We will build a complete component of an algorithmic trading system in Rust—a decision service. It accepts the market state from the client—technical indicators and their short history—forms a request to the Jev AI model from them, receives probabilistic assessments for each side of the trade from it, and turns them into one decision according to a rule: open a long position, a short position, or stay out of the market.
The main principle: the model assesses, the service decides. The model does not calculate indicators or issue orders—it says how closely the market picture resembles the one described in the criteria, while the rule that turns its assessments into an action remains ordinary code: with thresholds for the sides of the trade and two brakes—one for market overheating and one for hostile volatility. Along with the data, the model receives a description of each field, while the thresholds, questions, and criteria live in the configuration with the ability to override them locally.