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Writing

Articles tagged “Vector Search”

15 articles on Vector Search. All articles →

Branded cover card: The Silent Search Killer: Using dbt Tests to Guard Your Vector Ingestion Pipeline
Vector Search Data Engineering

The Silent Search Killer: Using dbt Tests to Guard Your Vector Ingestion Pipeline

Stop silent search degradation by implementing dbt macros to validate vector dimensions, L2 norms, and semantic drift across your ingestion pipelines.

Jul 14, 2026 · 31 min
Branded cover card: The Privacy Moat: Implementing Hard Multi-Tenancy in pgvector with PostgreSQL RLS
Laravel 13 Vector Search

The Privacy Moat: Implementing Hard Multi-Tenancy in pgvector with PostgreSQL RLS

Secure your RAG architecture by moving from application-side metadata filtering to database-level isolation using pgvector multi-tenancy, PostgreSQL RLS, and HNSW optimization.

Jul 13, 2026 · 29 min
Branded cover card: Hybrid Retrieval 2.0: Tuning HNSW Parameters for pgvector at Scale
Backend Architecture Vector Search

Hybrid Retrieval 2.0: Tuning HNSW Parameters for pgvector at Scale

Optimize pgvector HNSW parameters for million-row vector databases. This guide covers m, ef_construction, and memory management for production-grade RAG.

Jul 10, 2026 · 30 min
An engineering schematic showing a geographical map overlayed with sharp neon hexagons acting as pre-filters to narrow down vector space queries.
Laravel 13 Vector Search

Location-Aware RAG: Combining Uber’s H3 Grids with Laravel 13 Vector Search

An extensive system architecture tutorial analyzing how to construct location-aware Retrieval-Augmented Generation engines within the Laravel 13 ecosystem. We detail how to implement Uber's H3 Hexagonal indexing parameters inside PostgreSQL tables to narrow down local regional records before performing dense pgvector semantic similarity updates.

Jun 13, 2026 · 9 min
A high-level software engineering schematic demonstrating the transition of data chunks through Vespa's first-phase text filter and second-phase vector ranking.
Vespa.AI Vector Search

Vespa Multi-Stage Ranking: Merging BM25 and Vector Search

An in-depth technical tutorial detailing how to craft hybrid, multi-stage rank profiles inside Vespa.ai. It breaks down the mechanical logic of first-phase (lexical) and second-phase (semantic vector) scoring layers, allowing developers to safely merge exact string matching with high-intent vector representations without sacrificing execution latency.

May 18, 2026 · 7 min
A digital visualization of an AI agent reading multiple technical articles and curating them into a clean, modern newsletter layout.
AI SDK Laravel 13

Building a Semantic Newsletter Engine with Laravel 13 AI SDK

A comprehensive guide to building an AI-powered newsletter engine. We demonstrate how to leverage Laravel 13's native vector search and the first-party AI SDK to create a curation tool that understands user intent and delivers deeply relevant technical content.

May 11, 2026 · 4 min
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