Nansen AI, a new way to trade. It's the first agentic onchain app that puts an entire research team in the pocket, accessible anywhere, 24/7.

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Promote with Leviathan NewsNansen, the crypto analytics firm known for its on-chain data and “Smart Money” tracking, has launched Nansen AI, a mobile-first “agentic onchain app” that combines AI research, portfolio intelligence, and trade execution in a single interface. The product is positioned as “a new way to trade,” designed to let users ask natural-language questions about tokens, wallets, or markets and then execute trades directly from the same app, effectively acting like an AI research assistant in a trader’s pocket. According to Nansen’s launch materials, the app is powered by a dataset of over 500 million labeled blockchain addresses, which feeds AI-driven conversations, real-time on-chain analytics, and personalized portfolio insights for multichain investors. Rather than navigating dashboards, users are encouraged to interact via chat-style queries—covering topics such as token performance, wallet behavior, and “Smart Money” flows—and can then move from analysis to trade execution within seconds. The app is marketed as the first “truly agentic onchain” mobile experience, available on iOS with rollout to Android as well, extending Nansen’s strategy of turning its institutional-grade on-chain data into a consumer-facing trading assistant. This launch matters because it exemplifies the broader trend of AI-native trading interfaces in crypto, where models are not only generating insights but also directly driving transaction flows on-chain. By integrating Nansen’s existing analytics stack—portfolio tracking, DeFi position monitoring, and Smart Money tracking—into a conversational, action-oriented mobile agent, the company is competing in a growing segment of AI trading tools and signaling how on-chain data platforms may evolve from passive dashboards into active, execution-capable agents.
AI-generated background, compiled from web sources — not editorial content.

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