CoinQuant trading platform has expanded its architecture to serve both human traders and autonomous AI agents, marking a significant evolution from its existing user base of over 15,000 users since launch. According to reports from CoinQuant, the platform converts plain-English strategy descriptions into complete algorithmic trading systems, including entries, exits, position sizing, filters, and risk rules. The expansion targets the emerging agent economy, where AI agents settled more than $73 million across 176 million blockchain transactions in the twelve months through April 2026, as reported by research firm Keyrock. As reported by CoinQuant, the platform's no-code approach allows users to create and test trading strategies using verbal or written input, with the system automatically generating complete algorithmic systems for execution.
CoinQuant's expansion introduces a unified intelligence system combining institutional-grade backtesting, structured market data from providers including Kaiko and Financial Modeling Prep, AI-powered optimization, and CoinQuant's proprietary Domain Expert system. According to Maan Ftouni, Founder and CEO of CoinQuant, the platform delivers "structured validation, disciplined risk management, and intelligence infrastructure" that ensures no strategy goes live unvalidated. The system embeds backtesting, risk metrics, and parameter optimization directly into the workflow, with every strategy built, tested, and deployed contributing to an anonymized aggregated intelligence layer. Human traders interact through a natural language interface while AI agents connect programmatically through API and MCP integrations to validate strategies and access structured data at scale. As reported by Cointelegraph, while many AI agents connect directly to exchanges and wallets, most rely on raw APIs lacking systematic backtesting, risk analysis, or validated data pipelines, making CoinQuant's systematic intelligence layer particularly valuable.
The broader market CoinQuant is targeting spans more than a million potential autonomous trading agents active across crypto markets, according to the company's announcement. The expansion into agent-native infrastructure allows autonomous AI agents to deploy, test, and execute crypto trading strategies without human intervention at each step, positioning CoinQuant within the fast-growing market for machine-to-machine crypto infrastructure. As reported by CoinQuant, the platform's growing base of over 15,000 traders validates product-market fit and generates structured strategy intelligence that multiplies value through high-volume programmatic validation and automation workflows. The agentic economy is fundamentally transforming financial markets, with open-source agent frameworks accelerating autonomous financial activity, as reported by Cointelegraph.
CoinQuant is preparing to launch its automated strategy execution layer on HyperLiquid as its second major revenue stream, enabling validated strategies to transition seamlessly from backtest to live deployment within the same intelligence framework. The company is currently raising a $3 million Seed round to support product development, infrastructure scaling, and global expansion. Additionally, CoinQuant is developing HYDRA, a hierarchical multi-agent architecture designed for advanced research, risk modeling, and strategy optimization. With over 15,000 users validating demand for structured trading intelligence, CoinQuant aims to become the intelligence backbone of algorithmic trading in the agent-driven financial era.
