Existing Retrieval-Augmented Generation (RAG) systems face challenges in enterprise settings due to limited retrieval scope and data security risks. When relevant internal documents are unavailable, the system struggles to generate accurate and complete responses. Additionally, using closed-source Large Language Models (LLMs) raises concerns about exposing proprietary information. To address these issues, we propose the Secure Multifaceted-RAG (SecMulti-RAG) framework, which retrieves not only from internal documents but also from two supplementary sources: pre-generated expert knowledge for anticipated queries and on-demand external LLM-generated knowledge. To mitigate security risks, we adopt a local open-source generator and selectively utilize external LLMs only when prompts are deemed safe by a filtering mechanism. This approach enhances completeness, prevents data leakage, and reduces costs. In our evaluation on a report generation task in the automotive industry, SecMulti-RAG significantly outperforms traditional RAG - achieving 79.3 to 91.9 percent win rates across correctness, richness, and helpfulness in LLM-based evaluation, and 56.3 to 70.4 percent in human evaluation. This highlights SecMulti-RAG as a practical and secure solution for enterprise RAG.

Today is a great day because our first blog post is being published. We introduce our project in this blog post. Let's start with the name of the project. The project name is Question Assistant Barlas. We thought why not give a human name to our question-generating machine like Alan Turing's Christopher.

The idea behind this project to make a hardware and Big brain AI work together, to implement the real world scenario to help and understanding the machine logic. This idea came from Alpha-Go game but in Alpha-Go the ai work from inside (software) but here we are dealing with hardware to make it real like human player. I am presenting this project idea to make this project real with help of your company so for that I need your support and sponsorship as I'm an undergrad student and it's my opportunity to see the real future by working with you on this project and many more. Carrom is a tabletop game with resemblances to snooker or billiards, and also the more modern games of air hockey. Carrom is played by propelling discs with the fingers with the aim of potting them into one of four corner pockets on a wooden playing board-Game.

The US military is equipped with a number of stealthy underwater robots to spy on enemies, but these high-tech innovations come years after Charlie the robotic catfish. Developed in the 1990s by the Central Intelligence Agency (CIA), this unmanned underwater vehicle is operated remotely using a line-of-sight audio and fitted with sensors to spy on adversaries, along with collecting water samples. The'catfish' is also designed with a pressure hull, ballast system and communication system in the main part of its body and propulsion system in the tail. Details of Charlie's missions are still classified, but the technology led engineers to design robotic submarines and other aquatic inspired machines to investigate the seas. The robotic fish measures about two feet long and some of its specifications, according to the CIA website, include speed, endurance, depth control and navigational accuracy.