Revolut has connected Revolut X, its dedicated cryptocurrency trading platform, to several third-party artificial intelligence assistants, allowing customers to use natural-language prompts to review markets, monitor portfolios and prepare trades without working directly inside the Revolut X interface.
The integration links Revolut X with AI assistants including Claude, Gemini, OpenClaw and Cursor through a common interface designed to let customers ask questions, request data and build trading ideas in plain English. Revolut said the feature is intended to make advanced trading tools easier to use by removing the need for coding skills or separate analytics software.
The new setup allows Revolut X users to retrieve live market prices, check portfolio performance, set custom price alerts and manage open positions through connected AI platforms. Customers can also describe a trading idea in everyday language, such as testing a Bitcoin grid strategy over a chosen historical period, and receive backtested results, performance figures and related market metrics.
The company said customers must still approve every order before it is executed. Revolut has also said it does not endorse the third-party AI assistants linked to the service and will not be responsible for inaccurate outputs, mistaken prompts or unintended transactions caused by external software errors.
The move places Revolut more directly into the fast-growing market for AI-assisted trading, where financial technology companies are trying to combine conversational interfaces with real-time market access. It also raises fresh questions about risk controls, user responsibility and the reliability of automated tools in volatile cryptocurrency markets.
Revolut said it now has more than 75 million retail accounts and more than 16 million active crypto users. Its digital asset business in Europe is operated through a Cyprus-based licensed entity under the region’s crypto asset rules.
How the new AI connection works
The integration is built around the idea that traders can interact with market tools through written instructions instead of dashboards, code or manual searches across several platforms.
A customer using a linked AI assistant could ask for current Bitcoin or Ethereum prices, request a summary of portfolio performance over a certain period, compare assets, or set alerts for selected price levels. The same interface can also be used to examine open positions and prepare trades.
The most notable part of the rollout is the ability to test trade ideas with simple commands. Rather than building a model manually, a user can type a prompt describing a strategy, time frame and asset. The connected assistant can then return historical testing results, including how the idea would have performed under past market conditions.
For example, a trader could ask for a Bitcoin grid strategy to be tested over a specific six-month period, or request a comparison between different entry and exit levels. The system is designed to respond with figures that may include hypothetical returns, drawdowns and other analytical measures.
This structure could reduce the barrier to more complex strategy testing. In traditional trading settings, testing strategies often requires spreadsheet work, programming knowledge or specialized trading software. With AI assistants, the same process can be started through a chat window.
However, Revolut’s warning makes clear that the system is not intended to remove human review. Customers remain responsible for checking the order details and confirming activity before any trade is placed.
Revolut X expansion
Revolut X was launched in May 2024 as a desktop crypto trading platform for customers in the United Kingdom. It was designed as a more specialized venue for users who wanted access to digital asset trading beyond the main Revolut app.
The platform expanded to 30 European markets in November 2024. Revolut then released a mobile version in March 2025 for users in the United Kingdom and the European Economic Area.
The AI assistant integration represents another step in Revolut’s effort to build out Revolut X as a separate crypto trading service. By connecting the platform to outside AI tools, the company is moving beyond the standard app-based trading model and toward a more open system where customers can use external interfaces to interact with their accounts.
The company’s scale gives the rollout broader significance. With tens of millions of retail accounts and millions of active crypto users, even a partial adoption of AI-linked trading tools could place natural-language trade management in front of a large consumer base.
Responsibility stays with the user
Revolut’s public position places the final responsibility for trading decisions on the customer.
Bashlykov, who oversees crypto product development at the firm, said users retain full responsibility for confirming every order before execution. That distinction is important because AI systems can misread instructions, produce inaccurate calculations or return responses that appear confident while containing errors.
The company has also said it does not endorse the connected AI tools. That means Revolut is allowing access through supported links, but it is not guaranteeing that the outside assistants will always interpret prompts correctly or provide accurate analysis.
This limitation could become a key issue as AI-assisted trading grows. Natural-language systems are simple to use, but simple instructions can still create complex or risky outcomes. A vague prompt, a misunderstood command or an incorrect assumption by an AI tool could lead to an order that does not match the user’s original intention.
The requirement that users confirm every order is meant to reduce that risk. It creates a final checkpoint before capital is put into the market. Still, traders may need to review not only the order itself, but also the reasoning and data behind it.
