Shipped to production, not pitched as a demo
AI Marketing & Consulting
Most of the marketing work that eats senior time can be handled by an orchestrated AI pipeline — briefs, scoring, drafting, enrichment — when the pipeline around the model is designed properly. This is consulting and integration work, not a demo.
How this work runs in practice
Most AI engagements start with a workflow audit — what repeats, what depends on judgment, and where a language model can do useful work without generating liability. From there the design favours the smallest viable model for each step, with human review gates wherever the output materially matters.
The pattern draws on operational practice: governed pipelines with per-token cost tracking, retrieval over structured data, and quality-analysis steps before anything is published. The aim is systems that ship, get measured, and improve — not speculative autonomy.
What's included
- Workflow audit
- A written pass over the marketing operation identifying what repeats, what depends on judgment, and where a language model can do useful work without generating liability.
- Content pipeline design
- Orchestrated production pipelines with distinct steps — signal ingestion, research, drafting, quality analysis — and human review checkpoints where the output actually matters.
- Model orchestration
- The right model for each step, with a per-token cost ledger so spend stays predictable and the team can compare runs.
- Human-in-the-loop gates
- Explicit checkpoints where a human reviews, approves, or rejects before anything goes live. The team stays in control; AI handles the repeatable parts underneath.
- Governance and review
- Written guidelines for when the team trusts model output, when it requires review, and how to handle model releases and drift without rewriting the integration.
How it works
From audit to governance
Five phases, each producing a concrete artifact the team can operate from — not a slide deck.
- 1AuditMap current marketing workflows and identify where language-model work will be useful — and where it will not.
- 2DesignDesign an integration for the specific workflow: model selection per step, cost projections, fallback behavior, human checkpoints.
- 3PilotBuild a working prototype against the real workflow. Observability and cost tracking wired in from day one — not a demo.
- 4IntegrateWire the pilot into the existing stack. CMS, CRM, calendar, analytics — AI as a layer on top, not a replacement.
- 5GovernDocument when the team trusts output, when review is required, and how to handle model drift and releases.
Frequently asked questions
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