AIQuant, a new platform, has launched autonomous trading bots that operate across Solana, BNB Chain, and Base, allowing users to configure and deploy algorithmic strategies without continuous manual input.
The platform’s trading agents, referred to as AI Quants, function around the clock and execute trades using real-time blockchain data.
Users can design strategies, set risk parameters, and track performance through a central dashboard.
Instead of offering subscription tiers, the platform charges a one-time activation fee, initially in ETH and later in its AIQ token. The approach is aimed at making high-frequency, automated trading tools accessible to a broader audience.
According to the project, each AI Quant comes with options for evaluation criteria, adaptive stop-loss and take-profit settings, and slippage controls.
A bonding curve feature with tokenized quants is scheduled for later in 2025, designed to expand the ecosystem.
The launch positions AIQuant in a growing segment of crypto where algorithmic trading intersects with artificial intelligence.
Rivals in the space include decentralized exchanges and trading platforms that offer automation tools, though few have integrated cross-chain functionality across multiple networks from day one.
Marlon Williams, founder of AIQuant, told Yellow Media that the tool was built to simplify trading in an increasingly fragmented token landscape.
He added that the bots are designed to function without human emotion, enabling continuous trading activity.
The broader trend highlights attempts to lower barriers for both retail and professional traders by providing algorithmic tools once limited to institutional finance. While algorithmic trading has been common in traditional markets, its application in decentralized crypto markets remains an emerging area.
AIQuant’s entry also raises questions about potential risks, including reliance on automated systems, the complexity of risk management across volatile assets, and the impact of widespread bot-driven trading on market behavior.
