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Typical content throughput increase
Service · AI Marketing Engine
One marketer, the output of a team of five.
An AI marketing engine is a custom-built system that owns the production side of marketing — content, SEO pages, outbound, lifecycle — while your team owns strategy, brand, and judgment. It's the leverage a lean marketing org has been waiting for.
6–12 wks
Build time, end-to-end
Your voice
Trained on your best writing, not ChatGPT default
Human-approved
Nothing ships without editorial review
01 — The leverage
Marketing teams are stuck at production.
Every B2B marketing team we talk to has the same shape: a good strategist, a good writer, and a backlog of content, landing pages, and emails that will take 18 months to work through. They ship when they can, skip when they can't, and their competitors do the same — everyone losing at the same pace.
An AI marketing engine is the way out. The strategist does their job. The writer becomes an editor. And the production bottleneck — the reason you "don't have time to blog" — simply goes away.
02 — What's in the engine
Five production lines.
- Editorial content. Blog posts, thought-leadership pieces, long-form guides — drafted in your voice from real research, with citations and human-review queue before publish. Not ChatGPT slop.
- Programmatic SEO. Hundreds or thousands of targeted landing pages generated from a structured data source — comparison pages, location pages, integration pages, use-case pages. Quality-gated, indexed, performance-tracked.
- Lifecycle & nurture email. Trigger-based sequences that personalize per recipient using real CRM signals. Onboarding, re-engagement, expansion, win-back. No more "Hi {FIRSTNAME}" spam.
- Outbound sequences. Research-first outbound — the engine reads each prospect's LinkedIn, company news, and public signals before drafting. Rep reviews and sends. Reply rates that look more like warm intros than cold email.
- Ad & social production. Weekly social posts, ad variants, LinkedIn founder content, scripts for video. Consistent, on-brand, and on a cadence you could never sustain manually.
03 — How we train it
Your voice, not the model's.
Week one is voice work. We read your best writing, interview your founders, extract the principles that make your content distinctly yours ("no hype language," "always lead with a specific scenario," "never use 'synergy,'" whatever). Those become rules the model follows on every draft.
By the end of week two, a human on your team should fail a blind taste test — unable to reliably tell which draft was written by your writer and which by the engine. That's our bar. If we don't hit it, we don't ship.
04 — What's not in scope
We don't replace strategy.
Positioning, messaging architecture, ICP definition, campaign design, editorial calendar, brand — all human work. The engine produces; it doesn't decide what to produce. If you don't have a strategist in-house, we'll recommend one or partner with your agency. We're explicit about this because we've seen teams try to automate strategy and end up with prettier mediocrity.
FAQ
The questions we get first.
Isn't AI-generated content bad for SEO?
Bad AI content is bad for SEO. Good AI content — built on real research, grounded in your data, edited by humans, and published at the right cadence — is just content. Google's stated position is that helpfulness matters, not authorship. We ship engines that produce content a reader would actually finish, which is the only metric that matters to Google long-term.
Can you write in our brand voice?
Yes — that's the first week of the engagement. We analyze your existing content, extract voice principles, build a style guide the model uses on every draft, and run hundreds of test outputs until a human on your team can't tell which was written by a writer and which by the engine.
What does the engine actually produce?
Depends on your motion. For most B2B clients: blog posts, landing pages, SEO pages, email sequences, social posts, sales enablement, and personalized outbound. For e-commerce: product pages, category pages, lifecycle emails, ad copy. The engine outputs drafts; a human reviews and publishes.
How does programmatic SEO fit in?
For many businesses, programmatic SEO (hundreds or thousands of targeted landing pages generated from structured data) is a goldmine. We build the data model, the page templates, the quality gates, and the publishing pipeline. Pages get indexed, ranked, and converted — without a human writing every one.
What does this typically cost?
Build: $40k–$120k fixed-fee depending on scope. Ongoing model cost: typically $300–$1,500/month. Compare to hiring a content marketer ($8k–$12k/month) or an agency retainer ($5k–$15k/month) and you're usually saving within 4–6 months.
Does this replace our marketing team?
No. It replaces the production bottleneck. Your marketing team still owns strategy, positioning, campaign design, editorial judgment, and brand. They just stop being stuck writing the 15th blog post of the quarter. Teams we've built engines for usually redirect the team toward higher-leverage work rather than shrink it.
Drowning in the content backlog?
Let's scope your engine.
Bring your content calendar, your site traffic, and your biggest production gaps. We'll tell you where AI gets you leverage — and where you're better off hiring a human.
Start the conversation →