"Bitget AI disclosed that it crossed 1 million users and $1.2 billion in trading volume across 58 tools as of mid-May 2026. The platform, now branded Bitget AI, combines market analysis, strategy execution, and risk management into a single infrastructure layer accessible to retail traders and developers. The announcement positions the exchange as moving toward what it calls an agent-native model under its Universal Exchange (UEX) framework."
"Gracy Chen signals Bitget is shifting from AI chat features to full execution, targeting an agent-native exchange model. The role of AI in trading is starting to shift from chat to execution, Chen said. Platforms will need to evolve around that behavior, and Bitget AI reflects how we see trading infrastructure developing over time."
"At the center of the system are two existing tools: Getclaw, a zero-install AI agent built for real-time market insights, and Getagent, an AI assistant that handles strategy execution and automated trading. Both feed into Agent Hub, a developer platform that provides API access, model integrations, MCP Server support, and CLI tools for building and deploying custom agents. The unified system creates a closed-loop environment where insight, strategy, and execution connect without switching between tools."
"A new feature called AI Trading Playbooks is currently in beta. The tool lets traders create strategies in natural language, then backtest, deploy, host, and distribute them through a built-in marketplace. Retail traders and autonomous agents can operate side by side within the same infrastructure, with dedicated sub-accounts and risk controls, including sandbox environments and capital limits."
Bitget AI reported crossing 1 million users and $1.2 billion in trading volume across 58 tools as of mid-May 2026. The platform is moving from AI chat features toward full execution using an agent-native exchange model under its Universal Exchange (UEX) framework. Bitget AI Trading Playbooks is in beta, enabling traders to create natural-language strategies, backtest them, deploy them, host them, and distribute them through a marketplace. The system combines market analysis, strategy execution, and risk management into a single infrastructure layer for retail traders and developers. Getclaw provides real-time market insights, Getagent handles strategy execution and automated trading, and Agent Hub offers API access, model integrations, MCP Server support, and CLI tools. Retail traders and autonomous agents can operate together with sub-accounts, sandbox environments, and capital limits.
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