Exact-match search missed synonyms. AI now maps intent—linking "cooling goods" to inventory—turning vague queries into sales.
A lifestyle and apparel retailer operating approximately 60 brands, offering a diverse catalog ranging from fashion items to general merchandise.
Legacy search tools relied on exact keyword matching, failing to retrieve products when customers used synonyms, spelling variations, or different...
“膨大な商品数と指標をすべて見続けることは困難ですが、AI が状況を言語化してくれることで、担当者は『そうなっているのか』とパッと理解でき、一旦の概況確認がスムーズに行えるようになりました。”
Retailer of apparel, accessories, and lifestyle products across specialty brands.
Implemented the Looker and Gemini integration and Vertex AI Search for commerce for Pal.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Pal Group's E-commerce search is part of this use case:
Related implementations across industries and use cases
Text matching failed on complex queries in a 50k catalog. Now, LLMs interpret intent to rank products by likelihood to convert.
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Keyword search missed nuance. AI now decodes intent—like "wet" meaning waterproof—to curate items like an in-store expert.
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Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.
Exact-match search missed synonyms. AI now maps intent—linking "cooling goods" to inventory—turning vague queries into sales.
A lifestyle and apparel retailer operating approximately 60 brands, offering a diverse catalog ranging from fashion items to general merchandise.
Legacy search tools relied on exact keyword matching, failing to retrieve products when customers used synonyms, spelling variations, or different...
“膨大な商品数と指標をすべて見続けることは困難ですが、AI が状況を言語化してくれることで、担当者は『そうなっているのか』とパッと理解でき、一旦の概況確認がスムーズに行えるようになりました。”
Retailer of apparel, accessories, and lifestyle products across specialty brands.
Implemented the Looker and Gemini integration and Vertex AI Search for commerce for Pal.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Pal Group's E-commerce search is part of this use case:
Related implementations across industries and use cases
Text matching failed on complex queries in a 50k catalog. Now, LLMs interpret intent to rank products by likelihood to convert.
Keyword search missed nuance. AI now decodes intent—like "wet" meaning waterproof—to curate items like an in-store expert.
Keyword search failed on complex vehicle queries. Now, an AI pipeline rewrites messy questions to power shopping and service assistants.
Keyword search missed nuance. AI now decodes intent—like "wet" meaning waterproof—to curate items like an in-store expert.
Scaling curation for 90M buyers was impossible. Now, experts build seed collections and Vertex AI expands them into millions of custom feeds.
Employees previously broke work into rigid tasks. Now, they delegate high-level goals to agents that work autonomously for hours.
An aging homegrown CRM held back 1,700 agents. Now, an AI co-pilot helps them draft faster, higher-quality emails from a single screen.
Staff missed the 30% of leads arriving after hours. AI agents now field 24/7 chats and book tours, prioritizing ready buyers.
Static forms ignored cultural nuance. Now, AI agents speak local dialects to capture leads and automate feedback calls.