Deep Instinct DSX is an endpoint protection platform that uses a purpose-built deep learning framework to prevent malware infections. The platform employs a neural network trained on hundreds of millions of samples to identify and block known, unknown, and zero-day threats before execution. The DSX Brain operates as the core prevention engine, utilizing deep learning algorithms that self-learn and improve over time without requiring frequent manual updates. The system analyzes files and delivers malicious verdicts in under 20 milliseconds at the endpoint level. The platform includes DIANNA, an AI companion that provides real-time explainability of detected threats. Deep Instinct reports a detection accuracy rate above 99% for unknown threats and maintains a false positive rate below 0.1%. The deep learning approach differs from traditional machine learning-based security tools by processing data through multiple neural network layers, enabling autonomous threat prediction and prevention. The framework continues to maintain prevention efficacy even when the detection models are six months old or older. Deep Instinct DSX targets ransomware, malware, and other file-based threats across endpoint environments. The platform is designed to reduce alert fatigue for security operations center teams by minimizing false positives while maintaining high detection accuracy for genuine threats.