Empirical Security Secures $25 Million in Series A Funding

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Empirical, a cybersecurity startup, secures $25 million in Series A financing, bringing total funding to $37 million.

Company Overview

Empirical, established in 2024, has secured $25 million in Series A financing, increasing its total funding to $37 million. The round was led by Brightmind Partners, with additional support from Costanoa Ventures and Hyde Park Angels, among others. The company plans to use the funds to accelerate development of its core offerings targeting emerging threats in the agentic AI landscape.

Investors and Funding Details

The latest round was spearheaded by Brightmind Partners, with additional backing from Costanoa Ventures and Hyde Park Angels. The funding follows recent announcements from other cybersecurity firms, including Neo’s $100 million raise for AI security solutions and Risk Ledger’s $32 million Series B round.

Core Offerings and Technology

Empirical’s primary tools include Foundation, a global cybersecurity model tracking over 18,000 known exploited vulnerabilities for threat forecasting, and Radiant, a predictive analytics engine tailored to individual organizational environments. These solutions help enterprises detect and prioritize risks by analyzing contextual data and reducing noise from irrelevant threats.

The platform leverages AI-driven insights to provide actionable intelligence, enabling security teams in sectors such as technology, healthcare, and finance to assess and mitigate cyber risks effectively. The company’s predictive models enhance decision-making through advanced forecasting, evidence-based risk evaluation, and targeted remediation strategies.

Leadership and Expertise

Empirical’s leadership team includes CEO Ed Bellis, who previously co-founded Kenna Security, CTO Michael Roytman, a former Chief Data Scientist at Kenna, and Chief Data Scientist Jay Jacobs, who co-developed the Exploit Prediction Scoring System (EPSS). Bellis emphasized the need for innovative approaches to counter AI-powered threats, stating that traditional methods are insufficient for addressing the scale and complexity of modern exploit landscapes.

“Traditional methods are insufficient for addressing the scale and complexity of modern exploit landscapes,” Bellis stated.

The startup’s founders highlighted that their work builds on prior advancements in risk-based vulnerability management, aiming to deliver predictive capabilities that were previously unattainable. They noted that the integration of AI into cybersecurity frameworks requires new methodologies to balance threat detection with operational efficiency.

Industry Context and Future Outlook

The funding comes amid growing concerns over AI-driven attack vectors and the need for adaptive defense mechanisms. Empirical’s focus on agentic AI aligns with broader industry trends, as organizations seek tools to manage the increasing volume of potential exploits. By combining machine learning with environment-specific data, Empirical aims to provide a scalable solution for enterprises navigating evolving threat landscapes.

Technical details about the company’s products and strategies remain confidential, but the funding round underscores investor confidence in its approach to predictive cybersecurity. The startup’s ability to integrate AI with traditional security practices positions it as a contender in the rapidly evolving field of enterprise threat management.