Traditional security tools, like Splunk, demand that modern enterprises centralize their massive volumes of security data for threat detection. This method is both slow and expensive, and it’s becoming increasingly impractical in dynamic cloud environments where data is exploding and dispersed.
AI cybersecurity firm Vega Security aims to transform this approach by conducting security operations where data natively resides, integrating directly into cloud services, data lakes, and existing storage systems. TechCrunch has exclusively learned that this two-year-old company just secured a $120 million Series B funding round to accelerate this vision.
The latest investment, spearheaded by Accel with contributions from Cyberstarts, Redpoint, and CRV, almost doubles Vega’s valuation to $700 million, bringing its total funding to $185 million. The startup intends to utilize these funds to further enhance its AI-native security operations suite, strengthen its go-to-market team, and expand its global presence.
Shay Sandler, Vega’s co-founder and CEO, informed TechCrunch that the prevalent operating model of SIEM (security information and event management) – which has dominated this field for the past two decades – is not only