Funding for a growing AI-security challenge
Mindgard, which is headquartered in London and Boston, has closed a $30m Series A led by Album VC. Karma Ventures and existing investors .406 Ventures, Atlantic Bridge, IQ Capital and Lakestar also participated. The company says the funding will support expansion across product, engineering, sales and marketing as more organisations move artificial-intelligence systems into operational use.
The investment comes as businesses face a security problem that is different from protecting conventional software alone. AI models, agents and applications can behave in unexpected ways, change as they are updated and connect to sensitive workflows. Mindgard’s proposition is to help security teams discover those systems, test them for weaknesses and protect them at runtime. The company describes this work through three linked capabilities: shadow-AI discovery, AI red teaming and runtime AI protection.
Research translated into enterprise tooling
Mindgard says its technology has helped publicly disclose more than 150 high-impact security and safety vulnerabilities across AI products. The examples cited by the company include a zero-day code-execution vulnerability in Cursor IDE, a trusted-workspace flaw in Google Antigravity and failures in image-generation guardrails in ChatGPT. These examples are presented as evidence of the range of weaknesses that can emerge when AI systems are used in development, productivity and creative applications.
The company’s platform grew out of more than a decade of AI-security research associated with Lancaster University. That research base is being combined with offensive-security expertise and software intended for repeatable use by enterprise teams. The practical benefit is a move away from one-off testing towards a process that can be revisited as models, prompts, tools and connected applications change.
Why the London connection matters
Mindgard’s London headquarters place the business within a capital-city technology ecosystem that includes financial services, healthcare, digital services and other organisations adopting AI. The company says its deployments include Fortune 2000 businesses and other AI innovators across sectors including pharmaceuticals, gaming, semiconductors and healthcare. Those customer descriptions come from the company and do not, by themselves, establish the performance of every deployment, but they show the type of market Mindgard is seeking to serve.
For London businesses, the immediate relevance is operational rather than theoretical. An AI system may be introduced by a team outside the central security function, creating what is often called shadow AI. Testing and monitoring can help an organisation identify where such systems exist, assess how they respond to attacks and decide what protection is required before they are embedded more deeply in business processes.
What the new capital is intended to deliver
Mindgard has not published a detailed allocation of the Series A. It has said, however, that the money will fund expansion in product, engineering, sales and marketing. That combination suggests a focus on strengthening the platform while making it available to more customers. The company’s central argument is that AI security needs to be continuous: discovery, offensive testing and protection must keep pace with the systems they are designed to secure.
The funding therefore marks a scale-up moment for a London-connected company whose identity remains closely tied to research. Its progress will be measured by how effectively it turns disclosed vulnerabilities, security expertise and customer demand into dependable tools for organisations putting AI into production.
London readers can also read our explainer on the challenge of AI finding vulnerabilities faster than enterprises can patch them.
