Qevlar AI: Can Autonomous AI Handle SOCs?

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Ahmed Achchak, Qevlar AI Co-Founder and CEO (Left) and Hamza Sayah, CTO & Co-Founder at Qevlar AI (Right)
Qevlar AI has secured US$30m worth of funding to support its proactive, autonomous AI SOC platform which improves enterprise security posture

AI has been steadily transforming the cybersecurity landscape for years.

Reinforcing this shift, Qevlar AI – a company specialising in AI-driven transformation of security operations centres (SOCs) – has secured US$30m in funding to advance its autonomous AI SOC platform.

Designed to enable a more proactive approach to security, the platform uses AI to shorten investigation times by as much as tenfold, bringing them down to roughly three minutes.

According to security leaders, the platform delivers measurable business benefits, including significantly “reduced operational costs”, while it also improves “operational security efficiency and excellence”.

Ahmed Achchak, Co-Founder and CEO at Qevlar AI, says: “Today, most SOCs measure success by how many alerts they tackle and how quickly they are resolved. But this is a firefighting approach that tells you nothing about your security posture.

Ahmed Achchak, Co-Founder and CEO at Qevlar AI

“The only way to understand that is by being able to identify patterns in the trends and that requires a completely new approach.

“We’re moving from autonomous alert investigations to an intelligent AI SOC platform that uncovers insights that transform how teams not only deal with alerts, but stop them from recurring.

“We’re putting out the fire and finding out what started it to make sure it doesn’t happen again.”

Moving beyond reactive security

Recent findings from Forrester reveal that just three attack scenarios can generate thousands of alerts.

Meanwhile, a report from Gartner estimates that around 70% of the time spent on threat detection and response is consumed by investigation and triage – processes that can be automated through Qevlar’s platform.

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With analysts relieved from time-consuming investigative work, they can instead focus on proactive activities such as threat hunting and incident response planning.

At the same time, Qevlar’s AI platform manages tasks including data enrichment, detecting alert patterns and generating reports.

These capabilities have led to adoption by Fortune 500 organisations including Mercedes-Benz and Sodexo, as well as major global managed security service providers (MSSPs) such as Orange Cyberdefense, ECI and Atos.

Qevlar's impressive momentum

Qevlar’s latest funding round – which brought in US$30m – was co-led by Partech and Forgepoint Capital International, with participation from EQT Ventures.

Damien Henault, Managing Director & Partner at Forgepoint Capital International | Credit: Forgepoint Capital International

“We have been impressed by Qevlar AI’s momentum over the last 12 months,” says Damien Henault, Managing Director & Partner at Forgepoint Capital International.

“It has seen exceptional commercial traction with both Fortune 500 enterprises and leading MSSPs, with its customer base expanding globally.

“It makes perfect sense for us to increase our backing as it evolves its offering from alerts investigation to a complete end-to-end next-generation AI SOC insights platform, extending all the way from Level 1 investigation to Level 2 enhanced detection and Level 3 remediation.”

Reza Malekzadeh, General Partner at Partech

According to Qevlar, the newly-raised funds will support further development of the platform as it leverages insights gathered during investigations to pinpoint root causes and implement remedial actions – ultimately strengthening the overall security posture and health of each organisation.

Reza Malekzadeh, General Partner at Partech, adds: “Qevlar AI stands out as a company with the potential to be genuinely transformative; rather than just allow SOCs to process alerts faster, it is giving them the power to tackle the underlying issues.

“The company’s success to date highlights just how much the market needs this approach.”

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