A new Messari Pulse report highlights early adoption across Bitget’s AI trading infrastructure, outlining how the exchange is building a multi-layer system that spans market analysis, trade execution, developer access, and user-facing strategic guidance. According to the report, Bitget’s AI stack is part of a broader trading infrastructure serving 125 million users worldwide.
The report breaks Bitget’s architecture into four core layers. These include GetAgent, a conversational interface for market analysis; GetClaw, an autonomous execution tool; Agent Hub, which gives developers direct access to exchange functions; and Gracy AI, a strategic guidance product built around the public market voice of Bitget CEO Gracy Chen. Together, these tools are designed to extend AI across the full trading workflow rather than limit it to a single analytics feature.
Early user traction highlighted by Messari
One of the report’s main takeaways is the scale of early engagement. Citing Bitget data, Messari says Gracy AI attracted more than 460,000 users in the first 11 days after its February launch. During the same period, it generated more than 2.6 million replies and produced over 390 million impressions. These figures suggest that AI-driven market interfaces are gaining visibility quickly among crypto platform users, especially when paired with a recognizable brand voice and direct in-platform utility.
Messari also notes that GetAgent has surpassed 450,000 registered users since launch. Before broader rollout, the product went through an invite-only phase from July to August 2025. During that period, Bitget says the tool generated more than 100 million impressions and built a waitlist of over 25,000 users. Those metrics point to strong pre-launch interest, even before full access was made available.
A full AI stack from research to execution
Beyond user numbers, the report focuses on how Bitget is attempting to build a more complete AI infrastructure around trading. At the center of that effort is Agent Hub, the layer that connects AI systems directly to exchange functions. Launched in February 2026, Agent Hub supports MCP Server, Skills, REST APIs, WebSocket APIs, and a command-line interface. According to the report, Bitget is the only exchange currently offering all four of these access methods simultaneously.
Messari says Agent Hub has since expanded to include five analytical AI Skills and more than 15 integrated data tools. These tools cover use cases such as macro analysis, technical signal detection, sentiment monitoring, market intelligence, and news aggregation. In practical terms, this positions Agent Hub as both an exchange connectivity layer and a toolkit for developers or advanced users who want AI systems to interact with live market infrastructure in a more structured way.
On the execution side, GetClaw represents Bitget’s approach to autonomous trading with retail-focused controls. Rather than allowing unrestricted access to user assets, the system operates through dedicated sub-accounts isolated from user-held funds. It also relies on sandbox environments and capital limits to define where the AI agent can operate and how much money it can deploy. This design reflects an effort to balance automation with risk management, particularly in a market where autonomous execution tools can raise concerns around control, volatility, and user oversight.
GetClaw is currently live on Telegram, and Bitget says later releases are planned for Discord, WhatsApp, and in-app integration. That rollout strategy suggests the company is not limiting AI trading tools to its core trading terminal, but is instead exploring distribution through messaging and social platforms where many crypto users already spend time discussing markets.
Bitget’s broader AI and market strategy
In comments included in the release, Bitget CEO Gracy Chen said the company wants to give billions of people the ability to trade more like Wall Street professionals. She described AI as an increasingly important component of modern trading infrastructure and said early usage of Bitget’s tools shows that users now expect analysis, execution, and strategy to be integrated inside a single trading platform.
That framing is consistent with a wider industry shift. Across crypto exchanges and fintech platforms, AI is no longer being presented solely as a chatbot or educational overlay. Instead, it is being positioned as a functional layer that can help users interpret markets, trigger actions, automate workflows, and connect directly to trading systems. The significance of Bitget’s rollout, as presented in the Messari report, lies in how those capabilities are being packaged together as an end-to-end infrastructure offering.
Bitget describes itself as the world’s largest Universal Exchange (UEX), with access to more than 2 million crypto tokens as well as 100+ tokenized stocks, ETFs, commodities, foreign exchange products, and precious metals including gold. The company says it serves users across 150 regions worldwide. While those broader business claims sit outside the core AI adoption metrics highlighted by Messari, they provide context for why the exchange is emphasizing infrastructure, scale, and product breadth in its AI narrative.
What the report suggests
Viewed together, the figures in the Messari Pulse report suggest that Bitget’s AI push is gaining early momentum, especially in user-facing products such as Gracy AI and GetAgent. At the same time, the company is trying to differentiate itself through the back-end architecture of Agent Hub and the controlled execution framework of GetClaw. The strategy appears to be centered on building a closed loop where AI can analyze markets, access infrastructure, guide users, and execute trades within a single platform environment.
As with all exchange-provided metrics and sponsored announcements, readers should interpret the data within that context. The material originated from a press release supplied by Bitget, and the report primarily reflects disclosed platform progress and adoption indicators rather than an independent investment assessment. It also does not change the underlying risks of digital asset markets, where volatility remains high and losses can be significant.
Still, the report offers a useful snapshot of how crypto trading platforms are evolving beyond simple order matching and charting. If the adoption figures continue to scale, Bitget’s AI stack could become an important case study in how exchanges move from offering standalone AI features to building AI-native trading infrastructure.