Manticore Launches Conversational Search Combining Full-Text, Vector, and AI Layers

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Search technology company Manticore has introduced a Conversational Search system designed to handle complex, natural-language shopping queries that traditional full-text search cannot fully resolve. The system combines full-text search, vector search, hybrid ranking, and a large language model to extract user intent, apply filters, and generate contextual answers in a single flow. The shift is driven by changing user behavior: Google reported in May 2026 that its AI Mode surpassed one billion monthly users, with people asking longer, more nuanced questions than conventional search was built to handle. Manticore tested its approach using the ConvApparel dataset, which contains over 82,000 apparel products with descriptions, attributes, and images, building a demo store to showcase the technology. Rather than replacing keyword search, the system layers complementary methods so each handles the part of a query it is best suited for.

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