As cyber threats continue to increase in scale and sophistication, security operations centres across industries are facing growing pressure to analyse vast volumes of threat alerts while maintaining strong protection against potential attacks. In response to this challenge, French cybersecurity company Qevlar AI has raised $30 million in funding to further develop its autonomous artificial intelligence platform designed to assist security teams in managing and investigating cyber threats more efficiently.
The funding round was jointly led by Partech and Forgepoint Capital International, with participation from EQT Ventures. The new investment will support the continued development of Qevlar AI’s autonomous SOC platform and help the company expand its technology capabilities as demand grows for automated security operations.
Growing pressure on security operations teams
Security operations centres play a critical role in monitoring digital systems for suspicious activity and potential cyber threats. These teams analyse alerts generated by security tools such as intrusion detection systems, endpoint protection software and network monitoring platforms.
However the number of alerts generated by modern security systems has grown dramatically in recent years. Even a limited number of attack scenarios can produce thousands of alerts across multiple systems. As a result security analysts often spend significant time reviewing alerts that may ultimately prove harmless.
The triage and investigation process can consume a large share of an SOC team’s resources. At the same time organisations face shortages of skilled cybersecurity professionals, making it difficult for teams to keep pace with the growing volume of threats.
This operational strain has led many organisations to explore automation and artificial intelligence technologies that can help security teams analyse alerts more efficiently.
Automating the investigation process
Qevlar AI focuses on automating the investigation stage of security operations. Instead of requiring analysts to manually review large volumes of alerts, the company’s platform uses artificial intelligence to analyse security signals across multiple systems.
The platform performs tasks such as enriching alert data, identifying correlations between events and generating investigation reports. By automating these processes, the system aims to reduce the time required to analyse alerts while helping security teams focus on more strategic tasks.
Security analysts can then devote more attention to activities such as threat hunting, developing incident response strategies and improving overall security resilience.
The technology is currently used by managed security service providers and large enterprises that rely on security operations centres to monitor their digital infrastructure.
Building an autonomous AI SOC platform
Qevlar AI is positioning its technology as part of a broader shift toward autonomous security operations. Rather than focusing solely on responding to individual alerts, the company aims to help organisations gain deeper insight into the underlying causes of security events.
The platform uses artificial intelligence to enrich and correlate security signals from multiple sources. This approach enables security teams to identify patterns and trends across alerts that may indicate broader security issues.
By analysing these patterns the system can help organisations detect potential threats earlier and improve the consistency of security investigations.
According to the company organisations using the platform have reported reduced investigation times and improved capacity to analyse alerts more thoroughly while managing increasing alert volumes.
Moving beyond reactive security models
Traditionally many security operations centres measure performance based on how quickly alerts are processed or resolved. While this approach helps maintain operational efficiency, it can sometimes limit the ability of security teams to identify deeper systemic issues.
Qevlar AI aims to move beyond this reactive model by enabling organisations to analyse trends and recurring patterns in security alerts. By identifying root causes and recurring vulnerabilities the platform can help teams take corrective action and strengthen their overall security posture.
This shift from reactive alert management to more strategic threat analysis represents a broader evolution in how organisations approach cybersecurity.
Expanding the platform’s capabilities
The newly raised funding will support the next stage of development for Qevlar AI’s platform. The company plans to enhance its autonomous investigation capabilities and extend the system beyond alert analysis into broader security intelligence functions.
Future developments will focus on enabling the platform to generate deeper insights into underlying security issues, helping organisations identify root causes of threats and implement long term improvements.
As cyber threats continue to evolve and the volume of security alerts grows, Qevlar AI aims to position its autonomous SOC platform as a tool that allows security teams to manage complexity more effectively while strengthening organisational resilience against cyber risks.
