Bitget introduces unified AI trading ecosystem, surpasses 1M Users and $1.2B AI Agent trading volume

Bitget has introduced Bitget AI, which has already surpassed 1 million users and generated $1.2 billion in trading volume across more than 58 AI-powered tools. The unified AI-powered trading ecosystem is designed for market analysis, strategy execution, and risk management.

The milestone signals Bitget’s shift toward becoming an agent-native exchange, highlighting growing retail adoption and the platform’s ability to deliver AI-driven trading at scale. The expansion also reflects a broader architectural direction for Bitget as automation becomes more integrated into trading environments.

Bitget AI has now unified access to its suite of intelligent trading tools for traders and builders. It creates a single environment for developing, deploying, and scaling AI-driven strategies. 

At the core are GetClaw, a zero-install AI agent for real-time market insights, and GetAgent, Bitget’s AI assistant for strategy execution and automated trading. Together with Agent Hub, the developer platform providing API access and model integrations, they form a connected system where insight, strategy, and execution are seamlessly linked.

Bitget AI merges traders and builders’ tools into one platform

Bitget unifies tools for traders and builders into a single trading environment. The company is advancing toward an agent-native exchange – where AI moves from supporting decisions to actively participating in markets. Human users and autonomous agents can operate side by side, interacting with markets in real time.

New capabilities will also roll out in the coming months, including AI Trading Playbooks (now in beta). It is an end-to-end AI trading strategy platform that enables professional traders to create, backtest, deploy, and host human-readable strategies in natural language. A full suite of infrastructure, including data SDKs, trading harness standards, and marketplace distribution, supports AI Trading Playbooks.

Bitget CEO says AI is shifting from chat to trade execution

Gracy Chen, the CEO of Bitget, emphasizes that the role of AI in trading is shifting from chat to execution. She notes that the conversation is no longer just about using AI to interpret markets. It is now about helping users organize strategies, automate parts of their trading process, and interact with markets more efficiently. Chen believes that platforms will need to evolve around that behavior, and Bitget AI reflects how trading infrastructure will develop over time.

Bitget AI represents another step toward integrating intelligent systems directly into Bitget’s Universal Exchange model. The company continues building toward an agent-native exchange designed for both human traders and their autonomous agents. Crypto, tokenized assets, and AI-driven workflows are becoming increasingly interconnected.

Bitget also points out that GetClaw enables users to remain in control as playbooks execute, ensuring that keys never leave the users’ hands. Identity isolation also ensures that every interaction is verified, preventing cross-account data leaks and instruction interference. 

The Bitget team further points out that trading history and AI insights remain fully private and are never shared with other users or accessible to other agents. API access is also bound to unique user signatures, which are non-forgeable, non-transferable, and never delegated.