Elastic (Elasticsearch) × LG CNS

Elastic x LG CNS, from 75% to 95% search accuracy with hybrid AI search

Search accuracy from 75% to 95% with hybrid search

Keyword blind spots to intent-aware search

Breakthrough Efficiency Written narrativeChallenge-Solution-ResultsEnterprise Software

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Full screenshot of Elastic x LG CNS, from 75% to 95% search accuracy with hybrid AI search

Why it works

The story leads with a number going up (75% to 95% search relevance), making Breakthrough the clear primary tag, while the halving of retrieval time earns a strong secondary Efficiency tag. The case study is anchored by a single named engineer who speaks in specific technical terms, which adds credibility without requiring external validation. The mechanism is well explained: combining full-text, dense vector, and sparse vector modules into hybrid search is the concrete reason the number moved, not a vague platform benefit.

Steal this

Quantify the before-state with the same unit as the after-state. Stating '75% with full-text search alone' makes the '95% with hybrid search' result immediately legible and hard to dismiss.

View the original on elastic.co ↗

This is editorial commentary and curation. The case study, screenshot, and all metrics are Elastic (Elasticsearch)'s published work; we link to the source and lead with our analysis.

Vendor Elastic (Elasticsearch)
Customer LG CNS
Industry Enterprise Software
Trigger Shift to generative AI and RAG exposed limits of keyword-based search
Format Written narrative
Structure Challenge-Solution-Results
Medium Web page