That includes checking the asset, size, direction, order type, price level and any conditions attached to the trade. It also means reviewing backtest results carefully, especially when they come from an AI-generated workflow.
Why AI trading tools are growing
The broader financial technology market has been moving quickly toward AI-assisted trading and account management.
Chat-based systems are attractive because they can simplify complicated processes. A user no longer needs to search through multiple pages, charts or menus to find information. Instead, the user can ask the system to summarize market conditions, compare assets or evaluate a trading setup.
This shift is part of a wider move toward automation in finance. Computer-driven trading already accounts for a large share of stock market activity in the United States, with some market estimates placing automated systems at around 70 percent of U.S. equity trading volume. While crypto markets differ from traditional stock markets, they also operate continuously and are heavily influenced by rapid data processing, algorithmic execution and automated risk systems.
Corporate spending on artificial intelligence has also increased sharply. Global funding for AI tools moved above $200 billion last year, reflecting the scale of demand for automation, data processing and productivity software across industries.
In trading, the appeal is clear. AI tools can process large amounts of information quickly, translate user instructions into structured actions and reduce the time needed to test ideas. They can also help less technical users access tools that were once mostly used by professional quant teams or advanced retail traders.
At the same time, faster access does not remove market risk. It can increase it if users rely too heavily on outputs they do not understand.
Industry competition is increasing
Revolut’s move comes as other financial technology and digital asset companies experiment with AI-led trading tools.
Gemini introduced an agent-led system in April 2026 that allowed AI bots to manage trading accounts through the MCP open standard. Liquid followed in May with Co-Invest, a feature designed to allow trade execution through AI chat interfaces.
Earlier in July, Robinhood said its U.S. customers would soon gain access to crypto-focused agentic accounts after pilot testing automated stock trading features.
Together, these developments show how quickly the sector is moving toward AI-driven account interaction. Instead of treating AI as a separate research tool, companies are starting to connect it directly to trading systems.
That shift is significant. A chatbot that only answers market questions carries one type of risk. A chatbot linked to a trading account carries another. Once an AI assistant can help prepare, manage or trigger trades, the quality of prompts, data checks and user confirmations becomes more important.
The competition also suggests that trading platforms are trying to make their services feel more conversational. Instead of asking customers to learn platform-specific tools, firms are building systems that let customers describe what they want and allow software to translate that into action.
The risks behind simple prompts
The new generation of AI-linked trading tools may make markets feel easier to access, but the underlying risks remain complex.
Backtesting is one example. A backtest can show how a strategy might have performed in the past, but it does not prove that the same approach will work in the future. Results can be affected by the chosen time period, assumptions about fees, market liquidity, execution prices and slippage.
AI tools may also summarize backtests in ways that make a strategy appear cleaner or more reliable than it really is. If a user does not check the assumptions behind the figures, the output can create a false sense of confidence.
There is also the risk of prompt ambiguity. A trader might ask for a “small” position, but the system must interpret what small means. A user might request a strategy over “recent market conditions,” leaving the AI to decide the exact time frame. These details matter in fast-moving cryptocurrency markets.
Software errors are another concern. Connected systems depend on data feeds, account permissions, third-party assistants and execution platforms working correctly together. If any part of the chain fails, the outcome may differ from what the user expected.
For that reason, risk controls remain central. Smaller test trades, manual checks, conservative order limits and clear prompts can reduce the chance of costly mistakes. Hard caps on daily order sizes may also help prevent an error from affecting an entire account.
What traders may do next
The launch gives Revolut X users a new way to interact with crypto markets, but the practical impact will depend on how carefully customers use the tools.
For experienced traders, the integration may speed up research workflows and help test ideas more efficiently. For less experienced users, it may make advanced tools more approachable, but it may also make risky strategies easier to deploy without a full understanding of the mechanics.
The key issue is whether AI assistants become decision-support tools or decision-making substitutes. Revolut’s structure, which requires manual confirmation before execution, keeps the user in control at the final stage. But the influence of AI-generated strategy suggestions may still be powerful.
As AI assistants become more closely connected to trading accounts, financial technology firms will face pressure to show that these systems are transparent, reliable and properly limited. Users, meanwhile, will need to treat convenience as only one part of the equation.
Revolut’s integration marks another step toward a future where trading platforms look less like traditional terminals and more like conversations. The technology may make analysis faster and easier, but in crypto markets, speed and simplicity do not eliminate the need for caution.
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