Analysis
Empirical Security raised a $25 million Series A led by Brightmind Partners, announced July 20, bringing the Chicago-based cybersecurity startup's total funding to $37 million. The company builds foundational and predictive models that forecast which vulnerabilities are actually likely to be exploited in the wild, moving past static CVSS scoring toward AI-driven prioritization for security teams drowning in unpatched-vulnerability backlogs.
It competes conceptually with established exposure-management players like Tenable and Rapid7 as well as newer entrants such as Nucleus Security, but leans harder on predictive modeling rather than aggregation and dashboarding. Existing seed investors Costanoa Ventures and Hyde Park Angels returned for the round, a vote of continuity in a Chicago-based security startup, a geography that rarely produces headline security rounds against Bay Area-dominated competitors.
Coming the same day as Neo's $100 million stealth launch into agent security, it's a second data point for a theme gaining real momentum heading into H2 2026: AI predicting and securing AI-era risk pulling investor attention away from generic AI-powered security tooling.
