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.
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.
1.32 adds collection aliases for no-downtime collection migrations, efficient & powerful rotational quantization (RQ), GA replica movement, memory reduction with compressed HNSW connections and more!
Learn about the new certified Weaviate Confluent Apache Kafka Connector!
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/
How Weaviate's day zero, day one, day two mindset helps developers build AI-native applications.
How we built cross-platform vector search and syncing for a thinking tool using Weaviate, RAG, and multi-tenant architecture.
Announcing Weaviate Enterprise Cloud new HIPAA compliance on AWS, enabling secure PHI storage, search, and vector-powered AI for healthcare workloads.
Master the art of scaling a vector database like Weaviate.
Learn how Weaviate and NVIDIA enable fast, scalable vector search for agentic AI.
