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AI Enablement & Governance
Practical AI adoption without feeding your data to a model you don't control
The Challenge
Leadership wants “AI everywhere” yesterday. In reality most shops have shadow AI, unclear data rules, and no idea which prompts or files are leaving the building. That is a compliance incident waiting to happen.
Our Approach
We start with what you actually run (Microsoft 365, Google Workspace, AWS, Azure) and what data must stay put. Then we define allowed tools, identity and logging, retrieval and RAG patterns where they make sense, and written policies your team can follow. Pilot first, scale with controls.
Who It's For
- Teams rolling out Microsoft Copilot or Google Duet and need tenant and data policies
- Companies building internal assistants or RAG over documents under HIPAA or SOC 2
- Leaders who want a sane roadmap instead of a dozen one off experiments
What We Deliver
- Use case prioritization and vendor shortlists aligned to your risk profile
- Architecture for secure API access, keys, and network boundaries
- Data classification guidance: what never goes to a public model
- Governance pack: acceptable use, review checkpoints, and audit friendly logging
- Hands on help prototyping assistants or workflows on Bedrock, Azure OpenAI, or similar
Key Outcomes
- A clear answer to “what are we allowed to use and how”
- Fewer rogue subscriptions and copied into ChatGPT incidents
- Faster time to a controlled pilot with measurable success criteria
- Documentation that satisfies security reviewers and auditors
Features
- Copilot and enterprise AI readiness assessments
- Private or VPC aligned model deployment patterns
- Integration with SSO, DLP, and existing monitoring
- Prompt and workflow patterns that reduce leakage risk
- Ongoing advisory as models and vendor terms change
Ready to secure your cloud environment?
Book a free infrastructure assessment and get a custom roadmap for cloud operations that stay inside your compliance boundaries.