The transaction, and the asset underneath it.

For investors, owners, and boards approaching a transaction

M&A Advisory

Partner-led M&A for the middle market, run on a national network of private equity funds, independent sponsors, and family offices built over decades. The senior advisor who takes the brief is the one who works the mandate.

• Buy-side search against a written mandate: sector, size, geography, timeline
• Sell-side advisory, positioning and process through to close
• Capital raising across debt and equity for growth, acquisitions, and recapitalizations
• Outsourced business development into PE-backed portfolios, from value proposition to warm introduction

For deal teams, operating partners, and portfolio company boards

Technology & AI

The technology in a target, read before the money moves, by an operator who ran engineering, security, and IT through a full hold and exit. Then the same person takes a seat and runs what the read says needs running. Every finding carries a number and a window, because a deal team cannot act on an adjective.

• PRISM™ due diligence: what gates the deal, what moves price, what threatens the thesis, and what is a lever
• CLEAR™ across the hold, sequenced against the value creation plan rather than worked as a backlog
• AI value creation, cost, and attribution: allocate the spend, recover the waste, then prove the return
• AI governance and the control plane it runs on, built to hold up under a buyer’s questions
• Fractional CTO, CISO, CAIO, or CDO in the seat, accountable to the board and to the number

A six-layer model of AI spend (API, infrastructure, tooling, people, waste, risk) that uses governance as the detection layer. Three of the six layers carry 55 percent of spend and are the least visible; working all six recovers 20 to 34 percent of AI spend in the first year.

The engagement that runs between the diagnostic and the target architecture: five phases that take a portfolio company from unlisted AI systems to a board-ready, regulator-ready governance posture.

One GP-level engagement that every current and future portfolio company inherits. Governance, readiness, and a repeatable deployment playbook: portfolio AI as operating capacity, not per-portco pilots.

A five-level measurement hierarchy (Cost, Adoption, Productivity, Business Outcomes, Enterprise Value) for verifying what AI investment produced. Most companies can evidence the first two levels and report as though they had evidenced the last two.

Turning AI from a cost and distraction into a measurable margin driver. Use case prioritization, governance, and a board-ready AI narrative: all tied to EBITDA, not pilots.

Five phases ending at exit, matching fund economics. PRISM™ diagnoses the asset; CLEAR™ operates it.

A unified governance architecture (5 pillars × 4 lifecycle stages = 20 control domains) that treats AI systems as enterprise operational infrastructure requiring identity, access, observability, and resilience controls.

Five dimensions scored 0–100. Every finding priced as CapEx requirement, EBITDA drag, or exit multiple implication. A financial instrument, not a checklist.