Vega Nabs $120M Series B to Reimagine Enterprise Cyber Threat Detection

Modern enterprises contend with an overwhelming volume of security data. However, conventional tools such as Splunk still mandate that companies consolidate all this information into a single location before threats can be identified. This method is not only slow and expensive but is also increasingly failing in cloud environments where data volumes are exploding and distributed across numerous locations.

AI cybersecurity startup Vega Security aims to fundamentally alter this approach by executing security operations directly where the data already resides, integrating within cloud services, data lakes, and existing storage systems. The two-year-old firm recently secured a $120 million Series B funding round to scale this innovative vision, an exclusive revelation by TechCrunch.

The latest funding round, led by Accel with contributions from Cyberstarts, Redpoint, and CRV, almost doubles Vega’s valuation to $700 million, bringing its total capital raised to $185 million. This investment will be utilized to further develop its AI-native security operations suite, bolster its go-to-market team, and facilitate global expansion.

Shay Sandler, co-founder and CEO of Vega, informed TechCrunch that the prevailing operating model of SIEM (Security Information and Event Management) — the dominant technology in this sector for the past two decades — is not merely “crazy expensive,” but is also progressively hindering the success of AI-native security operations. In complex cloud environments, he argues, the current model frequently escalates exposure to threat actors.

“Vega has defined a new operating model that enables organizations to leverage the full potential of their enterprise data to achieve incident response readiness, without all the complexity, the cost, the drama,” Shay Sandler told TechCrunch. He added, “We want to simply enable them to reach AI-native detection response capability anywhere the data is, at scale.”

Like many cybersecurity founders, Sandler honed his skills in the Israeli military’s cybersecurity unit before becoming one of the founding employees of Granulate, which Intel acquired for $650 million in 2022. After a year with Intel, Sandler decided to “do it big time in the cybersecurity world.”

This impressive background partially drew the attention of Andrei Brasoveanu, a partner at Accel. However, it was also Vega’s ambitious approach to security management in a market already dominated by a single player: Splunk.

Brasoveanu conveyed to TechCrunch that legacy SIEM companies like Splunk, which Cisco acquired for $28 billion in 2024, have faced criticism in recent years due to the inherent difficulty in scaling their solutions. He noted their struggle to process the immense surge in data volumes driven by AI.

“Splunk and every contender since has always centralized the data, but by doing that you essentially hold the customer hostage,” Brasoveanu stated.

Nevertheless, it is often simpler to criticize the status quo than to undertake the effort required to transition to a superior alternative—a challenge well understood by any startup aiming to penetrate enterprise budgets. This understanding led Sandler to define Vega’s “North Star”: not only to build a more cost-effective solution with enhanced threat detection capabilities but also “to make it no drama, as simple as possible for the biggest, most complex enterprises in the world to adopt it within minutes.”

Vega’s strategy appears to be proving successful. The 100-person startup has already secured multi-million-dollar contracts with prominent banks, healthcare companies, and Fortune 500 firms, including cloud-intensive entities like Instacart.

Sandler explained this rapid adoption, stating, “The only reason they would do that with a two-year-old startup is because the problem is so painful and other solutions on the market require an unrealistic expectation that the enterprise change the way they operate or do two years of data migrations.” He concluded, “Vega enables them to just plug and play and achieve immediate detection response value.”