| Feature | AI Search (Keyword Search) | Gen-AI Search (Semantic Search) |
|---|---|---|
| Core Approach | Direct term matching against titles, descriptions, and tags | Vector-based intent matching that understands meaning and context |
| Control & Precision | Exact control over which terms match; ideal for precise, governed setups | Automatic handling of synonyms, slang, and higher-level concepts without manual rules |
| Query Handling | Fuzzy matching (typo tolerance), prefix/suffix options, custom synonyms, stop-words, and phrase rules | Holistic interpretation of long-tail and conversational queries (“cozy winter boots”), as well as pure-image inputs |
| Multimodal Capabilities | Text-only search | Unified vector space for text + images—mix keywords, questions, or uploads seamlessly |
| Maintenance & Tuning | Requires ongoing manual tuning of synonyms, dictionaries, and phrase lists | Self-learning model that adapts to new products, trends, and visual styles with zero manual effort |
| Performance & Scalability | Lightweight footprint; predictable latency; suited for smaller catalogs or lower-traffic sites | Optimized for large, dynamic catalogs; minimal performance impact thanks to precomputed embeddings |
| Best-Fit Scenarios | Controlled environments requiring exact matches or strict governance | Ambitious brands needing richer relevance, zero-maintenance synonym management, and cutting-edge multimodal discovery |
When to Use Which Mode
- Start with Keyword Search for controlled, exact matches and minimal overhead. It’s a solid choice for smaller catalogs or when you need tight governance over term handling.
- Upgrade to Semantic Search to unlock powerful Gen AI-driven discovery: richer relevance, true multimodal queries, and zero-maintenance synonym management—ideal for ambitious brands seeking a competitive edge.