Wintermute plans to turn AI investments into one of its main growth drivers: the company intends to invest about $1 billion in high-frequency trading infrastructure, data centers, and artificial intelligence technologies to become more active in the equities, commodities, and currency markets.
This marks a significant shift for Wintermute from its usual cryptocurrency specialization to a broader financial business. Currently, non-crypto segments account for about 10% of revenue, but by the end of 2027, the company wants to increase their share to more than 50%.
What Is Included in Wintermute’s Plan
The London-based company expects to spread investments over about five years. The main investment areas:
- Computing infrastructure.
- Data storage.
- Network capacity.
- Systems for training quantitative models.
In Wintermute’s business, AI is expected to help train quantitative models on large volumes of market information, find trading signals faster, and support high-frequency strategies outside the crypto market. The expected effect is a stronger technology base for working with stocks, commodity instruments, and currencies.
Wintermute founder and CEO Evgeny Gaevoy plans to finance this program from retained earnings. He also noted that competition in traditional markets has long been about more than just fighting for microseconds in trade execution: success requires data, models, and a reliable technology base.
- Plan/Event: About $1 billion investment in AI infrastructure and high-frequency trading. Description/Goal: strengthen Wintermute’s technology base. Timeline: about five years.
- Plan/Event: Business growth outside cryptocurrency markets. Description/Goal: receive more than half of revenue from non-crypto segments. Timeline: by 2027.
- Plan/Event: Accelerate diversification. Description/Goal: reduce dependence on the crypto market amid declining activity and average daily volumes at Wintermute. Timeline: current stage of strategy.
Why the Company Is Accelerating Diversification
The shift toward stocks, commodities, and currencies comes after a cooling of activity in the crypto market. Wintermute’s average daily trading volume this year fell to about $10 billion from $15 billion in 2025. Pressure increased after Bitcoin dropped nearly in half from its October peak above $126,000.
At the same time, institutional clients remain an important part of the business. In the first half of 2026, they accounted for a record 72% of spot OTC trading volume at Wintermute.
Evgeny Gaevoy stated that the private company was profitable in 2025 and expects to remain profitable this year. Specific financial figures were not disclosed. During the 2021 bull market, Wintermute recorded a profit of $582 million.
Competition With Major Wall Street Players
The new investments are expected to help Wintermute compete with market participants such as Jane Street, Citadel Securities, and XTX Markets. The scale of the technology race is already high: XTX Markets, which executes more than $250 billion in trades daily, previously announced plans to spend 1 billion euros, or about $1.15 billion, on five data centers in Finland.
Jane Street is also preparing to build and fund its own data center. Against this backdrop, Wintermute is essentially entering the same infrastructure league, where not only trading algorithms matter but also access to computing resources, quality data, and fast networks.
How Wintermute Is Moving Beyond Cryptocurrency
The expansion did not start from scratch. In 2025, Wintermute began trading exchange-traded funds and perpetual futures linked to real assets. In March, the company added 24/7 exposure to WTI oil, and in early 2026, it launched a prediction markets division.
Wintermute’s U.S. division recently obtained licensed broker-dealer status. This allows it to trade stocks and stock options, as well as act as an authorized participant for exchange-traded funds.
In the crypto market, Wintermute remains a prominent market maker working with digital assets, including Ethereum. However, the new strategy shows that cryptocurrency is no longer the company’s only growth center. With the development of Wintermute Ventures, interest in venture capital, and strengthening of technology infrastructure, the business is gradually becoming broader than classic crypto market making.
Can You Invest Using AI
AI can help automate part of the investment process: quickly analyze large volumes of market data, look for recurring signals, compare assets, and show how portfolio risk is changing.
In practice, it is used to analyze financial statements, check news and market data, select ideas, rebalance portfolios, and control limits. The decision to make a trade usually remains with the investor or manager, since the model can make mistakes and rely on incomplete data.
Where AI Investments Go and How to Choose Assets
The main areas of AI investment include software development, cloud and computing infrastructure, data centers, data storage, business services, chips, and other hardware.
When choosing AI company stocks and individual projects, it is important to look beyond bold technology claims. Investors should consider revenue, margins, product quality, access to data, team, client base, competitive advantages, and the company’s ability to turn AI into a sustainable business.
Direct investments provide a more targeted bet on a specific company or project but increase dependence on its outcome. ETFs spread investments among several issuers and simplify diversification, though they reduce control over portfolio composition and do not eliminate market risk.
Why Investors Are Looking at AI and What Risks to Consider
Interest in AI is driven by several factors: companies are using automation, demand for computing and data is growing, and the financial sector is seeking faster ways to analyze markets and reporting. If the technology provides businesses with significant savings or a new source of revenue, this can support the value of such companies, but potential returns are not guaranteed.
Risks are also significant: high stock valuations, expensive infrastructure, competition, regulatory restrictions, model errors, and dependence on data quality. Diversification across sectors, countries, asset types, and entry methods—through individual stocks, ETFs, venture projects, or infrastructure companies—helps mitigate these risks.
Globally, AI prospects are tied to the adoption of technology in finance, industry, healthcare, software development, and corporate services. In Russia, potential depends on business demand for automation, availability of computing power, talent, and local technology solutions.
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