<p>Ransomware blocks access to data or a system. It demands a ransom to restore access. In terms of ransomware, preventative cybersecurity is essential. The present work creates a Next Generation Antivirus enterprise. Our solution is able to detect ransomware before it is even clicked on by the user. Our antivirus monitor and weight the behavior of 672 suspicious behaviors. This occurs when the suspect file is executed in a controlled environment. The characteristics and behaviors monitored via dynamic analysis were used as input parameters for machine learning algorithms. It classifies them as benign or malignant. The proposal aims to serve both low-capacity devices and large data centers. It will do this by tailoring the pattern recognition stage to the user’s profile. We suggest using shallow networks for low-capacity devices. In opposition, deep networks for large corporations. Our simpler networks achieve an average accuracy of 95.44%. The authorial antivirus can detect ransomware before it runs. It does this, rather than relying only on reactive measures. The system uses advanced machine learning and neural networks. It can find patterns linked to ransomware before it fully runs.</p>