Generative AI Consulting · Marketing

Generative AI Consulting for Marketing

Brand-safe generative content systems with a claims library and evals — not another ChatGPT seat and a hope.

Service
Generative AI
Industry
Marketing
Updated
2026-08-25
Engagement
6–10 wks
The short answer

Generative AI consulting for marketing helps brands replace ad-hoc ChatGPT use with a production content system: a versioned brand kit, a claims library, retrieval of approved proof points, evals that block invented claims, and CMS write-back — typically live on one content type in 6–10 weeks with 50–80% automation on targeted intents.

The premise

A shared ChatGPT login is not a marketing system: it has no claims library, no evals, and no audit of what shipped.

Engagement
6–10 wks
to production content workflow
50–80%
automation on targeted intents
Claims-gated
copy before it leaves the building
The path
01Discover
02Design
03Build
04Validate
05Enable

Why teams pick this engagement

Generative AI × Marketing

Claims library, not vibes

Product claims, disclaimers, and prohibited phrases are retrieved and checked on every draft. The model does not invent clinical, financial, or performance claims.

Brand kit as system context

Voice, terminology, and example packs are versioned. A new campaign uses the kit that legal signed, not last quarter’s Slack thread.

Evals on brand and factuality

Golden briefs score voice match, banned-claim hits, and citation of approved proof points before a draft reaches a channel owner.

CMS and DAM integration

Drafts land in Contentful, Sanity, or your DAM with source assets attached. The system of record is not a chat history.

Legal and brand still approve

Regulated claims, comparative copy, and net-new product language stay in a review queue. High-volume variants auto-ship only after evals hold.

6–10 weeks to a live workflow

One content type — product pages, email variants, or localized listings — in production with 50–80% automation on those targeted intents.

Key takeaways

  • 01

    A shared ChatGPT login is not a marketing system: it has no claims library, no evals, and no audit of what shipped.

  • 02

    The first content types that automate cleanly are structured ones — product copy, email variants, localized listings — not the brand manifesto.

  • 03

    Every product claim must map to an approved proof point; invented performance, clinical, or pricing language is a failed eval.

  • 04

    Legal and brand review stays on net-new and regulated claims; high-volume variants can auto-publish only after those evals hold.

  • 05

    On targeted intents, 50–80% of first-draft and variant work typically moves off the human, with channel owners still accountable for what goes live.

What the engagement covers

01

Content System Discovery

Inventory channels, volume, brand-kit maturity, and legal constraints. Pick one content type with enough structure and proof points to automate without inventing the brand.

02

Brand Kit & Claims Architecture

Versioned voice pack, terminology, approved claims, disclaimers, and banned phrases; retrieval over proof points; output schemas that force citations to the library.

03

Production Content Workflow Build

Brief-to-draft pipeline in your VPC with CMS/DAM write-back, localization memory, and a review queue for claims that are not in the library.

04

Brand & Claims Evaluation

Golden briefs, voice graders, banned-phrase scanners, factuality against the claims library, and a CI gate on prompt or model changes.

05

Brand Team Enablement

How to add a claim, retire a phrase, and read eval failures — plus 30 days on-call so marketing ops owns the system.

How we work

  1. 01

    Discover

    Channel volumes, brand-kit gaps, legal claims constraints, and the single content type we will ship.

  2. 02

    Design

    Claims library schema, review gates, CMS write path, and evals reviewed with brand and legal.

  3. 03

    Build

    Retrieval, generation workflow, and CMS/DAM integration in your environment with weekly draft reviews.

  4. 04

    Validate

    Golden-brief scoring, banned-claim red team, and localization checks on real campaigns.

  5. 05

    Enable

    Production on the targeted content type, runbooks, and 30 days on-call.

Take the playbook with you

The working documents from real engagements — free, in exchange for an email. They’re useful whether or not we ever talk.

Flagship resource · PDF · 18 pages

Brand-Safe Generative AI Operating System

How to stand up a claims library, eval gates, and CMS write-back so marketing GenAI is a system, not a login — with a 20-point launch checklist.

Get the operating system ·
DOCX + XLSX

Brand-Safe GenAI Claims Library Template

The schema for approved claims, proof points, disclaimers, and banned phrases — plus the eval rubric that blocks drafts that invent them.

Get the template ·
PDF · 7 pages

Marketing Content Eval Scorecard

Voice, factuality, claims, and channel-fit graders we run in CI so a prompt tweak cannot silently change the brand.

Get the scorecard ·

Frequently asked questions

What is generative AI consulting for marketing?

It is the design and implementation of a production content system: brand kit, claims library, retrieval of approved proof points, evals, and CMS write-back. It is not prompt training for a ChatGPT workspace.

Why not just give the team ChatGPT or Copilot?

Those tools do not know your approved claims, do not fail a draft that invents a statistic, and do not leave an audit trail in the CMS. They are fine for brainstorming. They are a risk as the path to published copy.

How do you keep generated copy on-brand?

Versioned examples and terminology in context, retrieval of the claims library, a voice grader on golden briefs, and a human queue for anything that is not a variant of approved language.

Can generative AI invent product claims?

It will try if you let it. The control is architectural: claims must cite the library, and a banned-phrase plus factuality eval blocks the draft. There is no prompt that is a substitute for that gate.

How much of content production can be automated?

On targeted, structured intents — product descriptions, email variants, localized listings — 50–80% of first-draft and variant work is typical. Brand films, thought leadership, and net-new regulated claims stay human-led.

How long until a marketing GenAI workflow is in production?

One content type with brand kit, claims gates, and CMS integration typically takes 6–10 weeks. Additional channels reuse the same library and evals.

Does legal still review copy?

Yes for net-new and regulated claims. High-volume variants that only recombine approved proof points can skip review once evals hold. That split is a design decision, not an accident.

Will this work with our CMS?

Drafts write into Contentful, Sanity, Adobe, or your custom CMS as unpublished items with the brief, sources, and eval scores attached. Publishing remains your existing workflow.

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