Most “AI solutions” are a chat window bolted onto a process nobody mapped. The useful kind is quieter: a pipeline that drafts, checks, formats and publishes while a person reviews the exceptions; an agent that reads the morning numbers and writes the report; a step in a creative workflow that used to take a day and now takes the time it takes to approve it.
Content systems. Pipelines that research, draft, edit and publish directly into WordPress or Shopify at volume, with brand voice held consistent and a human editing step that stays in the loop. Multi-language where you need it.
Creative production. Product images, ad creative, thumbnails and video generated and composited to a repeatable recipe, so the fiftieth asset looks like the first instead of drifting.
Automation and agents. Custom agents and integrations that do a defined job: pull a report, triage an inbox, update a CRM, generate a draft, reconcile two systems. Built on your existing tools rather than a new dashboard for you to learn.
AI inside your product. Support deflection, search and recommendations, document understanding, and language model APIs integrated into your app or site.
Volume is easy. Consistency is the engineering.
AI output at volume is easy. AI output at volume that stays consistent is the hard part, and it is almost never solved by a better prompt.
It is solved with structure: a locked specification the model cannot drift from, a generation step, and a deterministic step that handles anything which must be exactly right. In our own image pipeline, every piece of text in a finished graphic is drawn programmatically rather than generated, because a model will eventually misspell a word and at the hundredth asset that is a certainty. Generate what can vary, compute what must not — that is how we design every AI system we hand over.
We run on this stuff
Our own operation would not exist at its current size without it. Content pipelines that publish across properties with image generation built in. A daily report that assembles cost and revenue by country from several networks and puts the losing rows on top. Creative variation at the volume testing needs. Lead pipelines that move a form submission from Meta to a sheet to a WhatsApp message without anyone touching it. We build for clients what we had to build for ourselves — with the review step kept in.
- Find the job
Which repeated task costs the most hours or produces the most errors.
- Scope it
What the system must do, and what it must never do unsupervised.
- Build and connect
Into your real tools, with the human checkpoints kept.
- Test against the old way
Same inputs, outputs compared side by side.
- Hand over
Documented, and runnable by you without us.
What you get
- A scoped pipeline or agent with its inputs, outputs and failure handling defined
- Integration with the tools you already run, with credentials you keep
- Documentation and a hand-over, so it does not depend on us
- Usage and cost reporting for the model APIs it calls
Outside our control
- Model provider pricing, limits and behaviour changes
- Output quality on inputs the system was never scoped for
- Decisions that need a human — we build the review step in, not around it
Scope, deliverables, timelines and fees go in writing before work starts. Ad spend, platform fees and third-party subscriptions are billed separately from our fee.
Publishers and brands producing content or creative at volume, teams drowning in repetitive operational work, and product companies that want AI features built properly rather than bolted on.
Will AI-written content hurt my SEO?
Unedited, generic AI content will. Content that is researched, structured, edited and genuinely useful performs on its own merits, because search engines rank the result rather than the production method. We build the editing step in, because that step decides which of the two you get.
Which models do you use?
Whichever fits the job and the budget. We are not tied to one vendor, and the choice is part of the scope.
Can this work with the tools we already use?
That is the point. We integrate with your CMS, store, sheets, inbox and CRM rather than replacing them.
Is our data used to train models?
We use API access rather than consumer apps, and configure retention per provider. We put the specifics in writing before anything is connected.
What does a project look like?
Usually one well-defined job first, scoped in weeks rather than months, so you can see the before and after before committing further.
Start with the audit
We look at what you have now and tell you what is costing you money. You get the findings whether or not you hire us.