Qdrant

Prerequisite: Familiarity with the concepts introduced in Part 2 — Ingestion Chunking. Review it first if the terminology in this part is unfamiliar. In Part 2: Data Ingestion & Atomic Chunking - Bringing Product Data into the AI Environment, we established a clean data synchronization pipeline from PostgreSQL to Qdrant via Kafka CDC. But the journey of building a standard e-commerce search engine has just begun. When a user enters: “Asus ROG Zephyrus G14 laptop under $1500 in stock” ...

Architecting Agentic E-commerce Search with Golang Practical strategies for tuning vector search precision without bloating RAM. How to coordinate multiple AI search agents to prevent search query latency spikes. If customers cannot find a product, they cannot buy it — search is core infrastructure for any e-commerce platform. User search behavior has evolved from typing short, abrupt keywords (e.g., “men’s running shoes”) to submitting complex, goal-oriented queries (e.g., “find me a pair of men’s waterproof trail running shoes, size 42, under $100, that can be delivered by tomorrow”). Against these multifaceted intents, traditional keyword search engines show their limitations. ...