Raidiness

Why I built Raidiness

“Are we ready for Copilot?” sounds like a simple question. In practice, I need to know what the organization wants to use, which information it can reach, and what the tenant actually tells me.

I'm Ziggy Itjoejaree, the Microsoft 365 engineer behind Cloud Toko. I built Raidiness to bring those questions together. It is a PowerShell tool for collecting read-only Microsoft 365 evidence and assessing it locally against AI readiness checks.

My starting point is practical: show me the findings, show me the evidence, and show me what we still haven't measured. That gives an engineer something useful to investigate and discuss with the organization.

What Raidiness checks

Microsoft Graph provides the core evidence. Depending on the intended rollout, you can add other workloads and a short intake about the organization's plans.

Source	Evidence it can contribute
Microsoft Graph	Users, licenses, groups, sites, usage, identity and governance signals, subject to approved access.
Exchange Online and Purview	Mailbox counts, audit settings, sensitivity labels, DLP policies, retention and label activity.
SharePoint Online	Tenant settings, site inventory and optional permission sampling.
Microsoft Teams	Meeting-policy inventory. This does not establish effective policy assignments for every user.
Power Platform	Environments and connector DLP policies relevant to Copilot Studio governance. This is not a complete agent inventory.
Intake	Intended AI capabilities, organizational decisions and context that tenant configuration cannot answer.

The available evidence depends on permissions, roles, licenses and the modules you select. Not measured means there isn't enough evidence to evaluate a check. It is a gap to investigate, not a confirmed configuration failure or a pass.

For the broader assessment approach, read my AI Readiness Check for Microsoft 365.

From tenant evidence to engineering findings

The current 0.5 development workflow collects the selected sources, evaluates them locally and generates a report. The HTML viewer brings together findings, measurements and collection gaps. Markdown and printable findings support review; JSON preserves the detailed evidence and diagnostics.

I keep the interpretation with the engineer. Raidiness does not automatically approve a deployment, write the customer's business case or decide which risk the organization should accept. A successful run tells you the command finished. You still need to review what it could measure and whether that covers the intended users and scenarios.

Published releases can differ from the development version. My installation and version guide explains which starting command to use.

Local processing, read-only collection

Raidiness reads from the selected Microsoft services and writes its results to your chosen folder. It does not change tenant settings, grant itself permissions, send evidence to me or call an AI model.

Authentication and collection still communicate with Microsoft 365. Reports can contain names, email addresses, tenant IDs, site URLs and configuration details. Choose an approved storage location: a Documents folder might be synchronized by OneDrive or copied by backup software.

An optional LLM export creates local files for separate review and use with your own model. It does not upload them. Your organization's data-handling rules still apply if you decide to share any output.

Who I built it for

Raidiness is for Microsoft 365 administrators, engineers and consultants who want a repeatable starting point for a Copilot readiness assessment. It is useful before a pilot, when adding an AI capability, or when revisiting findings after changes.

The module is available through PowerShell Gallery under the MIT license. Microsoft services, licenses and workload permissions are separate requirements.

Want to discuss the findings or the scope of your own environment? Get in touch with me.