What kind of AI systems do you build for marketing?

We build AI-powered reporting pipelines, automated campaign management systems, lead qualification tools, content generation workflows, and custom AI agents trained on your business data. Everything we build runs in production - not just demos.

Do I need a technical team to use your AI systems?

No. We build systems your team can operate without developers. Outputs arrive in Slack, email, or Google Drive - wherever your team already works. We handle the infrastructure, you handle the strategy decisions.

How much does AI engineering for marketing cost?

AI Engineering projects start from $10,000 + GST for the initial build, plus a monthly maintenance and improvement retainer from $500/month. Scope and pricing depend on the complexity of the systems required.

What's the difference between AI automation and regular marketing automation?

Traditional automation follows fixed rules - if X then Y. AI systems make judgment calls: analysing performance data, identifying patterns, writing copy, and recommending actions the way a senior analyst would. The difference is qualitative intelligence, not just speed.

AI Marketing Engineering - Install AI Into Your Team

Why this exists

Every SaaS is selling you AI. Almost none will install it in your company.

Most "AI marketing" offers today look the same: vendor builds something on their infrastructure, charges you a monthly subscription, and you rent access. When you cancel, the AI leaves. Your data trains their product. You never own the thing.

We built it the other way. Over the last 12 months we've shipped a working multi-agent marketing operation that runs inside Hedgehog - content, paid ads, SEO, reporting, brand QA, the lot. Now we can install that same system, customised to your brand and your marketing ops, inside your company.

1

You own it

Installed on your infrastructure. Your repos, your secrets, your data. When we're done, the AI is yours. Full stop.

2

Custom to your team

Every agent is tuned to your brand voice, your products, your customers, your reporting needs. Not a generic template with your logo on it.

3

Real infrastructure

Built on the same stack that runs ours. Claude, Anthropic SDK, Google Workspace, Slack, your ad platforms, your CRM. Production-grade, not a demo.

Step zero - before the agents do anything

We build a knowledge base first. So Hilda lands as an onboarded employee, not a stranger.

A new senior hire takes 3–6 months to ramp because nothing's written down. Your agents land on day one with everything they need: who you are, who you sell to, what good looks like, what to never say. Here's what goes in:

📚

Source of Truth

Products, pricing, positioning, USPs, target customers, ICP, segments, geographies. The single document every agent checks before doing anything.

🎨

Brand Files

Voice & tone guide, lexicon (words you say / words you don't), visual identity, brand personality, hero examples of on-brand work.

📄

Templates

Deliverable formats. Reports, briefs, proposals, decks, email layouts, ad copy frameworks - all stored so every agent ships in your house style.

📝

Playbooks & SOPs

Briefing checklists, approval flows, launch checklists, monthly cadence, QA standards, meeting rituals. Codified once, followed forever.

🔗

Live Data Connections

GA4, Search Console, ad platforms, CRM, email tool, social tools, helpdesk. Read access wired up so agents work from real numbers.

👥

Team Map

Who owns what, who approves what, how decisions get made. So Hilda knows whether to send something to Sarah, Tom, or your CMO.

📊

Historical Context

Past campaigns, what worked, what failed, what got killed for political reasons. So agents don't suggest the same thing your last marketing director got fired over.

🎯

Customers & Personas

Real customer interview notes, ICPs, jobs-to-be-done, objection patterns. Agents speak to your customers, not at them.

It's yours. The knowledge base lives in your Drive / Notion / CMS - whatever you already use. We help you build it once during the install. After that it's an asset that compounds: every new hire, every new agent, every new tool inherits it. The single biggest reason most "AI for marketing" tools feel hollow is that they don't have one.

The agent catalog

24 agents trained on your knowledge base. Picked and tuned for how your team works.

Not every company needs all of them. The scoping call is where we figure out which ones actually matter for your team. Here's the menu:

HildaCEO OrchestratorReceives every brief, routes work, runs peer review between agents.

WrenStrategistWrites briefs before execution. Checks output against the brief.

