Mindgard raises USD $30 million to boost AI security

Mindgard has raised USD $30 million in a Series A funding round led by Album VC, with participation from Karma Ventures and existing investors .406 Ventures, Atlantic Bridge, IQ Capital, and Lakestar.

The AI security company will use the funding to expand its product, engineering, sales, and marketing teams as customer demand grows. Headquartered in Boston and London, Mindgard was spun out of AI security research at Lancaster University in the UK.

Mindgard focuses on testing and protecting AI systems against attacks. Its work has led to the public disclosure of more than 150 high-impact security and safety vulnerabilities in widely used AI products, including systems from OpenAI, Google, and Cursor.

Examples include a zero-day code execution vulnerability in Cursor IDE, a trusted workspace flaw in Google Antigravity, and image-generation guardrail failures in ChatGPT. Those findings feed into the company's knowledge base for its AI security platform.

The funding comes as businesses push AI tools deeper into day-to-day operations and face greater scrutiny over the risks tied to those systems. Mindgard has seen faster deployment among Fortune 2000 companies and AI-focused businesses in sectors including financial services, pharmaceuticals, gaming, digital services, semiconductors, and healthcare.

Research roots

Mindgard traces its origins to more than a decade of AI security work at Lancaster University. According to the company, that academic base supports what it describes as the world's largest AI security lab, which it uses to study attacks affecting AI models, agents, and applications.

Its platform is designed to identify so-called shadow AI, carry out AI red teaming, and provide run-time protection. Mindgard argues that AI systems create a distinct attack surface that differs from traditional software security.

Chief Executive Officer James Brear outlined that view in remarks accompanying the funding announcement.

"AI is creating an entirely new attack surface and organisations need a fundamentally different approach to securing it," said James Brear, Chief Executive Officer, Mindgard.

"We don't just automate attacks. We operationalize expertise, turning the knowledge of leading AI security researchers and offensive security practitioners into the capabilities every enterprise needs to secure their AI. This investment will expand our global reach and help make attacker-driven AI security a core part of how organizations implement and manage AI," Brear said.

Investor view

Investors backing the round said Mindgard has gained traction as corporate customers look for security tools tailored to AI use in production environments.

"Organisations are moving AI into critical operations without security infrastructure designed for how these systems operate in practice," said Ty Boswell, Partner, Album VC.

"Mindgard has translated deep research and elite offensive-security expertise into a continuously evolving capability that enables enterprises to stay ahead of emerging AI threats. We believe this team can define the AI security category," Boswell said.

Karma Ventures also pointed to adoption among large companies as a factor in its decision to invest.

"AI security is an emerging category and Mindgard stands out as one of the names to watch," said Kristjan Laanemaa, Founding Partner, Karma Ventures.

"Its technology is built on world-class offensive security research, combining automated reconnaissance with smart penetration testing. Crucially, it's already proven in production - some of the most demanding F2000 enterprises rely on it to safeguard their AI systems. That combination of a defensible research moat and proven enterprise pull is rare. We're proud to support James, Peter, and the team in defining this category," Laanemaa said.

The financing places Mindgard among a growing group of specialist companies building businesses around AI-specific cyber risks as customers move beyond experimentation and embed models and agents in core workflows. Organisations are using its tools to discover, assess, and defend AI systems across models, agents, and applications.