Coinrule's AI Trading Agents Make the Leap From Crypto to Stocks

LONDON, UK – February 25, 2026 – Coinrule, a London-based AI trading company backed by Y Combinator, today announced a significant expansion of its services from the volatile world of cryptocurrency into the heart of traditional finance. The company has extended its AI-driven “agentic trading” framework to U.S. equities and Exchange-Traded Funds (ETFs), activating integrations with seven major retail brokerage platforms.

Effective today, users can connect their accounts from Trading 212, Tradier, E*TRADE, tastytrade, Public, Webull, and TradeStation to deploy AI-assisted trading agents. This move allows retail investors to automate their stock and ETF trading strategies using the same interface previously dedicated to digital assets. The expansion is underpinned by an AI model trained on a massive dataset of over 1.7 million user-built strategies executed on its platform between 2022 and 2026.

This strategic pivot aims to bridge the gap between sophisticated institutional trading tools and the rapidly growing retail investor market. “Our community has already built and deployed 1.7 million strategies across crypto markets,” said Gabriele Musella, CEO of Coinrule, in the announcement. “What we are releasing now is the evolution of that work into agent-based equity execution. Retail traders have long been experimenting with automation. Now, they are building investment skills for agents and supervising capital through structured AI systems.”

From Crypto Proving Grounds to Wall Street

Coinrule's journey from a crypto-centric platform to a multi-asset tool reflects a broader trend of technological innovation flowing from digital asset markets into traditional finance. Having honed its technology with a global user base of over 400,000 traders across more than 30 crypto exchanges, the company is now applying those lessons to the significantly larger and more established equities market.

The core of the offering is what the company describes as a “human-in-the-loop” model. Unlike static trading bots that execute rigid, pre-programmed commands, Coinrule's system uses AI agents that operate within boundaries and objectives set by the user. These agents are designed with strategy memory and context retention, allowing performance data from past trades to inform future execution logic through a process of continuous refinement. This positions the AI less as an autonomous manager and more as an intelligent co-pilot, executing a human-devised strategy with greater speed and discipline.

This approach seems tailored to a specific demand. The company's proprietary data indicates that over 76% of its active users were seeking to integrate AI-driven execution into their stock trading workflows, signaling a clear appetite for more sophisticated automation tools among individual investors.

Riding a Wave of Retail AI Adoption

The timing of Coinrule's expansion appears well-aligned with a surge in AI adoption among retail investors. A 2025 report from eToro highlighted a 75% year-over-year increase in AI tool usage among U.S. retail investors, with 30% now using AI to help pick or alter their investments. This trend is particularly pronounced among younger demographics, with millennials leading the charge.

Investors are turning to AI to save time on research, gain an analytical edge, and access capabilities that were once the exclusive domain of institutional trading desks. The global market for algorithmic trading among retail investors was valued at over $3.5 billion in 2024 and is projected to more than double by 2030, according to industry reports. This rapid growth creates a fertile environment for platforms like Coinrule that aim to democratize access to advanced financial technology.

However, the enthusiasm is not universal. Recent surveys indicate a degree of skepticism remains. A February 2026 study from Cerulli Associates found that only 38% of affluent investors are comfortable with AI in their financial advisory relationships. This suggests that while investors are eager to use AI for research and analysis, many are still hesitant to cede final decision-making authority, reinforcing the potential appeal of Coinrule's supervised, human-in-the-loop framework.

A Crowded Field of Intelligent Competitors

Coinrule is not entering an empty arena. The market for AI-powered retail trading tools is becoming increasingly crowded and competitive. A host of platforms are already vying to become the go-to solution for tech-savvy traders.

Firms like Trade Ideas have long offered their “Holly AI” engine for generating predictive stock trades, while Tickeron provides powerful AI for pattern recognition across stocks and ETFs. Other competitors, such as AlgosOne and Kavout, focus on using AI and quantitative models to score and rank investment opportunities. These platforms often boast features like advanced backtesting, real-time market scanning, and AI-powered chart analysis, setting a high bar for new entrants.

To stand out, Coinrule will need to emphasize its unique value proposition: a unified, multi-asset platform that grew out of the demanding 24/7 crypto market, combined with an AI model trained on a vast repository of real-world, user-generated strategies. The integration with a broad swath of popular retail brokers is a key strategic advantage, lowering the barrier to entry for users who can connect their existing accounts rather than needing to fund a new one.

Navigating the Regulatory Tightrope

Perhaps the most significant challenge for Coinrule and its competitors is the evolving regulatory landscape. Financial regulators, including the U.S. Securities and Exchange Commission (SEC) and the Financial Industry Regulatory Authority (FINRA), are paying close attention to the proliferation of AI in financial markets. While no comprehensive AI-specific rules exist yet, regulators have made it clear that existing rules around investor protection, fairness, and transparency apply.

Key concerns revolve around the “black box” problem, where the decision-making process of an AI is opaque, and the potential for inherited biases in algorithms to lead to unfair outcomes. Regulators are focused on ensuring that firms do not overstate their AI's capabilities or use the technology to place their interests ahead of their clients'.

The rise of increasingly autonomous “agentic AI” also creates an “accountability gap,” raising complex questions about liability when an automated trade goes wrong. By emphasizing financial guardrails and a human-in-the-loop system, Coinrule appears to be proactively addressing these concerns, framing its platform as a tool for augmenting human oversight, not replacing it entirely.

As AI-driven trading moves from a niche activity to a mainstream phenomenon, the success of platforms in this space will depend not only on the sophistication of their technology but also on their ability to build trust and responsibly navigate the complex web of market risks and regulatory expectations.