AI your security team can approve.
Atidan designs the boundaries, identity controls and monitoring that let AI connect to your systems without exposing what it shouldn’t — so projects clear review and reach production.
Connecting AI to your systems changes your risk surface
An AI assistant that reads SharePoint, queries CRM or acts through an API inherits whatever access you give it. Oversharing in Microsoft 365 becomes an AI problem the day an assistant can search it. Employees paste sensitive data into unapproved tools. Agents that take actions need the same least-privilege discipline as a new employee, and an audit trail to prove it.
Most AI projects treat these as a checklist at the end. We start with them.
Secure by design: four layers, set before any code
Boundaries
We define what data the AI can see, what it can do, and what it must never do, and write those limits into the architecture.
Identity & access
Single sign-on, role-based permissions and least-privilege service accounts for every agent and integration.
Data protection
Encryption, governed and curated data sources instead of open-ended access, and no bulk export unless the use case needs it.
Monitoring & audit
Logging of AI activity, alerting through Microsoft Sentinel, and periodic reviews of accuracy, access and drift.
How Kerry Group’s AI hub cleared approval
Before we wrote a line of code for Kerry’s People Intelligence Hub, Atidan and Kerry agreed on the limits, and the platform enforces them.
Those constraints are what made the platform straightforward to approve and roll out across the organization. The result: more than 75% less time spent on manual competitor research.
time, in production
Scope drawn deliberately
- Public activity only — no private profiles or personal contact details.
- Claude reads a governed, pre-ingested corpus; it never queries people live.
- No bulk data export for end users.
- No sentiment scoring or predictive profiling of individuals.
- Single sign-on, with administrators and viewers on separate roles.
AI security services
| Service | What you get |
|---|---|
| AI security readiness assessment | A review of identity, data exposure, AI usage and compliance obligations, with a prioritized roadmap, in 3–6 weeks. |
| Secure architecture for AI apps & agents | Boundaries, permissions, data flows and threat review designed into every build we deliver. |
| Data governance for AI | SharePoint and Microsoft 365 permission cleanup and data governance, so assistants only surface what users are allowed to see. |
| Identity protection for AI | SSO, role design and least-privilege access for users, agents and service accounts. |
| Monitoring & response | AI activity logging and alerting with Microsoft Sentinel, run by our managed cloud team. |
| Compliance mapping | AI controls mapped to GDPR and HIPAA, and for life sciences, GxP, 21 CFR Part 11 and EU Annex 11. |
| AI governance & model monitoring | Ongoing checks on accuracy, fairness and access, plus periodic health audits. |
| Shadow AI discovery | Visibility into which AI tools employees use and where sensitive data goes. |
| AI red teaming & prompt-injection testing | Adversarial testing of AI apps and agents before launch. |
Security that uses what you already own
We build AI security on the Microsoft tools most enterprises already license. AI models deployed through Microsoft Foundry use the Azure authentication, billing and governance you already have.
- Microsoft Sentinel
- Identity protection
- Azure encryption
- Intune
- Microsoft 365 data governance
- Microsoft Foundry
Get your AI project through security review.
Bring us the use case your security team hasn’t approved yet. We’ll show you the boundaries that would get it there.