Services  ·  AI Marketing Engine

Campaigns that write, test and iterate themselves.

Marketing output is capped by how fast a human can write. That cap is why most content calendars are aspirational. Remove it and the constraint becomes strategy — which is the part worth your attention anyway.

In short

An AI marketing engine produces, tests and refines marketing content at a volume a human team cannot match — landing pages, product copy, email sequences, ad variants — while a person keeps control of brand voice, claims and approval.

The problem

The bottleneck is production, not ideas.

The calendar is fiction by week three

Two posts in, someone gets busy, and the plan quietly dies. Consistency, not brilliance, is what compounds — and consistency is exactly what a human schedule cannot guarantee.

Thousands of pages nobody will ever write

Product, location and category pages that would each earn a little traffic go unwritten because writing them is not worth a person's week.

You test two variants instead of twenty

Testing is limited by production capacity, so you learn slowly and on a small sample of ideas.

Voice drifts across channels

Three freelancers produce three brands. Nobody is at fault; there is simply no enforced definition of how you sound.

What we build

What the engine produces.

01

Programmatic pages at scale

Product, category, location and comparison pages generated from your own catalogue or database, each one specific rather than templated filler.

02

Email sequences

Onboarding, nurture, win-back and post-purchase flows written, segmented and scheduled, with variants tested against each other.

03

Ad and landing-page variants

Enough versions to actually learn something, generated and rotated rather than hand-written two at a time.

04

A brand voice that is enforced, not hoped for

Your voice is captured as an explicit specification and applied to every output, so consistency does not depend on which person wrote it.

05

Refresh of what already exists

Existing pages updated against current facts and prices rather than left to rot — usually the fastest available win.

06

Human approval where it matters

Claims, prices, guarantees and regulated language route to a person before publication. Volume is automated; accountability is not.

How it works

From first call to running in production.

01  ·  Week 1

Capture the voice and the facts

We build an explicit specification of how you sound and what is true — products, prices, claims you can defend. This is the part that stops generated copy inventing authority you do not have.

02  ·  Weeks 1–2

Build the generation pipeline

Wired to your real catalogue or CMS, producing a first batch for review. You read actual output before scale, not a sample.

03  ·  Week 2

Review gate

You approve the first batch and we tune against your edits. Anything touching a claim or a price keeps a permanent human gate.

04  ·  Week 3+

Publish and measure

Output ships and performance is measured per cohort, so you can see what the volume actually earned rather than assuming it worked.

What you get

Included in every engagement.

  • Written brand-voice specification, yours to keep
  • Verified fact and claim base the engine may draw on
  • Generation pipeline wired to your CMS or catalogue
  • Human approval gate on claims, prices and regulated language
  • Variant testing with results reported per cohort
  • Refresh pass over existing pages
  • Performance measurement against a stated baseline
  • Full handover of pipeline and documentation

Works with

WordPressShopifyWebflowAstro / Next.jsHubSpotMailchimpKlaviyoResendGoogle Analytics 4Google Search ConsoleMeta AdsGoogle Ads

Not listed? Most tools with an API can be integrated — just ask.

Client results

Every figure came off a real engagement.

DTC Brand · AI Marketing Engine  ·  Feb 2026

2,400 product pages. +340% organic traffic. 90 days.

2,400pages rewritten in weeks
+340%organic traffic, 90 days
0copywriters hired

Fit

When this is the right call — and when it isn't.

A good fit if

  • A catalogue or database with many similar items
  • An existing brand voice worth preserving
  • Channels where volume genuinely compounds
  • Someone who can approve claims quickly

Not the right call if

  • Businesses with a handful of pages and no catalogue
  • Regulated copy requiring legal sign-off on every line — the gate would erase the speed
  • Anyone wanting content with no human review at all; we will not build that

Asked first

AI Marketing Engine, answered.

What does it cost?

There's no fixed package price — output volume, channel mix, and integrations vary by business. We scope a custom quote on a short call once we understand your goals and current setup.

Which channels does it cover?

Blog, email, LinkedIn, and the social platforms where your audience actually is. One piece of content is repurposed and reformatted for each channel automatically, rather than written from scratch every time.

How much content can the engine actually produce?

As much as your review process can approve and your channels can absorb — typically several times the output of a manual team. We tune the volume to your cadence so quality never slips to hit a quota.

What's the difference between this and just using ChatGPT?

The system connects your brand, your keyword strategy, your CMS, your email platform, and your analytics into one automated workflow. ChatGPT gives you a blank page. This gives you a running operation.

Do we still need a human reviewing content?

Yes, and we recommend it. The AI handles volume; humans handle judgment. We design the review workflow to be light — typically 20–30 minutes per week to approve a full week's content — not a full-time job.

Does the AI content actually sound like us?

We spend the first week documenting your brand voice — tone, vocabulary, messaging pillars, and things you never say. The system is trained on that before we publish a word, and you review and adjust until it sounds right.

Will this read like AI slop?

That is the failure mode we design against, and the defence is the fact base and the voice specification rather than a better prompt. Generic output comes from generic input — an engine given your real catalogue, real prices and a documented voice produces specific copy. You read the first batch before anything scales.

How do you stop it inventing facts?

It draws from a verified fact base rather than from open generation, and anything touching a claim, price or guarantee passes a human gate before publishing. Generated copy fabricating authority — invented case studies, invented prices — is a real and common failure, so it is gated structurally rather than checked by eye.

Does Google penalise AI content?

Google's stated position is that it rewards helpful content regardless of how it was produced, and penalises unhelpful content produced at scale. That distinction is the whole design constraint: pages must each be genuinely specific and useful, which is why the fact base matters more than the volume.

Start

Tell us the part you'd most like to hand off.

30 minutes. No deck, no pitch. Describe the part that costs you the most time, and we'll tell you exactly what it would take to automate it.