AI agency or your own team?
An honest comparison — including the cases where building your own team is the better choice.
An in-house team pays off when AI is permanently part of the core business, volume is sufficient to keep roles busy and you can retain staff in a competitive market. An agency works when speed matters, the initiative is time-boxed, or capabilities are missing whose build-up takes longer than the window. In practice the hybrid model is most common: built externally, taken over internally — with documentation and enablement as part of delivery.
Our approach: creative engineering
We work neither as tool consultancy nor as a classic production agency, but in between: creative engineering means building the production chain behind the creative work — templates, generative modules, checkable brand rules and delivery as one system. The creative judgement stays with the team, the multiplication becomes an engineering task.
The concept stays human
Idea, visual language and tone are created as before. What follows is what gets automated: variants, formats, language versions, delivery.
Brand rules the machine can check
Colour, typography, logo usage, forbidden claims — stored as rules that apply automatically before approval instead of sitting in a PDF guideline.
Production as a chain, not a tool
Template, generative module, validation step, approval and delivery interlock. A single tool without that chain only moves the manual work elsewhere.
Impact measurable at creative level
We evaluate not only the campaign but the individual attribute: hook, composition, colour world, length. That feeds the next production round.
What we take on
Speed
Building a team means recruiting, onboarding and tool selection before the first use case runs. Externally, delivery starts immediately — but internal context knowledge is missing at first.
Cost structure
In-house costs are fixed and independent of utilisation; external costs are variable and tied to engagements. With fluctuating demand that difference matters more than a day rate.
Dependency
External delivery without documentation creates dependency. That is why runbook, training and handover are part of our delivery, not of a follow-up quote.
Breadth of capability
AI initiatives need strategy, creative, data work, engineering and governance. Keeping all those roles busy internally only works from a certain size upwards.
How the engagement runs
- 01
Assessment
We review your processes, data situation and existing stack, and document where AI realistically creates impact today — and where it does not.
- 02
Prioritisation & business case
Use cases are ranked by effort, impact and risk. Every candidate gets a transparent calculation instead of a gut estimate.
- 03
Pilot in production
We build the first use case all the way into real operations — including system integration, approval flow and measurement points.
- 04
Scaling & enablement
What works gets rolled out and handed over: playbooks, training and governance, so you do not stay dependent on us.
Frequently asked questions
30 minutes, a concrete assessment
Describe your use case briefly — we will say plainly whether and how it pays off.