver accurate, source-backed insights.
Project Overview
Many businesses have valuable information spread across internal reports, documents, and public websites.
The RaG App brings all of this together by automatically collecting, organizing, and interpreting data from multiple sources.
Users can simply ask questions in natural language and receive precise, verifiable answers within seconds.
How It Works
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Data Collection and Crawling
The system includes a custom web crawler that scans chosen websites to gather relevant information.
It collects both structured and unstructured content such as articles, product information, and research materials.
The data is cleaned, filtered, and stored securely for further processing. -
Internal Data Integration
The app also processes internal company documents like PDFs, manuals, and reports.
All text is extracted, standardized, and converted into a searchable format to ensure consistency and accuracy. -
Vector Embedding and Semantic Search
Both internal and web data are transformed into vector embeddings, allowing the AI to understand meaning and context rather than just matching keywords.
A semantic search engine, built using tools like FAISS or Pinecone, retrieves the most relevant content for each user query. -
Context-Aware AI Response Generation
The retrieved information is passed to a language model that generates clear, natural responses based on real data.
Every answer is grounded in its sources, providing full transparency and trust. -
Continuous Data Updates
The web crawler runs on a schedule, keeping the knowledge base fresh with the latest online content.
This ensures that the system always delivers current and reliable insights.
Business Value
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Combines internal company data with live web insights for real-time awareness.
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Reduces information search and research time by up to 60 percent.
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Provides trustworthy, traceable responses that improve decision-making.
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Designed with a scalable and secure architecture suitable for enterprise systems.
Outcome
The RaG App demonstrates how applied AI, intelligent data crawling, and knowledge retrieval can create measurable value for businesses.
It transforms scattered information into a dynamic, continuously updated knowledge system that supports faster, smarter, and more confident decisions