IT OPS

Shadow-IT Owner Outreach: Ask the Heaviest User to Justify an Unsanctioned App

When a new unsanctioned app enters the review queue, an agent identifies its heaviest internal user and DMs them on Slack for a business justification.

CategoryIT Ops
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerMonday card moves to 'Needs owner'monday.com
  • ActionRank app users by login volume in DatadogDatadogDatadog
  • LogicSelect heaviest user as likely owner
  • ActionDM the owner on Slack for justification + data contextSlack
  • OutputWrite owner + structured justification back to Monday cardmonday.com

What it does

Discovery finds the app; this finds the human. When a Monday review-queue card moves to "Needs owner," an agent looks up which employee logs into that app most, opens a Slack conversation asking why they use it and what data it touches, and writes their answer back onto the card so reviewers decide with context instead of guesswork.

When to use it

Use it right after discovery to close the information gap before a security review. It turns a faceless vendor row into an owner, a use case, and a data-sensitivity note.

How it works

  1. 1A Monday status change to "Needs owner" triggers the workflow.
  2. 2The agent reads the card and queries Datadog auth logs to rank that app's users by login volume.
  3. 3It picks the top user as the likely owner and composes a short, plain-language outreach message.
  4. 4It sends the message as a Slack DM and waits for a reply.
  5. 5The agent classifies the response into use case, data sensitivity, and whether a sanctioned alternative exists.
  6. 6It updates the Monday card with the owner name and the structured justification.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect monday.comVisual work management for teams.
  2. 2
    Connect DatadogMetrics, traces, log search.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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