Who founded Prevalent AI?

Prevalent AI was founded in 2017 by Paul Stokes, now its CEO, and Arun Raj, now its COO. The founding group also drew on senior British intelligence and cybersecurity experience, including former GCHQ director Sir Iain Lobban and Andrew France, a former GCHQ cyber-defence leader and Darktrace co-founder.

That background helps explain the company’s initial focus. Intelligence and cybersecurity work depend on assembling an accurate picture from incomplete, distributed information—then using it to identify relationships, gaps, and risks.

What does Prevalent AI’s platform do?

Prevalent describes its technology as an AI-powered data fabric and a sovereign knowledge graph. In practical terms, the system connects information from enterprise systems and builds a unified model of the organization around it.

The graph can represent relationships among:

• assets and systems;
• identities and access;
• security controls;
• data and business processes; and
• operational or control gaps.

Because the graph is designed to stay current, security teams can query it to understand what exists across an estate, how components relate, and which assets or controls may not be adequately monitored.

“Sovereign” refers to the customer-controlled nature of the data foundation: the company says customers determine where the underlying data physically resides rather than placing it in a shared cloud environment.

The intended users extend beyond security specialists. Prevalent positions the same connected context as a foundation for business users and AI agents that need reliable information about an organization before they can act safely or consistently.

Why did Prevalent start with cybersecurity?

Cybersecurity was the most immediate proving ground for the platform because fragmented information can cause direct operational harm. Security teams often need to make consequential decisions across large estates of systems, identities, controls, and data sources, even when those sources do not agree or do not provide a complete picture.

CEO Paul Stokes described security as the area “where fragmented data does the most damage.”

Starting in that high-stakes environment gave Prevalent a focused use case for solving the broader enterprise-context problem. The company now argues that the same need applies wherever people or automated systems must make decisions using data spread across multiple parts of an organization.

How is Prevalent expanding beyond cybersecurity?

The company’s next target is broader enterprise risk, rather than cybersecurity alone. Reported areas of potential expansion include compliance, financial crime, and operational risk.

The underlying product concept remains the same: connect disparate information, preserve the relationships between records, and provide a current organizational context that can be queried by humans or AI systems. The difference is the business question being answered—whether it concerns a security exposure, a compliance obligation, a financial-crime risk, or an operational dependency.

The available announcements describe this as an extension of technology developed for cybersecurity and enterprise risk, not as a claim that every planned application is already fully launched.

What will the $22 million investment fund?

IGP’s investment is expected to support four main priorities:

1. Global go-to-market expansion: Prevalent plans to build out sales, marketing, customer success, and partnership capabilities.
2. U.S. growth: The company intends to accelerate its expansion in the United States while strengthening its presence in existing markets.
3. Leadership development: The funding will help deepen the leadership team as the business scales.
4. Product and market expansion: Capital will support continued development of the data-fabric and knowledge-graph platform and its extension into broader enterprise-risk and AI use cases.

The raise is notable because it is described as Prevalent AI’s first primary capital in its nine-year history. Company and industry reports say the business previously grew through customer demand and profitability rather than institutional funding.

The bigger proposition

Prevalent AI is not presenting the knowledge graph merely as another cybersecurity data store. Its broader proposition is that enterprise AI needs a dependable layer of organizational context before agents can operate reliably.

The $22 million investment gives the company the resources to test that proposition at a much larger scale: first by expanding the commercial organization and U.S. footprint, then by applying a cybersecurity-tested data foundation to a wider range of enterprise-risk decisions. Whether that expansion succeeds will depend on how effectively Prevalent can keep complex customer data connected, current, and usable across those new domains.

Who founded Prevalent AI?

Prevalent AI was founded in 2017 by Paul Stokes, now its CEO, and Arun Raj, now its COO. The founding group also drew on senior British intelligence and cybersecurity experience, including former GCHQ director Sir Iain Lobban and Andrew France, a former GCHQ cyber-defence leader and Darktrace co-founder.

That background helps explain the company’s initial focus. Intelligence and cybersecurity work depend on assembling an accurate picture from incomplete, distributed information—then using it to identify relationships, gaps, and risks.

What does Prevalent AI’s platform do?

Prevalent describes its technology as an AI-powered data fabric and a sovereign knowledge graph. In practical terms, the system connects information from enterprise systems and builds a unified model of the organization around it.

The graph can represent relationships among:

• assets and systems;
• identities and access;
• security controls;
• data and business processes; and
• operational or control gaps.

Because the graph is designed to stay current, security teams can query it to understand what exists across an estate, how components relate, and which assets or controls may not be adequately monitored.

“Sovereign” refers to the customer-controlled nature of the data foundation: the company says customers determine where the underlying data physically resides rather than placing it in a shared cloud environment.

The intended users extend beyond security specialists. Prevalent positions the same connected context as a foundation for business users and AI agents that need reliable information about an organization before they can act safely or consistently.

Why did Prevalent start with cybersecurity?

Cybersecurity was the most immediate proving ground for the platform because fragmented information can cause direct operational harm. Security teams often need to make consequential decisions across large estates of systems, identities, controls, and data sources, even when those sources do not agree or do not provide a complete picture.

CEO Paul Stokes described security as the area “where fragmented data does the most damage.”

Starting in that high-stakes environment gave Prevalent a focused use case for solving the broader enterprise-context problem. The company now argues that the same need applies wherever people or automated systems must make decisions using data spread across multiple parts of an organization.

How is Prevalent expanding beyond cybersecurity?

The company’s next target is broader enterprise risk, rather than cybersecurity alone. Reported areas of potential expansion include compliance, financial crime, and operational risk.

The underlying product concept remains the same: connect disparate information, preserve the relationships between records, and provide a current organizational context that can be queried by humans or AI systems. The difference is the business question being answered—whether it concerns a security exposure, a compliance obligation, a financial-crime risk, or an operational dependency.

The available announcements describe this as an extension of technology developed for cybersecurity and enterprise risk, not as a claim that every planned application is already fully launched.

What will the $22 million investment fund?

IGP’s investment is expected to support four main priorities:

1. Global go-to-market expansion: Prevalent plans to build out sales, marketing, customer success, and partnership capabilities.
2. U.S. growth: The company intends to accelerate its expansion in the United States while strengthening its presence in existing markets.
3. Leadership development: The funding will help deepen the leadership team as the business scales.
4. Product and market expansion: Capital will support continued development of the data-fabric and knowledge-graph platform and its extension into broader enterprise-risk and AI use cases.

The raise is notable because it is described as Prevalent AI’s first primary capital in its nine-year history. Company and industry reports say the business previously grew through customer demand and profitability rather than institutional funding.

The bigger proposition

Prevalent AI is not presenting the knowledge graph merely as another cybersecurity data store. Its broader proposition is that enterprise AI needs a dependable layer of organizational context before agents can operate reliably.

The $22 million investment gives the company the resources to test that proposition at a much larger scale: first by expanding the commercial organization and U.S. footprint, then by applying a cybersecurity-tested data foundation to a wider range of enterprise-risk decisions. Whether that expansion succeeds will depend on how effectively Prevalent can keep complex customer data connected, current, and usable across those new domains.