Audit trails

Joins the scattered administrative change records into one timeline, so an auditor's question is a search rather than a fortnight of exports.

macOS — coming soon

No ready-made setup for this job yet.

Describe the job in a sentence, the way you would brief a colleague: when it should happen, what to check, and what to hand you. That sentence is the automation.

The job, and what good looks like.

Every administrative change an organization makes already leaves a record somewhere, but it is scattered across the identity console, the endpoint console, the cloud tenant and the ticketing system, and nobody can search across them. This workflow joins those sources into one timeline keyed to the person and the system they touched, so a question like who changed a firewall rule in March becomes a search rather than a fortnight of exports. It captures the actor, the object, the previous value and the new one, keeps the read-only and unsuccessful attempts alongside the successful ones, and retains entries for long enough to cover a full audit cycle. Changes made through an approved workflow are joined to their ticket automatically, and a change with no matching request is flagged rather than quietly accepted. A scheduled extract pulls the entries for each control into the compliance record, so the evidence is gathered on a calendar instead of in the week before an audit. A human still decides which events count as sensitive, how long the trail is kept, and who is allowed to read it.

When it is handled

Every privileged change tied to one identity
Auditor questions answered from the record
Control evidence collected on a schedule
Unsuccessful attempts kept, not dropped

Works with tools like

Microsoft Sentinel
Splunk
ServiceNow Security Operations
Vanta

You stay in charge.
At every step.

It triages and sweeps. People approve every change.

No change without approval
Blocking, revoking and purging wait for an analyst's OK.
Every run on the record
What it read, what it did and what it is waiting on, kept for review and audit.
Scoped per automation
Each automation gets only the access you grant it, and a local model can keep processing on your machine.

Before you download.

Where does it run?: On your Mac or Windows computer, in the background. It keeps working after you close its window, and only reaches the folders and apps you connect for each automation.
How does it connect to our CRM and other tools?: Through each app's own connection where it offers one, signed in once by you, or by using the app in a browser the way you would. Each automation gets only the connections you give it, and the tools a page names are examples you can swap for your own.
Does it run when my computer is asleep?: It keeps your computer awake while a job runs and just before a scheduled one. While the computer is closed or off, nothing runs; when it wakes, it checks the inbox, calendar and other sources it watches for anything that arrived meanwhile.
How does my team use it?: Each person who runs automations installs the app. Keep a project in a shared folder, such as Google Drive or a network drive, and teammates can open it and follow every run, while one person owns it and runs it.
Do I need anyone technical to set it up?: No. Download the app, add an automation in plain words, and connect only what that job needs. Nothing runs until you switch it on.

Already have tools for this? Here is the difference.

Instead ofGood atWhere it stops

Scripts and scheduled jobs

Precise, repeatable system tasks.

They break on the unexpected, and only their author can read or change them.

Security automation platforms

High-volume response playbooks in large teams.

They need a project to set up and an engineer to maintain each playbook.

AI chat assistants

Explaining an alert when you paste it in.

Nothing runs on schedule, and there is no scoped access or record of what was done.

AUTOMATE.md

Your routine, written in plain words. It runs on its own, follows your rules, handles the exceptions a flowchart can't, and asks you when it matters. The file stays yours, whichever AI model runs it.

Start with one job.
Make it your own.