Vega, which uses AI to find security threats in cloud services and data storage, raised a $120M Series B at a $700M valuation, taking its total funding to $185M
Modern enterprises generate enormous amounts of security data, but legacy tools like Splunk still require companies to store …
Context & Ripple Effects
Vega’s new round follows its $65M seed and Series A financing in September 2025, lifting the company from early backing to a substantially larger capital base in a short span.
The company sits in a longer security-analytics lineage: Vectra previously raised successive rounds for AI-based network-threat detection, including a $130M growth round at a $1.2B post-money valuation. Vega’s focus on cloud services and data storage shifts that AI-security thesis toward where enterprise security data is now generated and retained.
First-order effects
- Vega now has $185M in total funding and a $700M valuation, giving it more capacity to build and sell its cloud-security analytics platform.
- The financing validates Vega’s approach of finding threats directly across cloud services and data storage, rather than relying solely on legacy security-data workflows.
Second-order effects
- Security analytics vendors competing for cloud-security budgets will need to show that their detection methods, data handling, and deployment models are differentiated from Vega’s AI-led approach.
- Enterprises evaluating legacy tools such as Splunk gain another well-funded option in the trade-off between storing security data in traditional platforms and analyzing it closer to cloud services.
Third-order effects
- If similarly funded vendors keep targeting cloud-resident security data, threat detection may increasingly be organized around cloud-native data access rather than centralized log-storage estates.
- The pattern could concentrate the market around vendors that can pair AI analysis with broad access to enterprise cloud data, though execution and customer trust will determine whether funding converts into durable share.
The trend: AI-based security analytics is moving from a network-focused category toward cloud-data-centric platforms backed by larger growth rounds.