Naver and Daum are intensifying competition in artificial intelligence (AI)-powered search, moving beyond chatbot-style responses toward agent-driven systems that leverage their proprietary data and service ecosystems to execute real-world tasks. Naver recently unveiled the road map for its conversational AI search service AI Tab, which launched for all users in late June, positioning it as a gateway to AI agents capable of handling tasks such as reservations and shopping. The company identified a product-native large language model (LLM), harness engineering and multimodal AI as three core technologies behind the strategy. Unlike conventional foundation models built for general-purpose reasoning, Naver said its product-native LLM is tailored for real-world services. The model is designed to handle long-context, multiturn interactions while selecting appropriate tools to complete tasks across Naver’s ecosystem, including search, shopping, maps, blogs and community platforms. Harness engineering connects the AI to Naver’s real-time data sources, including blogs, maps, shopping and new
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