Solutions
Who does your AI work for — and what can it touch?
Governance your compliance team and your engineers can both live with
When AI connects to SharePoint, email or your ERP, permissions stop being IT detail and become business risk. We define the rules before the agent goes live.
The problem
Teams connect AI to everything because they can — not because they should. Nobody knows who approved what, and when something goes wrong, there is no owner.
What we address
- Clear identity for every human and every agent
- Rules on what each agent can read, write and execute
- Safe connections to Microsoft 365, SAP and internal APIs
- Human approval before sensitive actions
- Full audit trail — who did what, when and why
- Limits on how far AI can act without supervision
Deliverables
- Identity and access model for AI systems
- Tool and connector permission matrix
- Approval and escalation workflows
- Audit and ownership framework
- Governance operating model
For whom
- — Business leaders deploying AI assistants across departments
- — Compliance teams asking hard questions about AI access
- — IT leaders connecting AI to existing enterprise systems
Focus the review on governance — permissions, connectors and accountability.
Solutions · Radiography
AI Governance
What can AI access — and what can it do?
An agent is only as capable as the systems it can reach. Governance defines identity, data access, tool permissions, approval workflows and accountability — so AI acts within explicit boundaries.
The problem
Connecting AI to SharePoint, SAP, email or internal APIs without a governance model creates invisible risk: over-privileged agents, unaudited actions and no clear owner when something goes wrong.
What we address
- Human and agent identity models (OIDC, workload identity)
- RBAC, ABAC and tool-level permissions with policy engine
- Connectors, MCP servers and enterprise integration patterns
- Memory stores, credential vaults and secret rotation
- Human-in-the-loop, approval queues and escalation paths
- Immutable audit trails, ownership registry and version control
- Autonomy limits, policy enforcement and guardrail hooks
Deliverables
- Identity and access model for AI systems
- Tool and connector permission matrix
- Approval and escalation workflows
- Audit and ownership framework
- Governance operating model
For whom
- / Teams deploying tool-using agents in the enterprise
- / Architects connecting AI to Microsoft 365, SAP or internal APIs
- / Compliance and platform leads defining AI control
Focus the review on governance — permissions, connectors and accountability.