SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.

Open-source context retrieval layer for AI agents

The open source platform for AI-native application development.

The ultimate RAG for your monorepo. Query, understand, and edit multi-language codebases with the power of AI and knowledge graphs

AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.

Everything you need to know to build your own RAG application

Harness LLMs with Multi-Agent Programming

⚡FlashRAG: A Python Toolkit for Efficient RAG Research (WWW2025 Resource)

[KDD'2026] "VideoRAG: Chat with Your Videos"

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.

All-in-one platform for search, recommendations, RAG, and analytics offered via API