Deep brand knowledge
I keep a detailed picture of each brand, so nothing starts from a blank page — the voice, the commercials, the people, and how each number is actually defined.
TJDY — Dubl Intelligence
The engine
behind the work.
It's the setup I use to do the reporting, auditing and monitoring side properly. It connects to the tools each brand runs on, learns the business in detail, and checks the numbers against source before anything goes out. If something doesn't add up, it says so rather than smoothing it over.
I built it, I run it, and I read everything before it reaches you.
Get in touch →Zero-dashboard.
Most setups hand you a dashboard and leave you to work out what it's telling you. But a dashboard is just raw numbers — you've still got to turn it into a decision yourself.
I'd rather do that part for you. So you get the answer in whatever form's actually useful — a quick line once a week, or a proper write-up to read with a coffee once a month. Whatever suits how you work.
There's a fair bit behind it: a detailed picture of each brand, connections into the tools you actually use (including a few that don't connect easily), and far more cross-checking than I could do by hand.
The loop, end to end.
Information goes in, checked work comes out, then it runs again — so effort and spend go where the numbers say they matter.
- 01Knowledge
- 02Connectors
- 03Agents
- 04Red team
- 05Human check
- 06Ship ↻
Bespoke connectors
Custom links into the tools each brand runs on — further than the off-the-shelf ones reach, and sometimes where there's no connector at all. It works off live, first-hand data.
Checked before it ships
Before anything's published, a deliberately disagreeable review re-derives the figures and tries to break them. Only what holds up makes the page.
The engineering is the product.
The clever part isn't the AI model — it's everything around it. The brand knowledge, the connectors and the checking are what make the output specific and worth trusting. The model itself is just one piece, and a swappable one: I use whichever suits the job rather than tying it to any single one. It's proper plumbing, not a chat window with a logo on it.
What it produces.
Audits
Thorough digital audits that put a number on the opportunity — each finding shown with its basis and how confident I am in it.
Reports
Monthly reports in plain English that tie back to your own numbers, with an honest status on each figure.
Monitoring
Daily alerts that flag what matters and stay quiet when nothing does. They suggest what to do — they don't act on their own.
The machine drafts. A human signs.
I read everything before it goes out. Each figure carries its basis and an honest status, and stays provisional until I've checked it. The monitoring suggests; it doesn't act by itself. That's the one line I won't cross — it's what keeps it worth trusting.
A board of adversaries.
When I set it a task, it puts agents to work — finding the information, writing the code, doing the research. But none of that comes straight back to me.
First it goes to what I call the board of adversaries: a set of agents briefed to disagree. They pick the work apart and argue it out, checking it against the real evidence — your emails and documents, the underlying data, and what good actually looks like in code and paid media. If it doesn't hold up, it goes back to be redone. Only what gets through that reaches me, and then you.
So by the time it reaches you, it's already been through the argument. You're seeing the version that came through it — which is why the numbers tend to stand up, and why you get the honest figure rather than the flattering one.
Want this behind your brand?
I run Dubl Intelligence inside the work for the brands I look after. If it sounds useful for yours, get in touch.
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