Part 2: Why folders, tags, and keyword search break down in real creative workflows and what retrieval needs to do instead.
Introducing medium, high, and ultrahigh effort tiers to the Query Agent's Search Mode.
Why AI won’t replace creatives, and how it can remove friction from messy workflows, lost files, and creative processes.
When a Weaviate query is slow, the first question is where the time went. Query profiling returns a per-stage, per-shard timing breakdown, making query performance issues visible.
Tokenization makes or breaks hybrid search. See how Weaviate's accent folding, custom stopwords, and /v1/tokenize endpoint power multilingual BM25.
A Researcher's Perspective on Retrieval Quality in RAG Systems
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.
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/
Late interaction allow for semantically rich interactions that enable a precise retrieval process across different modalities of unstructured data, including text and images.
How Weaviate achieved 10x Faster Keyword Search and 90% index compression
Learn about the hybrid search feature that enables you to combine dense and sparse vectors to deliver the best of both search methods!
Master modern search capabilities by building a powerful API server with Hono.js. Learn how to implement vector, hybrid, and generative search while maintaining performance and reliability.
