AI consulting · Private equity
AI consulting for private equity firms and their portfolio companies
Native helps private equity firms use AI at the deal team and inside the portfolio: faster due diligence, a first 100 days with AI built into the plan, value creation through agents in each company's operations, and portfolio reporting that no longer depends on spreadsheets. We map a portfolio company's workflows, rank them by EBITDA impact and put the first agents into production within weeks of close.
Featuring insights fromShaun Devan · Founder & CEOUpdated · 4 min read
Where AI has an impact in private equity
Data room review
Contracts, financials and customer files read end to end, with a cited summary and the exceptions flagged.
Commercial and operational diligence
Target workflows mapped and ranked by where agents would have impact after close.
Integration and system mapping
Charts of accounts, customer lists and supplier records reconciled across the platform and the add-on.
Portfolio reporting
Company packs collected, normalised to your KPI definitions and drafted into one quarterly view.
Value creation agents
Order entry, billing, collections and service rebuilt with agents inside each portfolio company.
Procurement and spend
Supplier spend and risk visible across the portfolio, with plain-English questions answered from the data.
LP reporting support
Quarterly letters and capital account figures drafted from the fund's own records for review.
Exit readiness
Data and documentation assembled ahead of a sale, with the AI capabilities documented as company assets.
Why AI belongs in the value creation plan
Most operating partners now have an AI line in their value creation plan, and most portfolio companies have done little more than buy a few licences. The gap is implementation. A mid-market company rarely has the engineers to rebuild its order entry, billing or customer service around agents, and a slide deck from a strategy firm does not change how the work gets done.
AI earns its place in the plan when it shows up in the numbers you already track: margin, cost to serve, working capital, revenue per employee. That means building agents into real workflows, in production, and measuring them against a baseline taken before the work starts.
AI-powered due diligence
In diligence, agents do the reading a deal team never has time for. They work through the data room, filings, contracts and customer files, write a cited brief on each area, and flag the clauses and figures that need a person's attention. On adjacent research work, a fully cited company brief that took an analyst about ten hours was drafted in about an hour.
Native also runs an operational read of the target: which workflows are manual, which systems hold the data, and where agents would have impact after close. That read becomes the first draft of the AI section of the 100-day plan.
The first 100 days and post-acquisition integration
Integration is where AI saves the most time and the most goodwill. Agents map the chart of accounts from the acquired company onto the platform's, reconcile customer and supplier records across two systems, and draft the reporting pack while the ERP migration is still being planned.
A typical first 100 days with Native looks like this: two weeks mapping the company's operations, the first agent in production in the first month, and a ranked roadmap for the rest of the hold. Everything is built in the portfolio company's own accounts, so it stays with the business at exit.
Portfolio reporting and monitoring
Portfolio companies report in different formats on different systems, and someone at the fund turns it all into one view each quarter. Agents collect the packs, map each company's figures onto your KPI definitions, flag the variances and draft the commentary for the operating partner to edit.
The same approach works for questions nobody built a report for. Native helped Pierpont Holdings build three AI agents on its existing Microsoft SQL infrastructure, so its users ask questions in plain English and get answers from 2.7M records in 11 seconds.
How to measure the impact across a portfolio
- Hours returned per workflow, against a baseline taken before the build
- Cost to serve and gross margin in each company where agents run
- Days to close the month and to deliver the quarterly reporting pack
- Time from close to the first agent in production
- Share of the value creation plan's AI initiatives running in production, not in pilot
Case study · Pierpont Holdings
Pierpont Holdings gave its procurement leaders one view of 2.7M records.
Native helped Pierpont build EP2, three AI agents on its existing Microsoft SQL infrastructure, so procurement leaders can see revenue at risk, ask questions in plain English, and pull supplier reports on demand.
Frequently asked questions
How are private equity firms using AI?
At the fund, AI speeds up due diligence and portfolio reporting. Inside portfolio companies, it rebuilds workflows such as order entry, billing and customer service around agents, which is where most of the margin impact sits.
Can AI do due diligence?
AI can read a data room far faster than a deal team, write cited summaries and flag the contracts and figures that need attention. The judgement on the deal stays with the people doing it.
How does AI help with post-acquisition integration?
Agents reconcile records across the platform and the acquired company, map one chart of accounts onto another, and produce combined reporting before the systems themselves are merged.
What does an AI consultant do for a portfolio company?
An AI consultant maps the company's operations, ranks the workflows by impact and builds agents that run them inside the company's own systems. At Native the forward-deployed engineers who do the mapping also do the build.
How quickly can AI show impact in a portfolio company?
The first agent is usually in production within weeks of starting, so its impact shows up inside the first 100 days. Whole departments can be working AI native within months.
