Manchester's Cytix Raises $7M to Secure AI-Driven Software Development
The cybersecurity startup will scale its change risk management platform to tackle vulnerabilities introduced by rapid AI code generation.
Manchester-based cybersecurity startup Cytix has secured $7 million in Series A funding to combat the security risks inherent in AI-accelerated software development. The investment arrives as enterprises struggle to maintain security standards while adopting generative AI to speed up their coding pipelines.
The funding round, which totals approximately £5.18 million (€6 million), was led by Northern Gritstone. The round also saw participation from existing investors NPIF II-PXN Equity Finance and Auriga Cyber Ventures. Cytix intends to use the new capital to scale its specialized change risk management platform, which is designed to identify and mitigate security vulnerabilities that emerge during the rapid deployment of software.
The AI Velocity Gap
The surge in AI-driven software development has fundamentally altered the speed of the development lifecycle. While AI tools allow developers to write and deploy code at an unprecedented pace, this velocity often outstrips the capacity of traditional security audits. The result is a growing gap where productivity gains are offset by the introduction of "silent" vulnerabilities—security flaws that are woven into the code by AI and overlooked by legacy scanning tools.
Implications for DevSecOps
This shift creates a critical need for systematic change risk management. As companies increasingly rely on AI to generate production-ready code, the potential for systemic vulnerabilities to enter live environments grows. By providing a dedicated layer to police AI-written code, Cytix aims to establish a new standard for DevSecOps. The goal is to ensure that the speed of AI deployment does not come at the cost of infrastructure integrity or data security.
Future Outlook
With the Series A capital, Cytix is positioned to expand its footprint in the cybersecurity market as more enterprises integrate AI into their core engineering workflows. The industry will be watching to see if specialized change risk management becomes a mandatory component of the AI software stack. While the platform's current focus is on scaling, the broader challenge remains whether automated policing can keep pace with the evolving nature of AI-generated exploits.