Hybrid Search Architecture: Combining BM25 Keyword Search with Dense Vector Embeddings
Introduction & Industry Context In the early wave of generative AI and Retrieval-Augmented Generation (RAG) deployments, engineering teams gravi…
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I Tested Amazon S3 Vectors' New Pre-Filtering Against Exact Ground Truth
A filtered vector query that asks for 10 results can come back with 2, and nothing errors. AWS's own launch post shows exactly that on a CLASSIC ind…
Vector Search Lands in DynamoDB Natively — Issue #89
This week shipped one of the more consequential infrastructure changes in a while: DynamoDB absorbed vector search, collapsing a common two-database…
Bringing an External CRM's Chats into Firestore for AI Search: Vector Search, Webhooks, and a Stubborn Bundling Error
A client wanted their management panel's AI assistant to answer questions like "what did this contact write me" or "who replied about a certain topi…
"Most Of Your Vectors Are Steerage. Why Are They In First Class?"
I was on a call last month with a startup CTO who had just gotten their AWS bill. They had built a beautiful RAG application: semantic search, conve…
ParadeDB NPM Package Seeks Feedback on Simplifying Postgres Integration with JavaScript via Drizzle ORM
Introduction: Bridging the Gap Between Postgres and JavaScript with ParadeDB The ParadeDB NPM package emerges as a targeted solution to a growing pa…
Vector Search at Scale: Why Your Index Isn't as Healthy as You Think
Vector search has become load-bearing infrastructure in modern AI systems remarkably fast. A year or two ago, it was primarily a research curiosity…