PE Fund × AI

AI implementation for fund operations — from sourcing to IC and monitoring

We move reading, searching, and summarizing to AI, and direct the time freed toward meeting owners, hearing management teams and LPs, deciding, and negotiating. We start with the current workflow and build an approach your fund can run with its own people.

AI in due diligence

Due diligence compresses a large volume of document review and issue tracking into a short timetable. We can start with one live or recent deal.

First-pass reading

AI performs a first pass over the VDR documents and surfaces summaries and potential issues, such as change-of-control and termination provisions in material contracts, signs of litigation or contingent liabilities, and customer concentration. People retain judgment; AI is limited to the first pass.

Q&A management

We put question-list drafts, reconciliation of answers against documents, and tracking of outstanding items into a repeatable workflow.

Cross-cutting issues

We connect findings across financial, legal, and business workstreams, organizing them in a form that feeds into the IC memo.

Measure before and after

We measure and show the change in reading time before and after due diligence.

Confidentiality by design

For each deal, we define data boundaries, disable training use, set access logging, and decide how data will be handled at the end before work begins.

How we work — Prepare, Build, Run

01
Prepare
We begin by inventorying the current deal workflow and information-handling practices, then define how the work should operate after AI is introduced: what AI will handle and where the fund's professionals will work directly with people.
02
Build
We implement around real materials and procedures. AI speeds up the creation of repeatable systems and operating guides, while training helps people in the fund become builders.
03
Run
Your fund embeds and improves the practice, directing the time freed toward closer work with owners, management teams, counterparties, and LPs.

Where the freed-up time goes

Implementation is not the end. With your fund, we decide how the time freed will be reinvested: meeting owners, spending more time with management teams and counterparties during diligence, turning LP reporting into dialogue, and handing the company over thoughtfully to its next steward. We stay involved through adoption.

Meeting owners — toward proprietary deals (sourcing)
Time with management and counterparties during DD (deal)
Turning LP reporting into dialogue — toward trust and re-ups
A careful handover to the next steward — toward lasting value (succession)

Where this can help

Reading IMs and VDR documents crowds out preparation before a meeting
IC materials and anticipated questions concentrate on a few team members
Knowledge from past deals is scattered and hard to reach quickly
AI stays with individual users instead of entering the deal workflow
The roles of people and AI after implementation remain undefined

Areas we cover

Sourcing

Industry research, long-list preparation, and first-pass screening of candidate companies.

Initial review

Reading teasers and IMs and drawing out the issues that matter.

Due diligence

Reading VDR documents, managing Q&A, and connecting issues across workstreams.

Valuation

Organizing assumptions and preparing the groundwork for sensitivity analysis.

Investment committee

Drafting materials and organizing anticipated questions and answers.

Monitoring

Summarizing monthly portfolio reports and identifying unusual KPI movements.

Knowledge

Making experience from past deals searchable inside the fund.

How information is handled

For each workflow and deal, we identify which data can go to AI and which data stays outside.

We review training-use settings, access rights, audit logs, and alignment with confidentiality obligations in the environment being used.

Related AI implementation work

These examples show people in the field moving from users to builders and growing systems around the way their work actually flows.

Before: No systems engineer in-house. Hired a staff member rich in field knowledge — but coding was completely new to him.
After: With hands-on support from 5D Management, he mastered AI-assisted coding. One month later a new app was live — plus an HP and internal tools, built from zero with their own hands. They know the field, so what they build works in the field. Website building has since grown into something they can take on as a new line of business.

Implemented at 5D Management Inc., where our founder serves as co-representative director

Before: Core operations ran on an Excel VBA system built up over many years. The CEO's own personal site had stayed on plain http — long overdue for a fix that never happened.
After: The reveal is simple: the right tool, in the right order. Day one ran 9am to 5pm, one-on-one. Using Claude Code himself, the CEO rebuilt his own long-neglected site, implemented the company's new-hire onboarding app, and wrote the migration runbook for the legacy system — all in that single day. The onboarding app with LINE WORKS and an in-house app are complete and in daily use, and the long-standing Excel VBA system is being rebuilt, in tandem with a hands-on staff member, into tools that work on a phone. And the centerpiece: a per-site budget-versus-actual tracker — the CEO's own management cockpit, once attempted in Excel and abandoned — whose implementation plan is now in the works alongside the legacy rebuild.