The opportunity map
A ranked, specific list of AI workflows that will return measurable time or quality within one quarter. Also a shorter list of the ones that won't.
§ Approach — How an engagement runs
Our business model is unusual, but deliberate. Most consultancies bill more because you come to depend on them. We work the other way around: our work is successful when you can run it yourself.
What follows is the actual shape of that arc: four phases over three to nine months, ending in a handover you'll recognise when it arrives.
This creates a rational incentive to deepen the dependency: keep the client in the room and the work in the firm, with the next phase always one quarter away. None of this is conspiratorial. It's what the contract rewards.
For the kind of teams we work with, that model is a quiet disaster. It leaves your people watching the work rather than doing it, and your organisation no better equipped at month nine than at month one.
The engagement is a fixed arc, and the final phase is a handover. Success is measured by whether your team is still shipping new workflows six months after we leave.
That standard is named in writing at the start of every engagement, and we report against it at the end of every phase. If a phase isn't moving the team closer to it, we redesign that phase, or end the engagement early.
Fig. 01 — The four phases
We start with team-based or role-by-role observation, watching how the work currently happens and writing down where the friction is. Then together we separate the AI use cases that will pay off the most from the ones that only read well in a deck. The output is a short, specific overview of where to start.
§ 02 — Deliverables
The objects, documents and habits a finished engagement leaves behind. None of these are decks for their own sake. They're the things your team uses after we are gone.
A ranked, specific list of AI workflows that will return measurable time or quality within one quarter. Also a shorter list of the ones that won't.
Two or three live AI-assisted pipelines, built together with your people. They run on your systems, maintained by your own team.
A short, plain-spoken document on how your team uses AI: which tools they've picked, what patterns work, what guardrails are in place. Updated by your team after we leave.
A working rhythm of fortnightly reviews and a quarterly horizon scan, kept by your team without a transformation budget or an external partner in the room.
§ 03 — Deliberate limits
No long-term managed service. No SaaS hidden inside a deck. The engagement has a defined end. After that, you can call when you want a second opinion, but the daily work is yours.
Most organisations shouldn't be buying intelligence; they should be building it. The reports you can buy are written for somebody else's questions, on somebody else's schedule. We help your team build the capability instead.
This is a small practice. Every engagement runs with the senior practitioner in the room. The pipeline is paced accordingly. If we can't do it well right now, we say so, and we say when we can.
We promise something less dramatic and more useful: a team that can keep doing this work on its own after the engagement. That outcome compounds for years; a 90-day spike does not.
We are deliberately a small practice. Every engagement runs through someone who has spent years heading the innovation and digital functions of the multinationals you might be competing with, and who now uses that experience on your side of the table.
Being small is the feature, not a limitation. The kind of attention that is structurally hard to get from a large consultancy firm is the default here. The alternative simply doesn't exist.
The constraint that follows is real and named openly: we take on a small number of engagements at a time. If the timing is wrong, we say so.