Keep up-to-date on the latest product updates, how-tos, industry insights, and community spotlights.
1.33 brings compression by default for optimal resource utilization, powerful 1-bit rotational quantization (RQ), streamlined server-side batch imports, enhanced OIDC group management, and collection aliases become generally available (GA).
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 using Weaviate’s APIs with your data.
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 Weaviate.
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. Built with pure Python logic and powered by Weaviate, it's designed to be the next evolution beyond traditional text-only AI assistants.
Key consideration for customizing an embedding model through fine-tuning it on company- or domain-specific data to improve the downstream retrieval performance in RAG applications.
