Agentic AI, built on your data — not off-the-shelf gimmicks.
AI marketing is not ChatGPT prompts and a blog schedule. It is autonomous agents that pull margin from your warehouse, throttle Meta budgets in real time, and personalise every lifecycle touch. That is what I build.
Platform ML is optimising your budget away. Agentic AI defends it.
Every ad platform's internal ML — Google Performance Max, Meta Advantage+ — is designed to spend your budget efficiently for the platform. Not for you. Its blind spot is your gross margin, your inventory position, your RTO risk, your product-market fit signal.
Agentic AI marketing lives outside the platform. It reads from your data warehouse, your CRM, your finance system — and takes autonomous action: pausing campaigns when margin drops, boosting bids on high-LTV cohorts, generating creative from top-performing angles, personalising every lifecycle touchpoint.
I build these agents on real infrastructure: OpenAI / Anthropic models via APIs, LangGraph for orchestration, your warehouse as the source of truth, and human-in-the-loop guardrails for anything that spends money.
Five agent archetypes I typically deploy
Budget Sentinel
Autonomously monitors blended MER hourly, throttles under-performing campaigns, boosts winners — against your business rules, not the platform's.
Creative Analyst
Reads your ad library, scores creatives against actual funnel metrics, drafts new variants using generative tools, and briefs your designer.
LTV Predictor
A predictive model that scores every new customer within their first session — feeding value-based bidding, cohort segmentation, and lifecycle triggers.
Personalisation Engine
Dynamic on-site content, hero copy, product recommendations, and email/SMS variants tuned to predicted LTV and behavioural intent.
Attribution Reconciler
Nightly reconciliation across GA4, ad platforms, warehouse, and finance. Flags anomalies before your Monday report does.
What an AI marketing engagement includes
Ninety days from proposal to production agents
AI audit
Data maturity check. Agent shortlist. Business-rule capture. Guardrail policy design.
Infrastructure
Warehouse hardening, LTV model training, first agent (Budget Sentinel or LTV Predictor) live.
Scale
Remaining agents deployed. Personalisation engine plugged in. Weekly retros.
Handoff
Playbook, documentation, team training. Agent maintenance retainer optional.
AI marketing — questions I get every week
Is this just ChatGPT for marketing?
No. LLM chat is a tool, not a strategy. Agentic AI marketing is autonomous software that reads your data, takes action, and learns — with humans in the loop for spend decisions.
Do you replace my current stack?
Rarely. Most engagements augment existing tools (Klaviyo, Braze, Segment, your ad platforms) with agent orchestration on top.
Which LLMs do you use?
Model-agnostic. OpenAI, Anthropic, Google Gemini, Emergent LLM key — chosen per task by capability and cost. Vendor lock-in is a bug.
What if the agents make a mistake?
Every agent with spend authority runs with hard guardrails, budget caps, and a human approval loop for anything above threshold. Autonomy is calibrated, not blind.
What data do you need?
Ad-platform data, GA4 or product analytics, CRM, revenue system. If you have a warehouse (BigQuery, Snowflake, Databricks), we go faster.
Continue reading
Ready to see the leaks in your growth stack?
Book a free 30-minute diagnostic. If there is no leverage to unlock, I will tell you on the call.
Book a Diagnostic