AI that starts with a business problem

We don’t sell software. We lay the foundation, explore the use cases worth solving, and develop working tools around the ones that change a decision.

Start a conversation about a use case

How we work with AI

  1. Lay the foundation

    Data, decision rights and guardrails come first: who owns what, what a tool may and may not do, and how a person stays in charge of every outcome.

  2. Explore the use cases

    We map where AI could change a real decision in your marketing function, then test the few that would make a measurable difference before anything gets built.

  3. Develop what works

    The use cases that earn it become working tools your team runs, with plain disclosure of what powers each suggestion and a named person approving it.

Our AI tools are built with EU AI Act transparency designed in: plain disclosure of what powers each suggestion, a clear record of where it came from, and a human makes every decision.

Each tool is built around one problem and handed over to run without us. None of them is a subscription.

Brand Visibility Tracker

Buyers now ask AI which brands to shortlist. Most marketing teams can’t say which questions matter most, or where their brand needs to appear.

Read the on-screen text (50 seconds, no sound)
  1. Your buyers now ask AI which brands to shortlist. Most marketing teams can’t say which questions matter most, or where their brand needs to appear.
  2. “Our dashboards are full, but they rarely change what we fund.” We built a tracker that starts with the questions your buyers ask, then shows what to do next.
  3. It shows whether you’re named in the answers that matter.
  4. How each answer frames you, line by line.
  5. Which sites shape those answers, and where you’re missing.
  6. Then what each team does next. Nothing changes until a named person accepts it.
  7. Now you know where your brand needs to appear, and what each team does next. Built and handed over by Sablebourne.
The live demo uses well-known brands, such as Nike, as illustrative examples. Its answers are simulated rather than produced by an AI model, and none of the brands are Sablebourne clients.
What we built
A tracker that starts with the questions your buyers ask. It shows whether your brand is named in the answers that matter, how those answers frame it and which sites shape them, then turns that into next steps for each team.
What it shows
How a visibility question becomes something a team can measure and act on, with every suggestion waiting for a named person to accept or park it.
Explore the tracker demo

Brief Studio

Briefs go back and forth between teams, approvals stall, and agencies work from out-of-date insight.

Read the on-screen text (49 seconds, no sound)
  1. “We know what to do, but delivery is messy, slow, political.”
  2. Briefs go back and forth between teams, approvals stall, and agencies work from out-of-date insight. So we built one place to brief, approve and issue work to agencies.
  3. Every brief follows the same stages, with 10 checks before it moves.
  4. Approvals sit in one queue, and a named reviewer clears each brief.
  5. One library holds the audiences, insights and approved claims. Update it once and every brief follows.
  6. Agencies read the cleared brief at a glance and ask questions on the exact line.
  7. Your team chases less, and agencies work from current insight. Built and handed over by Sablebourne.
The demo uses fictional client workspaces. Its suggestions come from Sablebourne’s briefing rules, and no AI model is used in the demo.
What we built
One place to brief, approve and issue work to agencies. Every brief follows the same stages with 10 checks, approvals sit in one queue, and a shared library of audiences, insights and approved claims keeps every brief current.
What it shows
How the briefing process a team already agrees on can run inside the work: a named reviewer clears each brief, and agencies ask questions on the exact line.
Explore Brief Studio

Message Engine

A messaging framework gets signed off, then sits in a deck. By the time it reaches each team and channel, the lines have drifted.

Read the on-screen text (51 seconds, no sound)
  1. “The strategy is clear on paper, but it changes shape by the time it reaches each team and channel.”
  2. Your messaging framework is signed off. Then it sits in a deck. So we turned it into a working tool your teams use every day.
  3. Pick the audience, stage, channel and objection. You get the approved line, with its proof.
  4. Paste a draft and every fault is marked with the rule it breaks. Nothing changes until a named person applies it.
  5. Compare two wordings on the same simulated panel. A way to rehearse, not research.
  6. Lay it out on brand. Break the identity guide and it’s stamped draft.
  7. Every line your teams use traces back to an approved message. Built and handed over by Sablebourne.
The demo runs on Skerry, a fictional outdoor clothing brand. Suggestions come from written rules, no AI model is used, and the audience panel is a simulation, not research.
What we built
A working tool built on the framework. Pick the audience, journey stage, channel and objection to get the approved line with its proof, check a draft against the rules, compare two wordings on a simulated panel, and lay a message out on brand.
What it shows
How a framework becomes something teams use every day, with every line traced to an approved message and nothing changed until a named person applies it.
Explore Message Engine

Have a problem you think AI could help with?

Start with a conversation. We’ll tell you plainly whether it’s a use case worth building.

Start a conversation about a use case Ask for a walkthrough of any demo