The time gap between public announcement of a vulnerability—its detection and reporting to stakeholders—is an important factor for cybersecurity of corporate networks. A large delay preceding an elimination of a critical vulnerability presents a significant risk to the network security and increases the probability of a sustained damage. Thus, accelerating the process of vulnerability identification and prioritization helps to red the probability of a successful cyberattack. This work introduces a flexible system that collects information about all known vulnerabilities present in the system, gathers data from organizational inventory database, and finally integrates and processes all collected information. Thanks to application of parallel processing and non relational databases, the results of this process are available subject to a negligible delay. The subsequent vulnerability prioritization is performed automatically on the basis of the calculated CVSS 2.0 and 3.1 scores for all scanned assets. The environmental CVSS vector component is evaluated accurately thanks to the fact that the environmental data is imported directly from the organizational inventory database.