Fashionable enterprises generate monumental quantities of security knowledge, however legacy instruments like Splunk nonetheless require corporations to retailer all of it in a single place earlier than they’ll detect threats — a gradual and expensive course of that’s more and more breaking down in cloud environments the place volumes are exploding and knowledge lives in every single place.
AI cybersecurity startup Vega Safety desires to flip that strategy by working security the place the information already lives, implementing in cloud companies, knowledge lakes, and current storage programs. And the two-year-old agency simply raised a $120 million Sequence B spherical to scale that imaginative and prescient, information.killnetswitch has completely discovered.
Led by Accel with participation from Cyberstarts, Redpoint, and CRV, the brand new spherical practically doubles Vega’s valuation to $700 million, and brings its whole funding to $185 million, cash the startup will use to additional develop its AI-native security operations suite, beef up its go-to-market crew, and broaden globally.
Shay Sandler, co-founder and CEO of Vega, instructed information.killnetswitch that the present working mannequin of the SIEM (security info and occasion administration) — the dominant expertise on this area for the final 20 years — is just not solely “loopy costly,” however can also be more and more inflicting AI-native security operations to fail. In advanced cloud environments, he says, the present mannequin usually will increase publicity to menace actors.
“Vega has outlined a brand new working mannequin that permits organizations to leverage the total potential of their enterprise knowledge to attain incident response readiness, with out all of the complexity, the fee, the drama,” Sandler instructed information.killnetswitch. “We wish to merely allow them to achieve AI-native detection response functionality wherever the information is, at scale.”
Like so many cybersecurity founders, Sandler did his time within the Israeli navy’s cybersecurity unit earlier than being one of many founding staff behind Granulate, which Intel acquired for $650 million in 2022. After a 12 months at Intel, Sandler determined to “do it massive time within the cybersecurity world.”
That pedigree is partly what attracted the eye of Andrei Brasoveanu, a associate at Accel. However it was additionally Vega’s formidable strategy to security administration in a market that’s already dominated by one participant: Splunk.
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Brasoveanu instructed information.killnetswitch that legacy SIEM corporations like Splunk, which Cisco acquired in 2024 for $28 billion, have been criticized lately as a result of their options are troublesome to scale. They fail at processing the insane rise of information volumes pushed by AI.
“Splunk and each contender since has at all times centralized the information, however by doing that you just basically maintain the shopper hostage,” Brasoveanu stated.
Nonetheless, typically it’s simpler to hate the established order than do the work of constructing a swap to a greater various, a quandary any startup making an attempt to breach enterprise budgets understands. That’s why Sandler says Vega’s “North Star” was to not solely construct an answer that’s less expensive and higher at menace detection, however “to make it no drama, so simple as attainable for the largest, most advanced enterprises on the planet to undertake it inside minutes.”
Vega’s strategy appears to be working. The 100-person startup has already signed multimillion-dollar contracts with banks, healthcare corporations, and Fortune 500 corporations, together with cloud-heavy corporations like Instacart.
“The one motive they might do this with a two-year-old startup is as a result of the issue is so painful and different options in the marketplace require an unrealistic expectation that the enterprise change the way in which they function or do two years of information migrations,” Sandler stated. “Vega allows them to only plug and play and obtain rapid detection response worth.”
