Your agency and brand can work on the same answer.
When one person runs the AI conversation, everyone else's questions pass through them. Adgent lets the agency and brand question the same analysis together, then carries the agreed work into the next report, plan or account move.
| Moment in the work | One person operating the AI | Agency + brand with Adgent |
|---|---|---|
| A client questions the analysis | The operator relays the question and brings back the answer. | The client and agency question Adgent in the same meeting. |
| A brand constraint changes the plan | The operator adds it to the prompt and explains the revision. | The team confirms the brand context that shapes the next piece of work. |
| The room agrees what to do | Someone turns the answer into a separate brief. | Adgent carries the agreed work into a report, plan or account action. |
| The next client review starts | The operator gathers the conversation and the work it produced. | Confirmed brand memory, account history and past work inform the next review. |
A comparison of working modes, not a claim that every AI tool works the same way.
Nobody decided to stop reading the accounts. It stopped fitting in the morning.
- Once
Three platforms, each grading its own homework.
- Every day
A dashboard, read before the stand-up.
- Then
Accounts per buyer outgrew the hours in a morning.
- So
Waste hid in the accounts nobody had read.
- So
The fix arrived after the money was gone.
- Now
A team of agents reads every account and brings you the move. You say go.
It looks first, then brings the move. Every change has a way back.
Both from live accounts: a build it questioned before drafting, and an account move put back from its recorded before-state.
One case, start to finishHotel group, Meta, Aug 2026
- The assumption"Page and pixel are connected. Set up a sales campaign."
- The question it asked insteadNot whether the pixel exists, but what it records.
- The evidence30 days: 65,042 custom events and 16,404 initiate-checkouts, but 4 purchases. Every live ad set optimised to a click with no value.
- The decisionA sales campaign could be built, but couldn't learn. The team chose initiate-checkout, knowing it carries no purchase value.
- The outputA full draft with that caveat written on the card and the reason under every field.
One live account, 11 Aug 2026. Condensed, translated.
Never one click: the way back is a new card you approve. One live account, 26 Aug 2026.
Touching the platform is easy. Knowing what to do is hard.
The shared conversation rests on the same account evidence and confirmed brand memory as the work in the app. These layers carry that context through to action.
- Wrong datamemory remembers a wrong number
- No memoryit re-suggests what you rejected
- No judgmentconfident, and unfounded
- L6Operating surfaceThe same Adgent in the app and your team's meetings
- L5Safe executionYour approval, and a way back for every change
- L4JudgmentRoot cause and a priced position
- L3MemoryYour brand's rules, confirmed by you
- L2AuditWhat happened, and where
- L1Data correctnessOne comparable number
- L0ConnectivityGoogle Ads, Meta, GA4, Search Console
Fair questions, short answers.
Isn't this a dashboard with a chat box?
Why use Adgent alongside the platform's own automation?
How is this different from an AI assistant on my ad accounts?
How much of this is built?
The comparison you can check is your own account.
Discuss how Adgent fits alongside the tools your team already uses.
- 1Connect Meta and Google AdsAdd GA4 or Search Console when useful.
- 2The agents run their daily readWith GA4 and Search Console for context.
- 3You get the decisionsEach with what it is worth a month.