See how AI connects the work behind an agency or an online store. From the first signal to a useful output, with a clear role for your team.
Explore the workflows ↓The team spends its reporting time collecting numbers instead of interpreting them.
Ad performance, store revenue, attribution windows and the previous reporting period.
Organizes the evidence, checks definitions and drafts the changes that need an explanation.
Reviews the interpretation, resolves mismatched figures and approves what goes to the client.
A sourced report draft with key movements, open questions and proposed next steps.
Define the goal, connect the context, set the review points and verify the result. AI OS brings these choices together into the way your company operates.
Explore the AI Operating Model →The methods behind the work: six campaign blueprints from our existing library. Explore the scope below.
Every asset stripped out, so the machine stops making display ads and behaves like Shopping you can steer.
inside — the two settings that must move together · when it beats full PMax · the guardrailsStop auctioning off customers who already chose you — impression-share bidding with a hard CPC ceiling.
inside — variant & misspelling set · target-IS with a ceiling · a 15/4 RSA built for ExcellentHow much of your PMax "performance" is your own brand name? Measure the leak, wall it off.
inside — the leak measurement · the exclusion route · where the freed budget goesMost audits kill TOFU for not converting like BOFU. This one reads terms by funnel stage first.
inside — the stage taxonomy · waste patterns per stage · the keep / cut / negate callsSpend per product against real search demand. Budget sitting on fading demand shows up immediately.
inside — title ↔ demand matching · rising vs fading flags · the reallocation ruleThe editorial page between the ad and your store — MOFU traffic gets sold on the way in.
inside — the page anatomy · ad ↔ page message match · where it beats a product pageOne address opens the whole shelf — every blueprint on it now, and the ones added later. The shelf grows the way the learning database grows: a method only gets written down after it has held in a live account.
Bring the recurring task, the systems involved and the decision that needs your attention. We’ll map a useful starting point together.
Discuss your workflow →