SilasAccount DirectorSets monthly priorities, runs health checks, keeps your marketing on strategy.

PoppyProject ManagerTracks delivery, flags blockers, chases owners. Keeps every project moving.

PiperPlanning AgentDrafts monthly marketing plans, content calendars, campaign timelines.

MoMeeting → TasksReads Gemini / Fireflies / Otter transcripts. Turns action items into tasks in your ClickUp / Asana / Notion.

JunoContent AgentDrafts blog posts, landing pages, product copy - on-brand.

BowieEmail AgentNurture sequences, broadcasts, lifecycle flows, abandoned cart.

MossySEO AgentKeyword research, metas, topical authority plans, on-page.

OttoAd Copy AgentWrites Google, Meta, LinkedIn ad variants tuned to your campaign angle.

IndieCreative DirectorBriefs visual work, grades designs against the brief, calls the shots.

PipGraphic DesignerGenerates concept imagery, ad creative, social graphics via image gen + Canva.

CloverSocial MediaWrites captions, schedules posts, drafts reels scripts - every channel.

BrambleCampaign BuilderParses a campaign brief, generates a structured plan, posts to the Ads agents for launch.

GoldieBrand QAChecks every deliverable against your brand guidelines before it ships.

PosieCopywriter QAStrips AI slop. No flat, generic, corporate tone - ever.

LedgerData QACross-checks every number in a report against GA4, GSC, Ads, CRM.

RookReporting AgentPulls GA4, GSC, ad platforms, CRM. Drafts weekly / monthly reports.

KitAnomaly AgentFlags spend spikes, conversion drops, ranking drops, traffic crashes.

CassCompetitor IntelTracks competitor ads, organic pages, pricing, and flags what's changed.

BeatrixSocial ListeningWatches for brand mentions, trending topics, and competitor news.

Hilda AI Tracking QA agent icon for analytics and pixel monitoring

Tracking QAMonitors GA4, GTM, pixels, conversions. Flags broken tracking immediately.

Want one we don't have? That's what your maintenance tier covers - feature requests, new agents, integrations with whatever tool your team adopts next.

The pipeline, not the demo

Every task routes through a CEO agent. Every output gets peer-reviewed before it reaches you.

This is how a real multi-agent system works - not one model doing everything, but a hierarchy where a CEO orchestrator receives briefs, routes work to specialists, and makes them check each other's output before anything hands back to a human.

The CEO is the front door. Everything starts with her.

You don't talk to 20 agents directly. You brief the CEO - in Slack, email, or a task - and she decides: who owns this, what context they need, who should review the output, and when it's ready to come back to you. It's the difference between an AI tool and an AI team.

The Prep or Do It rule

The CEO decides: can the agents ship this, or do they hand you a prep kit?

Every task that lands on the CEO gets sorted into one of two buckets. This is the single most important rule in our stack - it's what stops agents from over-reaching, and it's what makes you trust the system.

✓ Do It

The agents have the skills → they ship it.

Writing a blog post, drafting ad copy, optimising bids, building a weekly report, flagging anomalies. Anything with clear guardrails and agents trained for the job. The CEO routes, they execute, QA reviews, you approve.

Example: "Ship a blog about our new pricing" → Content Agent drafts, QA reviews, CEO delivers a ready-to-publish draft.

📝 Prep It

New territory → the agents prep you for it.

Something the agents can't (or shouldn't) execute alone - board decks, new hire briefs, strategic pivots, customer escalations. Instead of failing or faking it, the agents build you a prep kit: context, options, draft materials, risks.

Example: "We need a customer retention strategy" → agents pull churn data, competitor research, and draft options - you walk into the meeting prepped, not starting from zero.

Example 01 - Weekly content

"Ship a blog post on our new feature by Friday."

Brief lands in Slack → routes to the CEO orchestrator.

