Endee.io – A high-performance vector database, designed to handle up to 1B vectors on a single node, delivering significant performance gains through optimized indexing and execution. Also available in cloud https://endee.io/
endee 开源项目推荐(18 个)
endee 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 全部 18
GitHub 共 18 个仓库,已全部展示Endee.io – A high-performance vector database, designed to handle up to 1B vectors on a single node, delivering significant performance gains through optimized indexing and execution. Also available in cloud https://endee.io/
Noise-tolerant VLSI fault localization on the Endee vector database — retrieving nearest fault behaviours so diagnosis survives response noise that exact dictionary lookup cannot. Benchmarked on ISCAS-85 (c432/c880).
Agentic Insurance Claims Analyzer — Endee Hybrid Search (Dense + BM25) + 3-step RAG pipeline + Groq LLaMA3 + Streamlit UI
This project is a semantic search system using transformer embeddings and the Endee vector database. It turns text documents into vectors and finds the most relevant ones based on meaning, enabling smarter search beyond keywords.
AI Semantic Search powered by Endee Vector Database — Next.js 14, React, Tailwind CSS
AI-powered Multi-Agent Research Assistant using LangGraph, Endee Vector Database, Groq, and Tavily for automated research workflows
RAG-powered document Q&A system built using Endee Vector Database and FastAPI
RAG-powered Document Q&A system built with Endee Vector Database, sentence-transformers, Groq LLaMA 3, and Flask. Supports multi-document indexing, semantic search, query caching, and per-file filtering.
Agentic AI movie recommendation engine using Endee vector database + Groq LLaMA 3.3
Production-ready RAG system with Endee vector database featuring hybrid search (semantic + BM25), neural re-ranking, and Streamlit UI for AI/ML knowledge base querying
Echo-Ops: Autonomous Infrastructure Observability Agent powered by Endee Vector DB and LLM. Detects architectural entropy in log streams via semantic drift analysis.
A production-ready Retrieval-Augmented Generation (RAG) system enabling intelligent, context-aware document Q&A. Built with Python, Endee Vector Database, and Streamlit.
Production-ready RAG AI Assistant built using Node.js, React, Ollama, and Endee Vector Database.
Semantic Search + Question Answering RAG system using Endee Vector DB
👨💻 About the Author I am a BSc Data Science student passionate about building efficient, data-driven solutions. My work focuses on the intersection of Machine Learning, Software Engineering, and Embedded Systems. Interests: Natural Language Processing, Vector Databases, and Model Deployment. Tech Stack: Python, C++, SQL, and Git.
A production-ready Retrieval-Augmented Generation (RAG) assistant built with the Endee vector database, Streamlit, and Google Gemini 2.0 Flash.
🏦 AI-powered Financial Document Intelligence using RAG, Semantic Search & Agentic AI — built on Endee Vector Database
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 18 个项目;原始页面见 https://github.com/topics/endee。
- 该话题在 GitHub 上共有 18 个仓库, 本站收录的是其中最热门的 18 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 18 个项目累计 1297 Star,覆盖 3 种主要语言,数据更新于 2026-11-07。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。