AI Consulting · Private Equity

AI Consultingfor Private Equity

Most funds have the AI slide; few have the delivery mechanism. We give operating teams one: a standardized scan of every holding, builds at the portcos where the math clears, faster document review inside live deals, and a playbook that gets cheaper to run with each company.

The AI thesis dies between the fund and the portco

Operating partners can't be at every company, portco management teams are busy running their businesses, and vendor pilots stall the moment the internal champion gets pulled away. The result: one holding has a chatbot, another has a stalled pilot, and the fund has no comparable view of any of it.

We supply the missing layer — one assessment rubric, an execution team, and patterns that transfer from one holding to the next.

What We Do

The delivery mechanism behind the thesis

Portfolio-Wide Opportunity Scan

Every holding scored with the same rubric — automation potential, data maturity, integration complexity — so the operating team can rank portcos by expected value rather than by which CEO is loudest about AI.

Portco Value-Creation Builds

At the companies where the numbers clear, we execute: reporting automation, back-office and customer-ops workflows, document processing. The portco owns the system; the fund gets the EBITDA effect.

A Playbook That Compounds

Vendor selections, security patterns, integration templates, and rollout lessons codified after each build — so portco number four starts from decisions already vetted at portco number one.

Diligence & Data-Room Acceleration

During a live deal, AI-assisted review of data-room documents — contracts, financials, customer files — surfaces what your team should read closely, and a target's automation upside gets sized before the IC memo is final.

Proven for PE

The proof point is a sponsor-backed company

We took a PE-backed client's general-ledger mapping — days of skilled finance work per cycle — and compressed it into an automated pass with human sign-off. Scoped, operational, measurable: the profile of win we hunt for across a portfolio, grounded in enterprise AI work done inside a Fortune 50 organization.

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Who We Work With

Built for the firm and the portfolio

PE & growth firms

Operating partners who need the AI agenda to produce EBITDA, not another deck.

Portfolio companies

Management teams that want a working system delivered, with their people trained to run it.

Deal teams

Faster data-room review and a sized automation thesis while the deal is still live.

FAQ

PE AI consulting, answered

What does AI consulting for private equity look like?

Two motions. Across the portfolio: a standardized assessment of every holding, builds at the companies where the case is strongest, and a playbook that makes each successive rollout cheaper. Inside the deal: faster document review and a grounded view of a target's automation upside while diligence is still open. In both, we advise and we build — the thesis comes with an execution team attached.

Do you have experience with PE-backed companies?

Yes — our reference engagement is exactly this profile. A sponsor-backed company had a general-ledger mapping process eating days of finance time each cycle; we automated it into a supervised review step. That's the shape of value creation we look for: operational, measurable, and repeatable at the next portco.

How does a portfolio-wide engagement work?

It runs like a value-creation program, not a consulting study. One rubric applied across holdings produces a comparable ranking; the operating team decides where to deploy; we build at those companies while feeding what we learn back into the shared playbook. Each portco keeps ownership of its systems — which matters at exit — and the fund keeps the accumulated patterns.

Can you assess AI upside during diligence?

Yes, on deal timelines. Working from the data room and management sessions, we gauge a target's process maturity, data quality, and realistic automation headroom, then hand the deal team a scoped view they can use in the model and in first-100-day planning — not a generic AI-opportunity slide.

How much does it cost?

Per-company assessments are fixed-price once we've seen the shape of the portfolio; build engagements are priced per project at each portco, and diligence support is scoped to the deal calendar. Because the playbook carries forward, the marginal cost of each additional company falls. See the pricing guide for representative figures.

How quickly can a portfolio company see results?

A single-company build follows normal deployment timelines once management access and data are in place — but the portfolio effect is the point: the second and third rollouts move faster than the first, because the security reviews, vendor decisions, and integration patterns are already settled.

Put an execution engine behind the AI slide

One conversation with your operating team. We'll propose an assessment rubric for your holdings, name likely first-build candidates, and show how the playbook compounds.

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