Cloud, Data and AI Security

1. Security architecture and technology selection

   The security architecture for your environment and the technologies that fit it, assessed and selected before anything is deployed.

2. Endpoint, cloud and network protection

   Endpoint protection, EDR and XDR, cloud and workload security, and network security put in place.

3. Data security and loss prevention

   Controls around sensitive information throughout its lifecycle, including data loss prevention.

4. Application, API and AI security

   Security for the applications and APIs you build and run, and controls that protect AI applications, agents, models and their data access.

5. Security operations for cloud and endpoints

   Running and tuning the security platforms after deployment: cloud and endpoint operations, platform management and optimization.

1. Our cloud and hybrid infrastructure grew faster than the security around it.

2. We hold sensitive data and cannot say with confidence how it is protected throughout its lifecycle.

3. AI applications and agents are moving into production and nobody owns their security.

4. We own security tools that are not fully deployed or tuned.

1. Advise

   Understand risk. Design the right security approach.

   • Security Architecture Advisory
   • Security Technology Assessment & Selection
   • Data & AI Security Assessment

2. Build

   Put the right security capabilities in place.

   • Endpoint Protection, EDR & XDR
   • Cloud & Workload Security
   • Network Security
   • Data Security & Data Loss Prevention
   • Application & API Security
   • AI Security Controls & AI Workload Protection

3. Manage

   Keep the security environment effective as threats and requirements evolve.

   • Cloud & Endpoint Security Operations
   • Security Platform Management & Optimization

See the full Cybersecurity engagement model