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Natural-language product search
Understand everyday wording, ambiguous requests and multiple conditions without requiring exact product names.
Home / SHOPLINE · Planned
SHOPLINE · Planned
Extend product and sales scenarios with
intent-aware AI discovery
This planned integration would connect Cobinyiu AI Search with SHOPLINE product data and operating flows, helping shoppers and store teams find, compare and recommend products through natural language.
Concept preview
⌕A lightweight bag for commuting and weekends, under NT$3,000
AI analysis
Looking for a lightweight, versatile everyday bag under NT$3,000. Suggested directions are organized by use, capacity and material.
Light crossbodyNT$ 1,680
Commuter backpackNT$ 2,480
Mini toteNT$ 1,980
Why Cobinyiu AI
Move from keyword lookup to scenario-based product discovery
AI Search can turn conversational needs, budgets, preferences and use cases into product criteria, helping users narrow their options with less effort.
Customer need
“A bag that works for the office and weekends—lightweight and not too formal.”
CommuteWeekendLightweightCasual style
Intent understoodAI Search
Turn one sentence into searchable product criteria
The system maps conversational needs to use, weight, capacity and style, then explains relevant product directions.
ScenarioCommute, short trips
Product criteriaLight, easy to organize
PreferenceAvoid overly formal styles
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Scenario and criteria-based recommendations
Organize relevant products by recipient, use, budget and preference, with clear recommendation context.
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Multilingual search and answers
Evaluate intent understanding across languages against the existing catalog.
Planning Scope
Define an integration scope around existing data and workflows
The integration is currently in planning. Any implementation scope and schedule will depend on available APIs, catalog fields, synchronization frequency, permissions and presentation options.
1
Catalog and category assessment
Confirm usable items, variants, prices, inventory, categories and content fields.
2
Search indexing and synchronization
Evaluate APIs, webhooks or scheduled feeds, including update and exception rules.
3
Experience validation and rollout planning
Test real query scenarios before confirming a future rollout.
Cross-border Search and Service
Let customers search in familiar language, online or in store
The plan can begin with shopper self-service and staff lookup, then explore how multilingual search demand informs catalog content and operations.
Shopper self-service discovery
Let shoppers describe complete needs and receive product directions that are easier to understand and compare.
Fast lookup for store teams
Help frontline staff search products and information by customer scenario.
Search demand as operational insight
Reveal customer language, data gaps and unmet needs from real queries.
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Define the right AI Search integration for SHOPLINE
Start with product data, user scenarios and technical conditions to establish a practical planning scope.