Aurum Forest AI

Aurum Forest AI

Aurum Forest AI - Neural Core XAUUSD

Aurum Forest AI is a state-of-the-art Expert Advisor engineered specifically for XAUUSD (Gold). Powered by a native, pre-trained ONNX Machine Learning model (Random Forest Classifier), this system doesn't rely on outdated static indicators. Instead, it dynamically processes 20 complex market features in real-time—including Smart Money Concepts (SMC), Fair Value Gaps (FVG), and Multi-Timeframe volatility—to execute high-probability scalping and intraday trades.

This is NOT a dangerous martingale or grid system. Every single trade is protected by strict logic and hard Stop Losses.

? KEY ADVANTAGES:

• True Machine Learning Core: 100% native .onnx integration. The Neural Network evaluates structural shifts, momentum, and liquidity sweeps before making any decision.

• Multi-Timeframe Analysis: Scans H1 for macro-trend structure and executes precisely on the M15 timeframe.

• Advanced Drawdown Protection: Features a built-in 'Daily Limit Threshold'. If the daily loss limit is reached, the EA halts all operations to protect your capital.

• Secure Profit Protocol: Automatically trails and locks in profits when the target threshold is reached.

• Zero Toxic Logic: 100% NO Martingale, NO Grid, NO Arbitrage.

⚙️ RECOMMENDED SETUP:

• Symbol: XAUUSD (Gold)

• Timeframe: M15 (The EA will internally scan H1)

• Minimum Deposit (Standard Account): +$100

• Minimum Deposit (Cent / USC Account): $20 (2,000 USC) - Highly Recommended for optimal risk allocation and smooth compounding!

• Broker: Any low-spread broker (Hedging account type).

• VPS: Highly recommended to run 24/5 without interruption.

? HOW TO INSTALL: Simply attach the EA to your XAUUSD M15 chart. The ONNX model is already hardcoded inside the executable file. No need to download external DLLs or place model files in complex folders. Plug, play, and let the AI do the heavy lifting.

Disclaimer: Past performance does not guarantee future results. Please test on a Demo or Cent account first to understand the neural network's behavior before scaling up.