📰 Weaviate Blog

Learn how to use the Dify and Weaviate integration to build RAG applications.

1.34 introduces flat index support with RQ quantization, server-side batching improvements, new client libraries, Contextual AI integration and much more.

Weaviate announces two CVEs that are fixed in updated versions of our product.

What building AI apps with Weaviate and cooking have in common? Let’s find out!

Hands-on patterns: Design pattern for gen-AI enterprise applications, with Arize AI.

Learn how Confluent’s Streaming Agents and Weaviate combine real-time context with semantic understanding for agentic AI.

Weaviate Cloud gets an updated pricing model.

A guide to seamlessly transform data sitting in lakes and warehouses for GenAI capable applications

A strategic guide to the costs, risks and rewards of upgrading embedding models in production AI

Learn how Weaviate's native multi-tenancy architecture delivers scalable vector search with one shard per tenant, dynamic resource management, and true data iso

1.33 brings compression by default for optimal resource utilization, powerful 1-bit rotational quantization (RQ), streamlined server-side batch imports, enhance

Learn about how you can build multi-agent systems with CrewAI and Weaviate.

Hands-on patterns: LLM-as-Judge with LangChain and W&B

Announcing Weaviate has achieved ISO 27001 compliance.

Learn how Search Mode compares against Hybrid Search on the BEIR, LoTTe, BRIGHT, EnronQA, and WixQA Information Retrieval benchmarks.

The Query Agent is now generally available! Learn how the interface to databases is shifting with the introduction of agentic retrievers – domain experts at usi

A practical guide on using Weaviate Cloud Queries in MacOS apps.

Learn how chunking strategies improve LLM RAG pipelines, retrieval quality, and agent memory performance across production AI systems.

Get spun around by our new vector quantization algorithm that utilizes the power of random rotations to improve the speed-quality tradeoff of vector search with

Evals and Guardrails in enterprise workflows part 1

Elysia is an open-source, decision tree-based agentic RAG framework that dynamically displays data, learns from user feedback, and chunks documents on-demand. B

Key consideration for customizing an embedding model through fine-tuning it on company- or domain-specific data to improve the downstream retrieval performance

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.

You can now use Weaviate with n8n for no-code agentic workflows. This article teaches you how.