Scouty

Semantic Search

Understand what shoppers mean, not just what they type.

Scouty's semantic search retrieves products, documents, and assets by meaning — using embeddings, optional reranking, and a hybrid surface that combines keyword and vector results.

The problem

Synonym lists run out before shopper vocabulary does.

Use-case and natural-language queries dominate the long tail. No synonym list, however large, will catch them all.

How Scouty solves it

Vector retrieval that maps meaning, not surface form.

Scouty Semantic ships with embeddings, hybrid retrieval, and optional reranking. It is metered explicitly so semantic-heavy stores stay predictable.

Key features

What ships with semantic search.

Intent matching

Use-case queries find the right product even when no keyword overlap exists.

Hybrid retrieval

Keyword precision combined with semantic recall, merged and ranked.

Query expansion

Expand short queries with related concepts to surface long-tail products.

Reranking

Optional reranker model for noisy candidates and large catalogs.

Semantic analytics

See where semantic search recovers demand keyword search would have missed.

API + components

Same retrieval surface for storefronts, headless apps, and AI assistants.

Example use cases

Where it matters most.

Beauty / skincare

'Hydrating' finds products described as 'moisture repair' or 'rehydration complex'.

Outdoor / lifestyle

'For wet trails' finds GORE-TEX boots even when titles only list materials.

B2B technical

'Compatible with 480V three-phase' finds spec sheet content and the right SKUs.

Home / fashion

'Boho rug' or 'cottagecore lamp' surfaces visually-relevant products by style.

Related add-ons

Often turned on alongside semantic search.

Get started

Ready to put one search bar across your products, documents, and assets?

Start with a free expert-led Search Audit. A Scouty specialist will review your storefront and recommend a clear next step.