C

chromadb

Local first, AI-powered data analytic workspace.

AIQA (AI Questions Answering) — локальный стек для построения сервиса вопросов-ответов на базе LLM и векторных представлений. Быстрое развертывание в Docker, устойчивое хранение знаний и удобный API для интеграции.

The EUC RAG Agent is a Retrieval-Augmented Generation (RAG) system built to deliver accurate and relevant responses for the fictional Egyptian University in Cairo (EUC). It uses all-MiniLM-L6-v2, gemini embedding-001, or TF-IDF vectorization for precise information retrieval and employs gemini-1.5-flash, gemini-1.5-pro, or llama2:7b models for generating concise, professional answers. The agent efficiently addresses a variety of university-related inquiries.

Scholara: A Virtual Assistant Powered by LLM, RAG, and AI Agent.

Finding the right scholarship can be a timeconsuming and frustrating process. You'll likely spend hours poring over university websites, communicating with current students, and scouring the internet for information. Unfortunately, even after all that effort, there's no guarantee you'll find the perfect scholarship. That's where our AI scholar comes in. Let us handle the legwork for you, and we'll provide personalized assistance to find the most suitable scholarship for you and answer all your questions about the scholarships that interest you. We solved this by using LLM to provide a human-like when answer the students, RAG we build our own vector database to get more suitable scholarships from it based on student information and desire, also to keep our system up-to-date with all the updated information about the scholarships we built AI Web agent this helps the system to be aware about all the updates in the scholarships information, and new scholarships.