Prevalent AI is a security data and exposure management company founded by alumni of GCHQ. It turns the fragmented data held in an organisation’s many security and IT tools into a sovereign, continuously updated knowledge graph, and uses that graph to show which exposures matter and to give AI the context it needs to act safely.
The company works with organisations in high-risk, highly regulated environments, and every deployment runs inside the customer’s own environment. The problem it addresses is trust in data: neither analysts nor AI agents can make good decisions when every tool holds a different, partial record of the same estate.
At A Glance
| Vendor | Prevalent AI |
|---|---|
| Category | Security data fabric and exposure management |
| Identities covered | Human and non-human identities |
| Deployment | Sovereign deployment running within the customer environment |
| Agentic AI | Enterprise context for human teams and AI agents |
| Leadership | Paul Stokes (Co-Founder and CEO) |
| Market classification | Security Operations |
What Prevalent AI Does
Most security teams have more tools than they have a clear picture. Asset lists, vulnerability scanners, identity systems and ticketing queues each hold part of the story, often with conflicting records. Prevalent AI pulls data from hundreds of these sources, resolves the inconsistencies automatically and keeps one graph of what exists in the organisation, who owns it, which controls apply and how it has changed over time. Every later decision, by a person or an AI agent, then works from that graph rather than from each tool’s partial view. The principle behind the design is that enterprise AI should operate on infrastructure the customer owns.
Products
Security Data Fabric
The Security Data Fabric is the operational foundation of the platform. For teams that cannot trust their own inventory, it connects data from cloud, identity, endpoint, vulnerability, ticketing, operational and security systems, cleans and reconciles the records, and builds a knowledge graph of assets, identities, vulnerabilities, controls and operational context.
Exposure Management
Exposure Management helps vulnerability and risk teams cut through duplicate findings and focus on the exposures that create real operational risk. It continuously discovers, classifies and reconciles assets across devices, cloud, identity, applications and infrastructure, correlates findings across tools to remove duplicates and conflicting data, and measures exposure per asset and across the organisation. Remediation guidance is ranked by exploitability, operational risk and business impact.
DataBridge And DataForge
DataBridge is the integration layer, used to add new cloud, SaaS, operational or on-premises systems quickly. DataForge produces realistic, synchronised synthetic datasets for training AI models.
Further Modules
| Prevalent AI CCM | Continuous controls monitoring at scale. |
|---|---|
| Prevalent AI Studio | Integrations and a unified security knowledge graph. |
| Navigator Mobile | Generative AI security insights on mobile. |
AI Solutions
Agents that act on incomplete or conflicting data make poor decisions. Prevalent AI’s AI Solutions support both human decision-making and agentic workflows by letting customers deploy AI on top of a continuously updated enterprise memory, the knowledge graph. Because the platform runs in the customer’s environment, this AI is not tied to shared infrastructure or a single model provider.
How It Works
The Security Data Fabric has four core components that data passes through in order.
| Component | What it does |
|---|---|
| Connectors | Bring in data from the customer’s existing systems. |
| Pipelines | Move and clean incoming data before it reaches the graph. |
| Entity resolution | Reconciles records about the same asset or identity that arrive from different sources. |
| Knowledge graph | Holds the reconciled, current view of assets, identities, vulnerabilities, controls and context, which Exposure Management and AI Solutions query. |
Each deployment is sovereign by design and runs within the customer’s environment.
Identities And Systems Covered
| Human and non-human identities | Identity data connected across HR systems, directories, IAM platforms and cloud environments. |
|---|---|
| Privileged access | Identity and privileged access exposure. |
| Cloud | Multi-cloud environments, checked for drift, misconfigurations and excessive permissions. |
| Assets | Devices, applications and infrastructure, reconciled in the knowledge graph. |
Company Background
| Founders | Paul Stokes (Co-Founder and CEO) and Arun Raj (Co-Founder and COO), both among the GCHQ alumni who started the company. |
|---|---|
| Leadership | Nitin Maini (CTO) and JD Sherry (Chief Revenue Officer). |
| Funding | Growth investment, announced to meet demand for trusted enterprise context for AI. |
Note: This overview is compiled from Prevalent AI’s publicly available information as of 3 November 2026. It is provided for information only. NHI Mgmt Group does not endorse any vendor, and nothing on this page represents the opinions of NHI Mgmt Group.