Prevalent AI appoints new CTO after USD $22m raise

Prevalent AI has appointed Nitin Maini as Chief Technology Officer following a USD $22 million growth investment.

Maini joins from Qualys, where he was Senior Vice President of Engineering and led an engineering organisation of more than 1,000 people in India. He will lead Prevalent AI's technology strategy as the company expands the use of its AI-powered data fabric and knowledge graph beyond cybersecurity.

The London-based company, founded by former GCHQ staff, has spent much of its nine-year history building products for complex cybersecurity environments. It is now expanding into areas including financial crime analysis, operational intelligence, and governance, risk and compliance.

The appointment comes shortly after Prevalent AI raised its first primary capital. The USD $22 million investment from Integrity Growth Partners will support product development and international expansion.

Its customers include global banks, telecommunications groups, and critical national infrastructure operators. That customer base places the business in sectors where large volumes of fragmented internal data can create operational and regulatory problems.

Maini brings more than two decades of experience in cybersecurity and enterprise software. Before joining Qualys, he spent almost six years as Chief Technology Officer at Sapience Analytics and held senior engineering roles at Vuclip and BMC Software.

Broader push

Prevalent AI's platform connects data across enterprise systems and builds a continuously updated view of assets, identities, controls, and the relationships between them. The company argues that this organisational context becomes more important as businesses try to use AI systems in live internal environments rather than in limited pilot projects.

That view reflects a wider debate in the technology industry over whether AI tools can operate reliably when company data is incomplete, inconsistent, or spread across separate systems. Vendors across the sector are trying to address the problem by linking data sources and adding more structured context for automation and decision-making.

Paul Stokes, Chief Executive Officer and Co-Founder of Prevalent AI, outlined the rationale for the hire.

"Prevalent AI has spent nearly a decade building a connected data foundation for complex cybersecurity environments, and Nitin joins us at a point when that foundation has a much broader role to play. His experience scaling global engineering organisations and leading AI transformation will be important as we extend the Knowledge Graph into new enterprise use cases, such as financial crime analysis and operational intelligence, while continuing to serve our security customers," said Stokes.

Maini said he was drawn by the company's technology base and by the challenge of fragmented data in large organisations.

"Across my career, I have seen what happens when complex platforms are built on fragmented data. AI is making that weakness much harder to ignore. What drew me to Prevalent was the maturity and extensibility of the Knowledge Graph. It gives enterprises a connected foundation that can support security today and broader AI use cases tomorrow as those systems move into production," said Maini.

Technology focus

The hire suggests Prevalent AI is placing greater emphasis on product development as it looks to expand beyond its original cybersecurity focus. Bringing in an executive who has run a large engineering organisation also points to an effort to scale internal development as the company targets more industries and use cases.

For businesses in regulated sectors, the question is not only whether AI models can produce useful answers, but whether they can act with enough understanding of internal systems, permissions, and relationships. This is particularly relevant in financial services, telecoms, and infrastructure, where errors can have security, compliance, or operational consequences.

Maini linked that challenge to the company's next stage of development.

"Every enterprise I speak to wants to move AI into production, but confidence drops quickly once agents are expected to act inside live systems. They need current context about the organisation they operate in and how its systems are connected. My ambition is for Prevalent AI to become the trusted data and context layer for enterprise AI, with the Knowledge Graph extending from cybersecurity into areas such as governance, risk and compliance," said Maini.