How it works
What the first year looks like.
You keep talking to us in Slack or Teams. What changes, month by month, is how much of your operations runs on rules you decided — and how little of it needs you.
From the first request to the routine running itself.
Week one
Requests become operations.
You ask for something in plain language. We turn it into a named, tested operation, show you a preview in business terms, and you run it once against a real record before it goes live. Every run is logged from the first one.
For example"We need a returns tool." You get approve return, issue refund and restock item — previewed against last Tuesday's order before anything touches Shopify.
Month three
Drift gets caught and fixed; the glue retires.
We watch your systems for disagreement and bring you the fix, not an alert. The old automations run side by side with ours until the numbers match, then they're switched off.
For example"Shopify and ShipBob disagree on 14 SKUs from yesterday's receiving. Correcting them makes 6 purchasable again. Approve?" One tap. Two Zapier flows retired the same week.
Month six
Rules are drafted from your history, shadowed, then enforced.
We read what your team actually decided and propose the rule behind it. It runs in shadow first, so you see what it would have done, before it enforces anything.
For example"You declined 31 returns in 90 days; all were past 60 days or a third return. Want that as a rule?" Two weeks of shadow later, a warranty exception is added and the rule goes live.
Year one
Routine decisions run themselves; your ops manager approves the exceptions.
Operations with a clean track record move from per-run approval to a daily summary. The escalations that remain come with a recommendation and the context to decide in one tap.
For exampleSmall inventory corrections have run 212 times with zero reversals, so they now run on their own. Maria's queue is the dozen returns a day that genuinely need her.
Anytime
Your AI coworkers get the same safe hands as your staff.
When your team wants AI to do real work — answer support, adjust orders — it acts through the same operations, under the same rules, on the same record, with its own limits.
For exampleYour support assistant can approve returns under $150 and change addresses, with a $2,000 daily refund budget. Anything over the limit goes to Maria, as it does today.
Every interaction
The same four beats, every time.
Something happened, here's what we propose, tap to approve, here's the log. It's the same in Slack, in Teams, and in the email we send people who don't live in either.
You don't learn a new tool. You answer a message.
Adiom Crew1. Something happened
Shopify and ShipBob disagree on 14 SKUs, all from yesterday's receiving. Most likely a missed update from the warehouse.
Adiom Crew2. What we propose
Correct the 14 counts in Shopify. 6 SKUs become purchasable again.
Maria · Ops3. Tap to approve
Approved
Adiom Crew4. Here's the log
Done. Counts match across Shopify, ShipBob and NetSuite. Logged under Inventory drift v2, approved by Maria.
What you don't do
What we deliberately leave out.
No dashboard to check
The three numbers you'd look at arrive every morning. Everything else is one question away.
No builder to learn
Nobody on your team drags boxes around. You describe what you want; we build it and run it.
No engineering team to hire
Code, hosting, monitoring and the 2am fix are ours. And everything we build for you stays yours — you can take it with you at any time.
Start with a 30-minute stack review.
We'll map your systems and tell you the first three things we'd fix.