Bitget Unleashes AI Trading Agents with Autonomous Accounts: GetClaw Now Executes Live Market Trades

Cryptocurrency exchange Bitget has launched a groundbreaking autonomous trading account structure, enabling its GetClaw AI agent to execute real trades directly in live markets. The move, part of a major expansion of AI capabilities, allows agents to operate continuously with real-time data, analytics, and execution—eliminating manual intervention and fragmented workflows for the first time.

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.