Applied AI in the portfolio, not in the deck.
Every portco has the same back office and the same AI mandate from the board. We answer the AI question in diligence, pick the workflows that move EBITDA, and engineer them once, then deploy the pattern across the portfolio instead of starting over at each company.
- 1dataroom.ingestdata room2,400 files, 4 portfolio companies
- 2metrics.extractdata roomARR, churn, margin by month
- 3variance.flagmodel3 restatements against the CIM
- 4memo.draftmodelIC-ready summary, every figure sourced
4 calls · 2,400 files · 3 flags raised
The work today
Why the AI mandate stalls.
The mandate arrives from the board without an owner, a budget line, or a plan that fits the hold period. That’s the problem to solve.
Every portco solves it alone
Five companies, five vendors, five pilots, five repetitions of the same mistakes. Nothing built at the first company is reusable at the second, so the portfolio pays five times.
The mandate has no owner
The board asked for an AI plan. The portco CFO has no AI team, the CTO already has a full roadmap, and the sponsor doesn’t want to add headcount to find out.
Diligence skips the AI question
Tech diligence covers architecture, security, and debt. It rarely answers whether the target’s data and workflows can support AI at all, which is now a price question.
Value creation runs out of runway
You have a few quarters to show operating improvement before the exit story gets written. A twelve-month platform program doesn’t fit, and everyone knows it by month eight.
Workflows
Where AI now changes the economics.
Engineered once against the workflow your portcos already share, then redeployed. The second company costs a fraction of the first.
AI diligence
Ingests the data room, extracts metrics by month, flags restatements against the CIM, and drafts an IC-ready summary with every figure sourced back to a file.
Data room → model → IC memo
Back-office workflows across portcos
Runs AP/AR matching, vendor onboarding, and customer setup as AI workflows rather than three coordinators per company. Engineered once, then repeated at the next portco.
ERP → banking → CRM
Portfolio-wide knowledge layer
Consolidates policy, process, and institutional knowledge from each acquisition into one layer new companies onboard into instead of rebuilding.
Doc stores → knowledge layer → assistants
Board and lender reporting
Pulls the period numbers from each portco, reconciles them to one definition, and drafts the pack with the source and timestamp behind every figure.
Portco ERPs → warehouse → reporting pack
100-day AI plan
Turns the post-close AI mandate into a sequenced build with named workflows, sized savings, and the first system live inside the first hundred days.
Workflow audit → build → production
The frontier, applied
What’s newly possible here. And what each one changes in private equity.
Multimodal AI
A data room of PDFs, spreadsheets, and decks read and reconciled in days instead of weeks.
Documents, images, and forms become structured data without anyone keying them in.
Reasoning systems
Figures checked against the CIM and each other, with every variance explained and sourced.
Models work through policy, rules, and edge cases, and show how they reached the answer.
Agentic workflows
Shared back-office work runs as one pattern, redeployed across the portfolio.
Multi-step processes run end to end. People approve the exceptions instead of doing every step.
MCP & agent interoperability
One way for AI to reach each portco’s ERP and CRM, scoped and logged, instead of five integrations.
Your software gains a second kind of user: agents, with scoped and auditable access to act.
How we work
From the first workflow to production. Governed the whole way.
One senior squad at a flat rate, working across the portfolio. Getting faster is our problem and your gain.
- 01Advise
Diligence that answers the AI question
We assess a target or a portco the way we’d have to build inside it: data readiness, integration surface, workflow volume, and what AI could realistically take on. You get a sized opportunity, not an adjective.
- 02Engineer
One pattern, many portcos
We design against the workflow the portfolio shares and wire it into each portco’s ERP and CRM, with institutional knowledge consolidated into one layer the next company onboards into.
- 03Operate
Handover a buyer can diligence
Run logs, cost per run, and an operating manual that survives a CFO change. It reads well in a data room, which is the point.
Systems
Inside the systems you already run, not beside them.
- Data rooms and diligence repositories
- NetSuite, Sage Intacct, and mid-market ERP
- Salesforce, HubSpot, and portco CRMs
- Snowflake and portfolio reporting stacks
- Azure and AWS tenants per portco
- HRIS and shared services platforms
Proof
Work we can show you. Production systems, not demos.
Case studyPrivate Equity/Engineer · Operate
One AI assistant answers HR questions across every acquired company.
A PE roll-up: one AI assistant across every acquired company, with new acquisitions onboarding into the same knowledge layer.
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Case studyPrivate Equity/Govern
Security remediation that cleared every audit inside the deal timeline.
Security and compliance remediation across portfolio companies, cleared inside the deal timeline.
Read the case studyOther industries
Start with one portco.
Pick the company with the worst back-office ratio or the loudest board mandate. An AI engineer will tell you what AI can take there, what it costs, and how the build redeploys across the portfolio.