Intelligent Search: case study

Search / Knowledge Systems

A product search system designed to understand synonyms, abbreviations, product attributes and natural language.

Engagement: Catalogue-heavy product business. Scope: Search architecture, Query understanding, Relevance tuning, Evaluation tooling.

Context

Large product catalogues live or die by search. Customers type part numbers, abbreviations, misspellings and plain-language descriptions — and expect the right product first.

Problem

Keyword-only search misses what people mean. Abbreviations, synonyms and attribute queries (size, material, compatibility) return irrelevant or empty results, and nobody can tell whether a change made things better or worse.

Approach

Query parsing and attribute extraction, synonym and abbreviation graphs, hybrid lexical + semantic ranking, and — before any tuning — an evaluation set built from real queries, so every change is measured instead of guessed.

Outcome

A search system the team can reason about: relevance tracked against a fixed evaluation set, tunable without redeploying, and ready for AI-assisted features like conversational search.