Searchin5 is a customizable, all-in-one website search platform that helps visitors find anything on a website—from products and documentation to policies, support content, reviews, and answers—using natural language and intelligent search.
Ecommerce search is website search applied to an online store. It handles product discovery, but also the order, sizing, returns and policy questions shoppers type into the same box. Search users are a minority of traffic and a majority of intent, which is why store search converts far above site average.
AI search interprets meaning instead of matching strings. It uses embeddings to place queries and content in the same vector space, so "something warm for a winter wedding" can retrieve results that share no keywords with the query. In practice the strongest systems are hybrid: semantic recall plus keyword precision.
Search UX is everything a visitor experiences around the query: how visible the search bar is, how autocomplete behaves, how results are laid out and filtered, and what happens when nothing matches. Most search failures visitors blame on "bad results" are really interface failures.
Search analytics turns the query log into decisions. Zero-result queries, low-click queries, refinement chains and search-to-conversion rates tell you what visitors want and where the site fails them. It is the highest-signal, lowest-cost source of customer intent data most sites already own and never read.
Search infrastructure is the machinery underneath: crawling or syncing content, building an index, serving queries fast, and keeping the index fresh as content changes. It is the part teams most often build themselves and most often underestimate the maintenance cost of.