Our RAG (Retrieval-Augmented Generation) app is a privacy-focused AI assistant designed to streamline knowledge management within organizations. Leveraging a local Large Language Model (LLM), the app addresses data privacy concerns by processing all information internally, ensuring sensitive data never leaves the organization’s infrastructure. The system integrates a variety of data sources, including PDFs, DOCX, CSVs, XLSX, and more, to generate real-time insights and reports through a simple, intuitive chat interface.
Key features include a Q&A assistant, instant report generator, and business insights tool, tailored to meet the needs of departments like HR, Sales, and Marketing. To enhance the user experience, we optimized data ingestion flows to handle a wide range of document types efficiently, without the need for external cloud APIs. Our app is designed to bridge the gap between generative AI potential and corporate adoption, making it accessible to all organizational roles, from administrators to executives, empowering them to retrieve and analyze data naturally.
Project Name
Intelliscript
Description
Our RAG (Retrieval-Augmented Generation) app is a privacy-focused AI assistant designed to streamline knowledge management within organizations. Leveraging a local Large Language Model (LLM), the app addresses data privacy concerns by processing all information internally, ensuring sensitive data never leaves the organization’s infrastructure. The system integrates a variety of data sources, including PDFs, DOCX, CSVs, XLSX, and more, to generate real-time insights and reports through a simple, intuitive chat interface.
Key features include a Q&A assistant, instant report generator, and business insights tool, tailored to meet the needs of departments like HR, Sales, and Marketing. To enhance the user experience, we optimized data ingestion flows to handle a wide range of document types efficiently, without the need for external cloud APIs. Our app is designed to bridge the gap between generative AI potential and corporate adoption, making it accessible to all organizational roles, from administrators to executives, empowering them to retrieve and analyze data naturally.
You can learn more about the project by referring to the following report: https://drive.google.com/file/d/1nRaE7XCuxL0iz4erKwa9NEsC73TDhW_x/view?usp=sharing
Technology & Languages
Project Repository URL
https://github.com/ChathurangaMMP/FYP-IntelliScript-Final
Deployed Endpoint URL
No response
Project Video
https://youtu.be/8tP8joZY3yo?si=77hpb-6AhZDX1Aqt
Team Members
surenbandara7@gmail.com,mmpchathuranga.07@gmail.com,lakdiluabesingha@gmail.com, sevindu.ekanayake@gmail.com