Protect the information behind intelligence.
We extend SOC visibility and practical protection across enterprise data, cloud services, AI applications, model behaviour, and critical integrations.
AI expands the security boundary.
New data flows, retrieval sources, prompts, model providers, tools, agents, and outputs create risks that do not fit neatly inside one control domain. Security must address the complete system and the decisions it is allowed to make.
What this service covers
AI threat & control modelling
Assess manipulation, data exposure, excessive agency, insecure tools, model supply chain, and misuse scenarios.
Cloud security design
Define network, identity, workload, secret, logging, configuration, and platform controls around the service.
Data protection
Classify sensitive information and design access, encryption, retention, masking, monitoring, and lifecycle controls.
Secure AI engineering
Embed validation, grounded behaviour, tool boundaries, evaluation, monitoring, and human escalation into delivery.
Common applications
Enterprise copilots
Protect private knowledge, user permissions, retrieval paths, model interactions, and generated responses.
Agentic workflows
Limit tools, transactions, data access, memory, and autonomous actions within explicit operating boundaries.
Cloud data platforms
Secure the information foundations that support analytics, automation, and AI workloads.
Third-party AI adoption
Assess provider, integration, privacy, retention, access, and operating risks before deployment.
What this service produces.
- AI and cloud threat model
- Data-flow and trust-boundary map
- Security architecture and control plan
- Evaluation and monitoring requirements
- Implementation guidance and assurance findings
Five stages. Evidence at every one.
The same disciplined path runs through every engagement, scaled to the size of the problem. Each stage produces something you can review before the next begins.
Discover
Understand the business priority, users, current environment, constraints, risks, and definition of success.
Define
Prioritise the opportunity and establish a focused scope, target outcome, and practical route forward.
Design
Shape the architecture, experience, controls, delivery plan, and governance needed to support the solution.
Deliver
Build, integrate, validate, and introduce the capability with clear stakeholder visibility.
Improve
Observe real use, measure performance, resolve friction, and evolve as needs change.
Trust is part of the engagement.
Security, privacy and accountability are established at the start, not retrofitted before a review.
Controls from the first decision
Architecture, identity and controls built in from the first decision.
Recommendations you can check
Recommendations backed by data, testing and real operating experience.
Oversight in the operating model
Privacy, access and oversight designed into the operating model.
Come with a problem. Leave with a decision.
One working session. You leave knowing what to build first, what it needs, who owns it, and how you will know it worked.