Bitget introduced a new account structure that allows its GetClaw AI trading agent to execute trades autonomously within a dedicated environment. The exchange is expanding AI agent capabilities to adapt to the demand for direct participation under live market conditions. Bitget’s Agent Hub allows AI agents to access real-time data, analytical tools, and execution capabilities without fragmented workflows. Bitget , the world’s largest Universal Exchange (UEX), has introduced a new account structure that allows its AI trading agent, GetClaw, to execute trades autonomously within a dedicated account environment, marking a new stage in the evolution of AI-driven trading. Within this account, the agent can autonomously execute real trades based on natural language instructions, monitor markets continuously, and manage positions in real time without requiring manual intervention. Bitget expands trading agent capabilities The development builds on Bitget’s earlier launch of GetClaw , a zero-installation AI agent designed to operate as a persistent trading partner, as well as the recent expansion of Agent Hub , which introduced analytical AI Skills and integrated data tools that connect market analysis directly with execution. Together, these developments reflect a progression from access to intelligence, and now to independent execution. The introduction of agent accounts reflects a shift in how AI is being applied within trading. The beginning saw systems focused on assisting users through analysis or recommendations, but recent models are capable of observing markets continuously and acting on defined strategies. By assigning dedicated accounts to AI agents, Bitget extends this capability into direct participation under live market conditions. “Sooner or later emerging financial markets are going to be filled with AI agents trading on behalf of users. We’re preparing the infrastructure to run this on scale,” said Gracy Chen, CEO at Bitget. Bitget integrates AI directly into its trading environment The use of dedicated sub-accounts provides clear separation between user-controlled assets and agent-driven activity, allowing strategies to be deployed with greater transparency and control. Users can define strategies in simple terms, while GetClaw executes, monitors, and adjusts positions within predefined parameters. This approach reflects a broader architectural direction. Rather than treating AI as an external layer, Bitget is integrating AI directly into its trading environment, allowing both human users and automated systems to operate within the same infrastructure. Through Agent Hub, AI agents can access real-time data, analytical tools, and execution capabilities without relying on fragmented workflows. As AI-driven participation grows, trading environments are evolving to support both human and machine-driven activity. This transition is shaping what is increasingly described as agentic trading, where systems move from supporting decisions to actively participating in markets. Within Bitget’s Universal Exchange model, where crypto assets and tokenized traditional instruments operate within a unified account structure, the addition of agent accounts extends the platform’s functionality beyond manual trading. As automation becomes more integrated across markets, trading systems are evolving toward environments where analysis and execution operate together in real time.
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