LLM & generative AI

Generative AI content systems

Content pipelines with your brand rules, factual grounding and a human sign-off gate — built to scale output without scaling the risk.

What is a generative AI content system?

A generative AI content system is a production pipeline — not a chatbot — that takes a brief or data source, generates content against documented brand rules, checks it for factual grounding and compliance, and routes it to a human for approval before publication. The controls are the product.

The controls matter more than the generation

Anyone can generate content with a model. The difficulty is doing it a thousand times without publishing something factually wrong, off-brand or legally exposed. That is a workflow problem: grounding in verified source material, brand rules encoded as constraints rather than hoped for, automated checks, and a human who signs off with accountability.

We also build in the boring safeguards — plagiarism checking, claim substantiation for regulated categories, and an audit trail of who approved what. These are what make the system survive its first mistake.

Process

How we deliver it

1Codify brand voiceTurn your style guide intoexplicit, testableconstraints.2Ground the factsConnect verified productdata, policies and approvedclaims.3Build the pipelineBrief to draft to check toreview queue.4Add compliance checksClaim substantiation,prohibited terms, plagiarismscan.5Publish with sign-offHuman approval, thenautomated distribution toyour channels.
Process flow for Generative AI content systems
  1. 01

    Codify brand voice

    Turn your style guide into explicit, testable constraints.

  2. 02

    Ground the facts

    Connect verified product data, policies and approved claims.

  3. 03

    Build the pipeline

    Brief to draft to check to review queue.

  4. 04

    Add compliance checks

    Claim substantiation, prohibited terms, plagiarism scan.

  5. 05

    Publish with sign-off

    Human approval, then automated distribution to your channels.

Deliverables

What you receive

  • A running content pipeline connected to your CMS or channels
  • Encoded brand voice rules with test cases
  • Compliance and factual checking layer
  • Review queue with approval audit trail
  • Quality sampling process and team training

Engagement shape

Six to ten weeks. We strongly recommend running with mandatory human approval for the first quarter regardless of quality.

Tooling

What we typically build with

  • Anthropic API
  • OpenAI API
  • WordPress and headless CMS APIs
  • Python
  • Vector databases
  • Plagiarism check APIs

Stack decisions follow the problem. This is where we usually start, not a fixed menu.

Frequently asked

Questions we get about this

Will Google penalise AI-generated content?

Google's stated position is that it rewards helpful, original content regardless of how it was produced, and penalises low-value content produced primarily to manipulate rankings. In practice that means grounding, genuine usefulness and human review matter — which is exactly what this pipeline enforces. Mass-generating thin pages is the thing that gets punished.

Do we still need writers?

Yes, and their job changes rather than disappears. They define voice, write the pieces that carry the brand, and review at the gate. Teams that removed writers entirely produced content that was fluent, unremarkable and quietly ineffective.

Talk it through before you commit

A discovery call is a working session on your constraint, not a sales pitch.

Quick inquiry

Tell us what you're trying to build

A short note is enough. You'll hear back from the team, not a bot — usually within one working day.

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