CEO reads the brief, pulls brand guidelines + product context, assigns to Strategist.~30s
Strategist writes a detailed content brief - angle, outline, SEO target, CTA. Hands to Content.~2 min
Content Agent drafts the post. Submits to QA.~5 min
Copywriter QA reviews for AI slop, flat writing, lazy structure. Kicks back 3 edits.~1 min
Brand QA checks against brand voice, tone, disclaimers. Passes.~1 min
CEO packages the final draft + SEO metas and drops it in your inbox for approval.~30s

Example 02 - Automated ads

"Keep our Google & Meta ads optimised."

Runs on a schedule. No brief needed.

CEO triggers daily ads sweep.Daily
Google Ads pulls yesterday's performance. Pauses 2 underperforming keywords, shifts 8% budget to the best-converting ad group.~90s
Meta Ads checks creative fatigue. Queues 3 new variants for the winning adset.~2 min
Data QA validates the changes against your guardrails. Approves.~30s
Anomaly spots a conversion tracking gap on one campaign. Flags to CEO.~1 min
CEO posts a one-line summary in your Slack: "3 optimisations shipped. 1 tracking issue flagged."~30s

Example 03 - Monthly report

"Get the October performance report ready for the exec team."

Runs on the 1st of the month - or on demand.

CEO kicks off the monthly pipeline at 7am.1st of month
Reporting pulls GA4, GSC, Google Ads, Meta Ads, your CRM. Drafts narrative sections.~4 min
Data QA cross-checks every number against source-of-truth dashboards. Flags one GA4 discrepancy.~2 min
Reporting fixes the discrepancy, adds a note on the anomaly.~1 min
Brand QA checks formatting + exec-ready tone. Passes.~1 min
CEO drops the polished .docx in your Drive and pings your marketing lead.~30s

Example 04 - Campaign kickoff

"Launch a new product campaign in 2 weeks."

Big brief. Routes through the full stack.

CEO receives the brief, breaks it into workstreams, assigns owners.Day 1
Strategist writes the campaign brief. Planning builds the timeline.Day 1
Competitor Intel scans the space. SEO picks target keywords. Creative Director writes the visual brief.Day 2–3
Content drafts landing page + blog. Ad Copy writes 12 ad variants. Graphic Designer concepts 6 creatives.Day 4–6
Brand QA + Copy QA cycle. Feedback round-trips until ship-ready.Day 7–8
CEO packages the full campaign kit for your approval and briefs the ads agents for launch day.Day 9

Installed vs hosted

Why own it instead of renting it.

Most "AI for marketing" subscriptions are just an API wrapper + someone else's prompts. You pay monthly forever. You don't learn anything. You don't keep anything.

What you get	Hosted AI tool	AI Engineering (installed)
Where it lives	Their servers	Your infrastructure
Your data	Trains their product	Stays with you
Customisation	Whatever their roadmap allows	Anything you want, built for you
If you leave	Lose access, start again	Keep everything, keep running
Cost over 3 years	$200–$2,000/mo × 36 = $7k–$72k, you own nothing	$10k build + $6k–$36k maintenance = $16k–$46k, you own everything
Feature requests	"We'll add it to the backlog"	Shipped in your next monthly update

The build process

From scoping call to shipped infrastructure in ~6 weeks.

Step 01

Scoping call

We map your current marketing ops, workflows, tools, pain points. Then we pick the 5–10 agents that'll move the needle first.

Week 1

Step 02

Infrastructure setup

We provision your environment, wire up your Anthropic + Google + CRM + ads accounts, and set up the agent runtime in your stack.

Week 2

Step 03

Agent customisation

We take each agent from our stack and retune it for your brand, your voice, your data, your reporting needs. No generic prompts.

Week 3–5

Step 04

Training + handover

We train your team on how to brief agents, review their work, extend the system. You leave week 6 with a running operation.

Week 6

Investment

Transparent pricing. Every project scoped individually.

Build · one-off

From $10,000 + GST

Scoped based on number of agents and integration complexity. Typical range: $10k–$25k. Larger installs ($25k–$50k) quoted on scope.

