For Private Equity
An AI plan the board backs, and one team that carries it across every company in the portfolio. For operating partners at private equity firms and the companies they own.
How we work across a portfolio
A senior team works with your operating partners and inside each company you own, and it's in the room when the board asks what the AI budget bought. AI coding agents do the repetitive building and a senior engineer reviews every change, so one small team moves from company to company.
- One assessment across the portfolioWhere each company's time and money go, and which workflows would return an AI investment first, measured the same way everywhere so the answers compare.
- One project at one companyWe build the top item where it pays off fastest, and agree up front how we'll measure it.
- The next company starts aheadWhat we built and tested becomes the starting point at the next company, so each project costs less than the last.
- Each company owns its workCompany-specific code and data stay with that company, in its own accounts, so nothing we build complicates an exit.
Every add-on brings its own systems
Each acquisition brings another billing, scheduling or operating system, and its own way of counting. The numbers across the portfolio don't match, so the board doesn't trust them, and every portfolio review starts with someone reconciling spreadsheets by hand.
There's an AI budget too, and pressure to show where it pays off. Nobody has the time to prove it out across the companies, and their staff don't know which AI tools are safe to use with customer and business data.
One set of numbers across the portfolio.
- One view across every company
- A fix built once, reused at the next
What we fix
Five problems come up at company after company.
- No plan for where AI pays off. Leadership wants to know which companies and workflows return the money first, and that answer needs numbers it can trust.
- Systems that don't match. Each add-on counts customers, volume and revenue its own way. Our data science work maps every company to the same definitions.
- Information moved by hand. Staff retype the same details between PDFs, portals and the systems of record. Our automation work reads them once.
- Staff unsure which AI tools are safe. There's no written list of what can be used with customer and business data. AI team upskilling does, and trains each team on it.
- A target nobody has read. Before you close, a short read on the company's stack, its data and what AI could do there in the first 100 days. After you close, the same team builds it.
We already build for a PE-backed company
Knox Lane invested in HCEsquared, the company behind Dermsquared, in March 2025. Since then we've been Dermsquared's product team: the app it owns, the platforms behind it, the data pipelines across events, app and learning, and a weekly session with its leadership on what to build next. Support tickets are down 80% and the first release went from concept to production in three months. The Dermsquared case study shows the work.
They didn’t just build what we asked for. They understood what we were trying to accomplish and helped us get there.
What operating partners ask us
Can you do this across our portfolio?
That's how we work: one assessment across the portfolio, one project at one company, then the rest. Company-specific code stays with each company.
Where do we start?
With the assessment, then one project at the company where it pays off fastest. You see that project's numbers before deciding on the next.
Can you look at a company before we buy it?
Yes. A short read on its stack, its data and what AI could do there in the first 100 days, so the plan is ready at close.
Our portfolio companies run their own IT.
Good. We work alongside them on one project at a time, inside their accounts, and hand over code each company owns. You get one view across the portfolio, and their team takes it over when they're ready.
What about regulated data?
Where a company handles patient, financial or other regulated data, we design to the rules that apply, HIPAA included, and keep everything in that company's accounts. We'll walk its compliance team through the controls.
What happens at exit?
Nothing changes. Each company's code, data and accounts are its own from day one, so a buyer's diligence finds working software and a written record, not a vendor dependency.
We'd love to chat.
Bring what's slow, rented or stuck. You'll leave with what we'd build first and how long it takes.
Book a call