A no-code RAG server that keeps answers in sync with your documents. Works with 8 vector databases. Built on Pathway.
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database.
Represent, send, store and search multimodal data
The universal tool suite for vector database management. Manage Pinecone, Chroma, Qdrant, Weaviate and more vector databases with ease.
What if OpenAI Deep Research and Dify were one platform? OpenAgent — harness architecture for rapidly building vertical AI agents, with deep reasoning loops, visual workflows, RAG, and A2A delegation.
Weaviate vector database – examples
Home Assistant LLM integration for local OpenAI-compatible services (llamacpp, vllm, etc)
A modern desktop application for exploring, managing, and analyzing vector databases
A python native client for easy interaction with a Weaviate instance.
Knowledge work automation with AI agents
Production-ready RAG Framework (Python/FastAPI). 1-line config swaps: 6 Vector DBs (Weaviate, Pinecone, Qdrant, ChromaDB, pgvector, MongoDB), 5 LLMs (Gemini, OpenAI, Claude, Ollama, OpenRouter). OpenAI-compatible API. 2100+ tests.
Build super simple end-to-end data & ETL pipelines for your vector databases and Generative AI applications
Official Weaviate TypeScript Client
Website for the Weaviate vector database
Awesome Weaviate