HyperFlow Risk Agent

HyperFlow Risk Agent is an AI-ready risk intelligence layer for autonomous trading systems. The project focuses on a key problem in algorithmic trading: many systems can generate trade signals, but they do not always have a separate control layer that checks whether a trade should actually be allowed, scaled down, blocked, or escalated before execution. HyperFlow Risk Agent receives structured trade or market-event data through a FastAPI backend, evaluates the risk profile, produces a normalized risk score, assigns an action such as ALLOW, SCALE, BLOCK, or KILL_SWITCH, and returns an explanation for the decision. The goal is to make every trading decision traceable, reviewable, and useful for future model training. The demo includes an interactive API, a live dashboard, risk scoring, action distribution, active risk cluster tracking, system health indicators, and recent decision logs. The dashboard acts as a command-center view so a user can quickly understand what the system is seeing, how risky the current environment is, and what decisions the risk engine is making. The long-term vision is to turn HyperFlow into a safety and reasoning layer for AI-powered trading infrastructure. Instead of only chasing entries and exits, the system focuses on discipline, explainability, evidence capture, and controlled execution. Every decision can become training data, allowing future versions of the system to learn from previous outcomes and improve its risk logic over time. This project was built with Python, FastAPI, JSON-based data structures, automated tests, and a lightweight dashboard interface. It is prepared for deployment and designed to be extended with more advanced AI models, hardware-accelerated inference, broker integrations, and deeper analytics for drawdown, exposure, market regime, and model confidence.