Prove it at the portfolio company. Distribute it through the sponsor.
Lower-middle-market and middle-market sponsors have operating teams lean enough to need outside capability and portfolios large enough for it to matter. We start with one portfolio company and one measurable sprint, then extend the same finance-specialized operating model across the portfolio, with governance built in rather than bolted on.
Experimentation is high, production is uneven, and governance and data are the bottlenecks
That gap is where an implementation-focused partner earns its place. Boston Consulting Group found that 73 percent of private equity firms run digital due diligence on most deals, but only 22 percent say a target's digital readiness influences the go or no-go decision. Deloitte's 2026 Generative AI in M&A Pulse Study found that 90 percent of organizations are now using generative AI in mergers and acquisitions, and that human review remains the top requirement for high-stakes use.
| Fragmented portfolio data | Every company reports differently. Aggregation is manual, late and argued about. |
|---|---|
| Diligence request tracking | Request lists live in email and spreadsheets; status is a phone call. |
| Portfolio-company finance teams of three | A controller, a bookkeeper and a spreadsheet, reporting monthly to a sponsor who wants a weekly flash. |
| Experimentation without production | Pilots everywhere, integration nowhere, and no evidence file when the question is asked. |
| Value creation that stalls after the plan | The hundred-day plan names the initiatives; nobody owns the workflow that delivers them. |
Three engagements, in the order the trust is earned
- 01
AI Value Creation & Risk Sprint, one portfolio company
A focused diagnostic that ends with the first workflow installed, not a deck.
- Workflow and value map across finance, revenue and operations
- AI-disruption assessment and quantified initiatives, with governance gaps named
- A hundred-day roadmap with business cases and implementation priorities, then the first workflow live
- 02
AI and digital diligence, as an operating workstream
A structured read on a target that sits beside financial, commercial and legal diligence.
- AI-disruption risk to revenue and margin; competitive AI maturity; data quality, rights and integration debt
- Automation potential by function; cybersecurity, privacy and AI-governance posture; employee use of public models
- Estimated cost and time to target state. Not an audit and not a legal opinion
- 03
The portfolio AI operating layer
The same finance-specialized operating model, reused across companies.
- Finance close and reporting automation, working-capital and receivables automation, revenue and CRM automation
- A KPI control tower across companies, with data definitions controlled
- AI governance and vendor management as a shared service, with playbooks reused across the portfolio
The same core, cut for a portfolio finance team
| Who is in the room | A portfolio-company finance team of three reporting to a sponsor monthly. |
|---|---|
| Demo documents | Management reports, KPI packs, diligence request lists. |
| The automation scenario | The monthly reporting aggregation and the diligence tracker. |
| The guardrail | Investment decisions are never automated. |
| The forbidden claim | Any valuation statement. |
| The seasonal peak | The hundred-day plan, built before close. |
Formats, weeks and labs are on the training page.
The sprint informs the operating plan. Diligence output is an operating workstream that sits beside financial, commercial and legal diligence. Nothing we build makes or replaces an investment decision, and every model touching portfolio data runs under the sponsor's governance.
- Investment and valuation judgments: the sponsor's
- Portfolio data: tenant-separated, enterprise terms, no public models
- Every agent: a named owner, a written scope, an evidence trail
Start with a workflow review
Forty-five minutes, no obligation. We map where preparation is eating judgment in your practice and tell you what to install first.