Bitget’s AI Trading Platform Surpasses 1 Million Users and $1.2 Billion in Volume

Bitget’s AI trading ecosystem now encompasses 58 tools, boasting more than 1 million users and $1.2 billion in trading volume, as the exchange focuses on “agent-native” trading as a fundamental aspect of its Universal Exchange strategy.

Bitget has introduced a dedicated landing page for Bitget AI and released new metrics highlighting the adoption of its AI trading ecosystem, claiming over 1 million users and more than $1.2 billion in AI-powered trading volume. In a recent overview, the exchange, which identifies itself as the largest “Universal Exchange” globally, noted that Bitget AI now integrates 58 AI-based trading tools into a cohesive infrastructure, addressing key scenarios like market analysis, trading assistance, strategy development, and comprehensive automation.

Bitget embraces “agent-native” AI trading

Within Bitget’s UEX multi-asset trading structure, the company positions Bitget AI as “a crucial element” in its ambition to become a “native intelligent agent exchange,” wherein AI agents are directly embedded into trading workflows, rather than being added as separate bots. As Bitget describes, the ecosystem aims to establish “a unified AI-powered trading environment” that caters to both retail traders and developers, amalgamating market data processing, strategic logic, and execution into a seamless cycle.

At the heart of this cycle lie three primary products. GetClaw is introduced as a no-install AI agent for real-time market insights, able to analyze markets, summarize conditions, and present trade ideas through a conversational interface. GetAgent serves as an AI assistant for strategy execution and automated trading, interpreting user-defined parameters or signals to transform them into live orders and manage positions. Meanwhile, Agent Hub is a developer-centric platform that provides open APIs and AI-model integration points, allowing third parties to design and deploy their own agents and tools on Bitget’s infrastructure. Collectively, the company asserts that these elements “create a comprehensive closed-loop process of ‘insight-strategy-execution’” for AI-supported trading.

Bitget CEO Gracy Chen has highlighted a forthcoming phase centered on AI Trading Playbooks, which are currently undergoing internal testing. As described by Bitget, these Playbooks will empower traders to articulate strategies in natural language, convert them into executable logic, perform backtests, and subsequently deploy them in live markets, complete with distribution features for successful playbooks that enable creators to share or monetize their strategies.

For the time being, the notable figures—1 million users, $1.2 billion in AI-driven trading volume, and 58 tools—are more indicative of Bitget’s effort to establish “agent-native” trading as a distinctive factor in a burgeoning exchange landscape, where AI is evolving from a mere marketing phrase to a genuine source of order flow.