Log analysis

Converts a vague question about whether something happened into a scoped search with a written answer, its sources, and its limits.

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.

An investigation usually arrives as a question rather than a dataset, and the real work is working out which log source holds the answer, how far back it reaches, and what a negative result would look like. This workflow takes the question as written, names the systems and accounts involved, and turns it into a scoped search with an explicit time range and list of sources, so the scope is agreed before anyone starts reading. It runs the search across the collected sources, adds the context a raw result needs to be read, such as which users sit in an admin group, and writes every query and source into the case as it goes. If a source the question depends on has no data covering the period, the answer says so rather than returning a clean empty result. The finding is written as a short summary with its confidence and its limits, attached to one timeline other responders can pick up. A human still decides whether an absence of evidence is acceptable, and who else should see the answer.

When it is handled

Every question answered from a logged search
Searches recorded with sources and time range
Retention gaps named before they hide a result
One shared timeline per investigation

Works with tools like

Splunk
Microsoft Sentinel
Graylog
Elastic Security

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.