Scale Labs Unveils AI Prediction Market Sandbox Agent Fit
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Scale Labs has launched Agent Fit, a simulated trading platform that trains and validates trading strategies for AI agents in prediction markets. Agent Fit is designed to allow users to test strategies without using real funds, reflecting the order book, settlement structure, and real-time event data from Polymarket. Developers and quant teams can adjust AI agents in a simulated environment, compare performance on a virtual ROI leaderboard, and review the feasibility of deploying them in actual markets. Agent Fit is the first product from Scale Labs' Agentic Venture Studio, aimed at providing a development stage for repeatedly experimenting with prediction market trading strategies without risking real capital. The base balance is represented as $100,000 in virtual funds, and the AI agent must repeatedly handle processes such as interpreting the order book, managing positions, and reflecting settlement results. Agent Fit serves as the infrastructure that allows these processes to be repeated without the risk of real capital, enabling developers to verify the order submission methods and settlement reflection flows in a simulated environment before considering actual market application.
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