As enterprises move AI models and agents into production, security teams are confronting risks that conventional application security tools were not designed to assess. Mindgard is building its business around that gap, raising $30 million in Series A funding to expand a platform that applies offensive security research and attacker behavior to identifying weaknesses in enterprise AI systems.
The Boston- and London-headquartered AI security company said the financing was led by Album VC, with participation from Karma Ventures and existing investors .406 Ventures, Atlantic Bridge, IQ Capital and Lakestar. Mindgard plans to use the capital to expand its product and engineering operations as well as sales and marketing amid growing customer demand.
Mindgard emerged from more than a decade of AI security research at Lancaster University in the U.K., where its technology continues to be supported by an AI security research lab. The company combines that research with offensive security techniques to test models, agents and AI-powered applications for vulnerabilities that can emerge from the way those systems behave and interact with users, data and other software.
That approach reflects a growing operational challenge for companies deploying AI. Models and agents can introduce attack paths that differ from those found in conventional applications, requiring security teams to evaluate not only software code and infrastructure but also model behavior and the ways AI systems respond to adversarial inputs.
Mindgard said its platform has been used to discover and publicly disclose more than 150 security and safety vulnerabilities affecting widely used AI products. Those findings include a zero-day code execution vulnerability in Cursor IDE, a trusted workspace flaw in Google Antigravity and image-generation guardrail failures in ChatGPT.
The company uses intelligence gathered through that vulnerability research to update a proprietary knowledge base supporting its AI Security Platform. The goal is to translate findings from security researchers and offensive practitioners into testing and defensive capabilities that enterprise security teams can apply across their own AI deployments.
“AI is creating an entirely new attack surface and organizations need a fundamentally different approach to securing it,” said Mindgard CEO James Brear. “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.”
Brear said the funding will support Mindgard’s global expansion and its effort to make attacker-driven security testing a standard component of enterprise AI deployment and management.
Mindgard’s platform covers Shadow AI discovery, AI red teaming and runtime protection, allowing organizations to identify AI systems in use, assess them for weaknesses and monitor deployed systems for potential risks. The technology is designed to work across models, agents and applications rather than focusing on a single component of the AI stack.
The Series A follows increased deployment of Mindgard among Fortune 2000 companies and AI developers, according to the company. Customers span financial services, pharmaceuticals, gaming, digital services, semiconductors and healthcare. Mindgard did not disclose specific customer numbers or revenue figures.
The adoption reflects an increasingly practical security issue as businesses move AI beyond experimentation and into systems connected with internal data, software tools and critical workflows. Security teams must determine how models behave under attack, whether agents can be manipulated into taking unintended actions and where vulnerabilities could emerge as AI components interact with traditional enterprise infrastructure.
“Organizations are moving AI into critical operations without security infrastructure designed for how these systems operate in practice,” said Ty Boswell, partner at Album VC. He said Mindgard’s combination of research and offensive security expertise gives enterprises a way to respond as AI threats evolve.
Kristjan Laanemaa, founding partner at Karma Ventures, pointed to the company’s combination of automated reconnaissance and penetration testing, as well as its adoption among large enterprises, as factors behind the investment.
The new capital will give Mindgard additional resources to expand as AI security develops into a more established component of enterprise cybersecurity programs. Rather than treating model security as a standalone technical problem, the company is targeting the broader lifecycle of AI deployment, from discovering systems operating inside an organization to testing them against attacks and protecting them once they are running in production.
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