Ecosystem & Stack: qdrant

A modular framework built with LangGraph for developing advanced Agentic RAG systems, offering both learning materials and an extensible architecture.

An enterprise-grade platform for easily deploying agentic RAG applications in your own cloud infrastructure, offering an alternative to hosted solutions like OpenAI's custom GPTs.

A hands-on course to learn LLMs, LLMOps, and vector databases by building, training, and deploying a real-time financial advisor LLM system.

An intelligent dialogue system leveraging RAG technology to build custom Q&A systems from diverse knowledge bases.

A comprehensive practical guide and accompanying code repository for LLM engineers, covering the full lifecycle of building, deploying, and monitoring advanced LLM and RAG applications on AWS with LLMOps best practices.

A Python library for representing, transmitting, storing, and retrieving multimodal data, designed for AI applications.

An all-in-one API platform for building intelligent search, recommendations, and RAG applications with advanced semantic capabilities.

A free, hands-on course to build a production-ready LLM & RAG system, including a personalized AI replica, applying LLMOps best practices.

An open-source Docker Compose template for quickly setting up a secure, self-hosted AI and low-code development environment.

A graph-native platform for storing, enriching, and retrieving structured knowledge to power AI applications and intelligent agents.