Multimodal embeddings allow AI systems to search and reason across text, images, audio, and video in their native formats. This blog covers the key intuitions behind how this all works and walks through three practical implementations using Weaviate and Gemini.
Learn how we built a production-ready, end-to-end RAG application in just 36 hours using the Query Agent and the new Weaviate Agent Skills library.
Hands-on patterns: Design pattern for gen-AI enterprise applications, with Arize AI.
A guide to seamlessly transform data sitting in lakes and warehouses for GenAI capable applications
Learn about how you can build multi-agent systems with CrewAI and Weaviate.
Elysia is an open-source, decision tree-based agentic RAG framework that dynamically displays data, learns from user feedback, and chunks documents on-demand. Built with pure Python logic and powered by Weaviate, it's designed to be the next evolution beyond traditional text-only AI assistants.
LangChain and Weaviate v3 power scalable AI with fast, type-safe RAG workflows, practical code, and future-ready features like LLM eval and event-driven design.
Design for speed, build for experience.
Glowe is a Korean beauty recommendation app that uses domain knowledge agents, custom embedding strategies, and vector search to create personalized skincare routines. Try now: https://www.glowe.app/
Master the art of scaling a vector database like Weaviate.
Learn how to build generative AI data pipelines at scale with Weaviate and Databricks
Looking for our security documentation or auditors reports? We have now launched our trust portal to make your compliance reviews easy! Head over to https://trust.weaviate.io to learn more.
