Cybersecurity startup Noma Security, which develops a platform for AI and agent security, has raised $100 million in a Series B funding round. The round was led by Evolution Equity Partners, with participation from existing investors Ballistic Ventures and Glilot Capital Partners. The new capital brings Noma’s total funding to $132 million in less than two years.
Noma’s platform enables organizations to confidently adopt AI-based technologies at scale. The company helps cybersecurity teams manage AI-related risks through continuous vulnerability discovery, security profiling, risk prioritization, real-time attack simulations, and defense, all while ensuring compliance with organizational security policies.
Noma was founded in 2023 by CEO Niv Braun and CTO Alon Tron, who met in the IDF’s 8200 intelligence unit. The company came out of stealth in October 2024. While the company does not disclose revenue figures, it reports significant year-over-year growth following adoption by Fortune 500 companies and leading AI players in the financial services, life sciences, retail, and high-tech sectors. The company employs 40 people across its development center in Tel Aviv and offices in the U.S.
Related articles:
According to UBS Research, 53% of surveyed organizations plan to adopt agentic AI by 2026, with 83% adopting AI agents by 2028. The Noma platform identifies millions of AI and AI agent risks while simultaneously prioritizing and mitigating novel threats at scale. For example, one Noma Security customer processes hundreds of millions of AI prompts every month while scanning thousands of model artifacts and AI environments including cloud, code repositories and AI agent development platforms.
“AI agent adoption is exploding within our customer base and CISOs understand that AI innovation must be thoughtfully deployed with full guardrails,” said Niv Braun, Noma Security CEO and Co-Founder. “Noma Security is the only cybersecurity vendor to offer an end-to-end platform purpose-built to identify and mitigate the uniquely advanced risks of agentic AI.”
