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Check every release had an approved change
For operations teams who want Azure DevOps deployments matched to ServiceNow change requests, by asking their AI assistant.
On this page
Connector
Connect Azure DevOps, pick your AI tool and paste the prompt.
The problem
Unapproved deployments are found late
Checking that every deployed release had an approved change is a manual cross check between Azure DevOps and ServiceNow. It takes time and tends to be skipped, so unapproved deployments are found late.
Without PopdockAI
- Export deployments from Azure DevOps
- Search ServiceNow for each change request
- Check approval status by hand
- Skip the check when time is short
With PopdockAI
- Deployments and change requests are read for the window
- Each deployment is paired with a change request
- Rows are marked covered, unapproved or missing
- Each match states its confidence, and nothing is created or edited
The prompt
Use this prompt
Copy it into any AI tool connected to PopdockAI. Swap the values in braces for your own.
**Objective:** For Azure DevOps releases in project `{project}` deployed in the last `{lookback-days}` days (default 14), confirm a matching ServiceNow change request exists and was approved. If `{release-name}` is given, check only that release.
**Step 1: Read the deployments (azure-devops server)**
Call `azure-devops-get-deployment` with `project` = {project} and, if provided, `release-name` = {release-name}. Keep deployments with `completed-on` inside the lookback. Call `azure-devops-get-release` with `project` and `name` for each distinct release to get `description` and `created-by`.
**Step 2: Find the change request (servicenow server)**
For each release call `servicenow-get-change-request` with `short-description.contains` = the release name. Also search the release `description` text for a CHG number and fetch it with `number`. Check `planned-start-date`, `state` and `approval`.
**Step 3: Report**
A table: release, environment (`environment-name`), deployed on, `deployment-status`, change `number`, change `state`, `approval`, and a verdict: covered, change not approved, deployed outside the planned window, or no change found. Put unverdicted-as-covered rows first.
**Rules & Guidelines:**
* `azure-devops-get-deployment` and `azure-devops-get-release` are on the azure-devops server. `servicenow-get-change-request` is on the servicenow server.
* Read-only. Do NOT call `servicenow-add-change-request` or `servicenow-update-change-request`.
**Validation:**
* If no deployments are found, say so and stop.
* A name match alone is probable, not confirmed. State which kind of match each row has.Who it's for
One answer, three teams that use it
Change managers
Catch deployments without approval
Unapproved and missing changes are listed, so they are dealt with before the next audit.
Which Fabrikam API production deployments this month had no approved change?
IT auditors
Evidence change control
A covered, unapproved and missing list with match confidence supports your audit testing.
Reconcile Northwind Portal deployments from last quarter with ServiceNow change requests.
Release managers
Check your releases followed process
Confirm each deployment you ran had its change approved.
Did every Contoso Web staging deployment in the last 14 days have a ServiceNow change?
How it works
What PopdockAI does when you ask
You give a release definition and window, and your AI assistant checks every deployment for an approved change. Change requests are never created or edited.
01
Ask
You give the release definition and the time window.
02
Read
It reads the deployments and the ServiceNow change requests.
03
Match
It pairs each deployment with a change request and rates the match.
04
Report
You get covered, unapproved and missing, with confidence per row.
What PopdockAI provides
The tools behind the answer
Ready made tools for Azure DevOps and one secure connection to your AI tool. No code, no exports.
azure-devops-get-deployment
azure-devops-get-release
servicenow-get-change-request
This report is built from Get data tools only. PopdockAI applies the row, field and parameter rules your admin sets, and every query is written to the audit trail.
The outcome
Every deployment checked for an approved change
Related use cases
More ways to put this data to work
One prompt template with infinite possibilities.
Your AI assistant adapts its approach, tone, and capabilities to match each unique context while you maintain a single, manageable workflow.
Join forward-thinking companies that are transforming their operations with intelligent, secure AI automation.

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