Secure AI implementation
Ship AI fast, without shipping risk.
Copilot can surface any file a user can already open, and an unvetted AI tool can send your data somewhere you never agreed to. We sort out data access, controls and policy before launch, so you aren't cleaning up afterward.
AI platforms we secure
Enterprise copilots
Microsoft Copilot, GitHub Copilot and similar assistants, configured so they only see what each user is allowed to see.
ChatGPT Enterprise
Secure deployment of OpenAI's enterprise offerings with data protection measures.
Custom LLM deployment
Self-hosted or fine-tuned language models with appropriate security architecture.
AI platform security
AWS Bedrock, Azure OpenAI, and Google Vertex AI platform implementations.
RAG systems
Retrieval-augmented generation connected to your knowledge bases without exposing documents to the wrong users.
AI-powered applications
Your own applications built on AI APIs, with secure integration patterns.
Where we help
Enterprise AI deployment
Rolling out Microsoft Copilot, ChatGPT Enterprise, Claude and similar tools with permissions and data controls set first.
Custom LLM security
Architecture and security design for custom large language model deployments and fine-tuned models.
AI tool vetting
A security review of an AI tool or vendor before you sign, covering what it does with your data and what it needs from you.
Secure integration patterns
Architectures for connecting AI to your existing applications and workflows without widening access.
Data classification for AI
Decide which data may be used for AI training and inference, and put controls in place to enforce it.
Employee AI policies
Develop acceptable use policies and training for safe employee use of AI tools.
How a rollout runs
From your use cases and risk assessment through deployment and ongoing monitoring.
Requirements gathering
Understand your AI use cases, business objectives, and security requirements.
Risk assessment
Evaluate AI-specific risks including data exposure, compliance, and operational impacts.
Architecture design
Design secure AI implementation architecture with appropriate controls and boundaries.
Security controls
Implement technical and administrative controls for AI data protection and access.
Deployment support
Guide secure deployment with configuration hardening and integration testing.
Operationalization
Establish ongoing monitoring, policy enforcement, and governance processes.
What you get.
Security architecture
Detailed design documents for secure AI integration including data flows and controls.
Implementation guide
Step-by-step deployment instructions with security configuration settings.
Policy framework
AI acceptable use policies and data handling guidelines.
Training materials
Staff training on using AI tools safely day to day.
Planning a Copilot or LLM rollout?
Tell us which tools you're adopting and what data they'll touch. We'll help you plan the controls before anyone gets a login.