Scoping call + system design
Full infrastructure setup in your stack
5–10 custom-tuned agents installed
Integration with your CRM, analytics, ad platforms
Team training + documentation
90-day warranty on the initial build

Maintenance - pick a tier, change anytime

Light

Care & Feeding

$500

+ GST / month

Monthly health check, updates when we ship improvements to core agents, small fixes. No new builds.

This is not for everyone. And that's the point.

You're a good fit if…

You run marketing in-house for a real company - B2B SaaS, ecommerce, services, manufacturing.
You're a marketing team of 0–20 people - from a solo founder doing it all, to a small in-house crew buried in execution.
You're already spending serious money on ads, content, and tools - and seeing the inefficiency you want to fix.
You want AI installed permanently inside your company, not another SaaS subscription that rents it to you.
You have - or can get - a technical point-of-contact (internal dev, fractional CTO, or contractor) to work with us during the build.
You're ready to invest in a real system, not a demo.

You're not a fit if…

You're a marketing agency looking to install this for your clients - that's a different scope.
You're looking for a cheap AI chatbot you can bolt on in an afternoon.
You don't have ongoing marketing work for agents to plug into.
You want us to run your marketing for you - that's what Consulting is for.
You can't commit any internal capacity to the 6-week build phase.
You want to "try" AI before committing. This is a real investment, not a sandbox.

FAQ

Questions we get a lot.

What does "installed in my business" actually mean?

We deploy the agent infrastructure inside your own accounts - your Anthropic API key, your Google Cloud project, your GitHub repo, your Slack workspace. The agents run on your infrastructure, not ours. You own the code, the configuration, and the data. We're the builders; you're the owner.

Do I need to be technical?

You need a technical point-of-contact on your side - someone who can give us access to your accounts, review pull requests, and do basic ops work once we hand over. That could be an internal developer, a contractor, or someone on your team with engineering chops. It doesn't have to be the business owner.

What if I want more than 10 agents?

The $10k floor buys you 5–10 agents well-tuned for your core ops. Bigger installs with 15+ agents, complex integrations, or custom workflows typically scope at $25k–$50k. We'll scope on the call - no hidden charges.

What do the maintenance tiers actually cover?

Light ($500/mo) is care and feeding - monthly health checks, updates when we improve our core agents, small bug fixes. No new builds. Medium ($1,500/mo) is the sweet spot: everything in Light, plus ~1–2 new agents or significant feature builds per month. Heavy ($3,000/mo) is for clients with a busy feature pipeline - ongoing architecture work, 3–5 features per month, a dedicated engineer. Move between tiers with 30 days' notice.

Can I cancel maintenance and keep the agents?

Yes. Everything we install is yours. If you cancel maintenance, your agents keep running - you just won't get our ongoing builds, updates, or support. Most clients stay because the feature pipeline is worth it, but you're never locked in.

How does this compare to hiring an in-house developer?

An in-house mid-level developer costs ~$120k/year fully-loaded. We cost $10k upfront + $6k–$36k/year depending on tier. We're not a replacement for a dev team - we're a specialist crew for one specific job: installing marketing AI. Once the install is done, a less-senior internal person can maintain it with our support.

What tech stack do you use?

The Anthropic Claude SDK for the model layer. Node.js / Python / TypeScript for runtime. Google Cloud or AWS for infrastructure. ClickUp + Slack + Google Workspace for orchestration. We adapt to your stack where it makes sense, but the core is proven tech that will still be working in 5 years.

Can I see a demo of your agent stack before I commit?

Yes. The scoping call is where we walk through what we've built for Hedgehog, show how the agents interact, and talk about which ones would map to your business. It's free.

★★★★★

"The AI systems Hedgehog built us save hours every week. Our team spends less time on admin and more time on the work that actually matters."

Hedgehog Marketing Client

Want to see what this could look like for your business?

Book a free 45-minute scoping call with Josh. We'll walk through our stack, map it to your ops, and give you an honest answer on whether it's worth building.

Book a scoping call → Send a message

Install marketing AI inside your company.