// AI WORKFLOW AUTOMATION
Workflows that run the work, and ask before they write.
Tell ORiON what needs doing in plain English, show it by recording yourself doing the task once, or deploy one of the insights it surfaces on your dashboards. Each becomes a multi-step workflow that reads, decides and acts across your connected systems, on demand or on a schedule, with a person approving every write.
Describe it, record it, or deploy an insight.
Describe it in a sentence
“Every Monday at 8am, pull last week's orders, compare them with the pipeline in HubSpot, and send the ops team a summary.” Before it builds anything, ORiON asks the questions it needs answered, such as which system, which fields and who receives it, then shows you the steps to check.
Record yourself doing it once
Record the manual task, say copying a meeting's details from Google Calendar into the customer's record in HubSpot, and describe it in a sentence. ORiON turns the recording into a draft workflow that uses only the systems you have connected. The video never leaves your browser: ORiON works from a few still frames and keeps only the text of the workflow it drafts.
Deploy an actionable insight
Click the light bulb on any dashboard widget and ORiON shows the patterns and trends behind it, each with a suggested next step. One click turns that step into a workflow you can run now or put on a schedule.
Read across systems, make the call, write it back.
Read from several systems in one run
Pull from your ERP, CRM, billing, payroll, email and calendar in the same run, so a step can compare what NetSuite says with what HubSpot and Stripe say.
Decide, not just move data
Match records, flag duplicates, spot what changed since last week, and pick the right action for each case, written as instructions rather than field mappings.
Write back where the work lives
Create and update records, draft the email, post the summary. Every one of those writes waits for a person to approve it.
Run on a schedule, or on demand
Daily, weekly, monthly or whenever someone clicks run. Every run keeps its history: what it proposed, what was approved, and what changed.
Nothing changes until a person says so.
A run that would change something stops and lists its pending actions: what will be written, where, and the exact values. Approve or reject each one. Nothing is sent before that, and every run, approval and change is kept so you can see later exactly what happened and who signed it off.
It sounds like friction. In practice it is why teams let a workflow near their ERP and CRM at all, and it means a new workflow can be trusted from its first run instead of after a month of watching it.
A finance team’s morning, as a workflow.
One ORiON customer's finance team starts every day with a workflow that reads new deals from HubSpot, finds the matching customer in Stripe, flags any duplicates, and stages the NetSuite customer and billing account that need creating, all waiting for one person to approve. It replaced lookups across three systems that someone used to do by hand.
That is the pattern most teams start with: a recurring task that crosses two or three systems, has clear rules, and is currently done by someone who has better things to do.
Questions people ask
Can AI build a workflow from a screen recording?
Yes. Record yourself doing the task once and describe it in a sentence. ORiON samples the recording into a few still frames in your browser, works out the steps, and drafts a workflow using only the systems you have connected. The video never leaves your browser, and the frames are not stored.
Does an AI workflow change data in my systems without approval?
No. Every write is shown to a person first, with exactly what will change, and nothing is sent until it is approved. Approvals and runs are kept in an audit log.
What is an actionable insight?
On any dashboard widget ORiON surfaces patterns and trends, each with a suggested next step. One click turns that step into a workflow you can run now or put on a schedule.
How is this different from Zapier or other automation tools?
You describe the outcome in plain English instead of wiring triggers and field mappings, the workflow can read and reason across several systems in one run, and it pauses for a person before it writes.
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