AI trading systems can process massive amounts of market information, but relying on AI alone for financial decisions introduces risks such as inaccurate calculations, overconfidence, and poor risk control. Traditional quantitative systems, meanwhile, may lack the ability to interpret real-time news, sentiment, and market context. PRISM solves this by combining AI-driven analysis with deterministic quantitative and risk controls. Seven specialized agents examine a potential opportunity from different perspectives, with the News Agent identifying real-time catalysts and assessing their source, timing, uncertainty, and potential impact. Quantitative, Fundamental, Industry, Macro, and Market Reaction agents then independently validate the signal before the Trading Decision Agent produces a structured proposal. A Risk Management agent challenges the proposal, but none of the AI agents can authorize or execute a trade. Every proposal must pass PRISM’s six-tier deterministic risk gates, which independently verify authorization, portfolio exposure, instrument and volatility constraints, data freshness, trade economics, and exit conditions. What makes PRISM different is what happens beyond the trade. Decision Stories preserve the evidence and reasoning behind every decision, creating an auditable path from the original news catalyst to execution—or a NO_TRADE decision. ShadowFund then asks what would have happened under alternative choices, including cash, smaller positions, contrarian trades, or an unconstrained AI strategy. Together, these features allow PRISM not only to trade, but to explain, audit, and measure whether its decisions were actually better.
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