
Expand your search and AI knowledge with detailed tutorials, data studies, and product updates.
Deep-dive into the topics that matter most. Each hub is a curated collection of guides, tutorials, and insights.
Everything about building image search — reverse image lookup, text-to-image search, face search, visual search for e-commerce, and OCR. Tutorials, architecture breakdowns, and production cost analysis.
Go beyond keyword matching. Learn how semantic search understands meaning, how vector databases power it, and how to add it to your product. Comparisons, explainers, and integration guides.
Step-by-step coding guides for adding search, image recognition, and content moderation to your app. Python, JavaScript, React, Next.js — full code included.
How different industries use image search, semantic search, and content moderation. Real estate, fashion, marketplaces, dating apps, and more.
Side-by-side breakdowns of search and vector database tools. Vecstore vs Pinecone, Vecstore vs Algolia, and more — so you can pick the right tool for your stack.
Automate NSFW detection and content moderation without building your own ML pipeline. Practical guides for keeping user-generated content safe at scale.
The newest posts across all topics.
Add visual search to your WooCommerce store. Customers search by photo or text description and find matching products. Includes a WordPress plugin and similar products on every product page.
Giorgi Kenchadze2026-04-17Let your Shopify customers search by photo instead of keywords. Sync your product catalog, add visual search to your storefront, and show similar products on every product page.
Giorgi Kenchadze2026-04-15Elasticsearch gives you control. Vecstore gives you a finished search API. Here's where each one makes sense, and where teams usually underestimate the cost of doing it themselves.
Giorgi Kenchadze2026-04-13Build image search endpoints in FastAPI. Text-to-image search, reverse image search, and image uploads. Full code included.
Giorgi Kenchadze2026-04-12Three approaches to duplicate image detection: file hashing, perceptual hashing, and embedding similarity. When to use each, how they work, and how to build them.
Giorgi Kenchadze2026-04-08Multimodal search lets users search across text, images, and other data types using any of them as the query. Here's how it works, why it matters, and how to build it.
Giorgi Kenchadze2026-04-08