Executive summary
We’re building a consulting business that enters on advisory — senior judgment the big firms can’t deliver AI-native — and then stays to run the function it recommends. AI and agents carry the production and the ongoing operation; a small senior team supplies the judgment, the accountability, and the relationship. Advisory is the tip of the spear; the embedded, software-run operating function is the body of the business. And we scale on software, not headcount — the moment we grow by adding people the way a traditional firm does, we’ve rebuilt the firms we’re displacing.
Who we serve
Regulated scale-ups and SMEs carrying a heavy compliance load they must meet, but that are too small to staff the function in-house and too small for a major firm to serve profitably — companies operating below the big players’ floor. The regulatory load is the forcing function: it makes a serious digital and compliance function non-negotiable exactly when the company can least afford to build one. This is deliberately guerrilla — we win where the incumbents can’t profitably follow. And it means the work is never about cutting staff: these clients can’t afford the headcount in the first place, so there is no one to displace — we add a function that wouldn’t otherwise exist.
What we sell
A working function on a subscription, not hours. Advisory gets us in the door and earns the right to operate; then the research, analysis, documentation, vendor evaluation, monitoring, and compliance tracking that consulting firms staff with juniors is carried by AI and agents at near-zero marginal cost — and so, increasingly, is the ongoing run. The senior human makes the build-versus-buy calls, negotiates with vendors, sits at the board table, and puts a name on every decision. Clients pay a monthly fee for an outcome they can see running. Part of what we leave embedded is an intelligence layer the client’s own people can run — their data, documents, and processes answerable in plain language, what dashboards always promised and never delivered. It is the wedge-to-managed-service motion the best cyber-security firms already run, applied to the digital operating function.
Why now
The pre-AI version of this model worked. One of the founders built and ran an embedded, retained function for a major APAC data centre operator in its scale-up years, and the engagement only ended because an acquisition created an audit conflict. The constraint back then was that every hour of the operating layer needed a person, which set a floor on viable client size and a ceiling on margin. AI removes that constraint — the operate layer can now run predominantly on software — which is precisely what lets us serve profitable functions for regulated clients sitting below the big firms’ cost floor.
The incumbents can’t follow. Big 4 and strategy-house economics rest on a pyramid of junior labour billed at multiples of cost. Most have also mis-sized the shift — pricing AI as a 5–10% efficiency gain when the reality is an order of magnitude, one person doing the work of ten — and even those who see it are responding by bolting AI onto the old advisory motion (a copilot to write the deck faster) rather than rebuilding advisory around agentic workflows. Doing what we do would mean dismantling the revenue engine their partnerships depend on. They are cutting graduate intakes, not restructuring. That leaves the position genuinely unoccupied.
Where we start
The segment is a pattern, not a sector, and it generalises across regulated industries. We enter where it is most acute and accessible right now: the cohort of Australian companies forming to build and operate the renewable grid — backed by infrastructure capital, facing demanding digital and regulatory obligations from day one, with no internal IT function. Sector selection is the venture’s core discipline, and Australian renewables went through the same gating evaluation we’d apply to any sector — ratified as the beachhead in June 2026 (section 10). The first play is the Renewable Energy Zone delivery cohort, where the founding team has a direct, currently embedded relationship. Renewables is the wedge; the regulated-and-can’t-afford pattern is the business (section 5).
The shape of the business
Fee and retainer based, with a small senior team running several embedded engagements at once because the production and operate layers no longer scale with headcount. The worked financial model (section 8) shows the practice profitable at five clients with three people, with margin expanding as clients are added without proportional hiring. Whether the venture ever takes equity in its clients is deliberately undecided; it isn’t an assumption the model depends on.
What we’re honest about
This plan names its open problems rather than smoothing them over. The load-bearing bet is the one in the model itself: how light the operate layer’s human footprint can genuinely go — whether it runs on software at scale or quietly reverts to bodies. Go-to-market is unproven. The quality ceiling — the point at which engagement complexity demands materially more senior time — is unknown until we run a real engagement, and the first one is designed to measure exactly that. The model scales only as far as senior judgment and trust scale. And the founding team’s transition out of current employment has constraints that shape sequencing. Each has its own section.
The founding team
Three founders envisaged: the owner plus two partners. Between them the venture needs senior client judgment and advisory experience, AI-native delivery capability (one prospective founder already runs a hybrid local + frontier model stack with routing in a live production system), and sector access (including a currently embedded position in the beachhead cohort). Roles, equity, and commitment are worked through together in section 14.