How we work

Own the outcome, or buy it.

Two ways to work with us, with the same discipline in both: agree the result first, then build what produces it.

Portfolio · co-founding

We build companies and own part of them.

We co-found ventures with people who own a market, build the product and the operations, and take a stake alongside a fee. Investor and engineering team in one.

Role
Co-founder and builder
Terms
Equity plus fees
Horizon
Years
See the portfolio
Direct · for operators

We deliver a result you can measure.

Name the result you need. We agree the baseline and the measure, build what delivers it and keep it running, with pay tied to milestones and to the measure.

Build
Fixed fee per milestone
Run
Retainer against agreed measures
Reporting
Monthly, against the baseline
Start a conversation

Pay follows depth.

The further we go with you, the more of our pay rides on the result.

  1. ModelBaseline

    We map how the business works and agree the measure that matters, with a baseline and a date.

    Part of every engagement
  2. Build0 → 1

    We deliver the first result, live and accepted against that measure.

    Fixed fee per milestone
    Custom software development
  3. Run1 → n

    We run the systems, data and AI workflows behind the result, including ones another team built, and keep improving them.

    Retainer against agreed measures
    Maintenance, support and operations
  4. OwnEquity

    Where the result is a company, we build it with the founder and hold a stake.

    Equity plus fees
    See our ventures

Need one workflow fixed first? We also automate workflows and connect business systems, measured against a baseline.

The model

Start with a model of the business.

A result is only as clear as the definition behind it, so the model comes first.

Every business runs on a model of itself: what it deals with, how those things relate and who decides what. Most never write it down.

We write it down first, as one shared definition that every system, team and AI agent works from. It tells us what a good result looks like and how to measure it, and each thing we build on it costs less than the one before.

01Data
  • Inverter feeds
  • Site records
  • Bookings and payments
  • Spreadsheets
02Model
  • People and assets
  • Rules and decisions
  • The measure that matters
03Outcome
  • 358.4 GWh of clean energy measured
  • 92,895 tCO2e of carbon credits
  • 10,000+ vehicles risk-scored
Applied AI

AI earns its place when it moves a number.

MIT NANDA's 2025 study found that around 95 percent of enterprise generative AI initiatives in its dataset fell short of measurable financial impact.1

We work from first principles, and we're paid against the result, so AI has to earn its place:

  1. Name the number. Hours, errors, revenue, risk: the one that has to move.
  2. Model the work behind it. The people, data and decisions that move it today.
  3. Put AI where it shifts the number. Then measure it against the baseline, every month.
Bring us a number to move

1. MIT NANDA, The GenAI Divide: State of AI in Business 2025, as reported by Fortune. Findings apply to the study's own dataset.