For private equity

Your portfolio companies' customers ask AI who to call. Do you know who gets named?

ChatGPT, Claude, and Gemini answer with two or three names — and every miss routes demand to a competitor, multiplied across every company you hold. Hoss baselines the whole portfolio with one fixed methodology, fixes the companies with the most recoverable demand, and re-measures monthly.

PLAIN ANSWER

AI visibility — sometimes called GEO or AEO — is whether AI assistants name your companies when their customers ask for recommendations. For a PE firm it behaves like any other value-creation lever: it can be baselined across every portco with the same methodology, fixed where the gap is largest, and reported monthly as a portfolio scoreboard.

01 — The deliverable

One baseline. Every company. Ranked.

Every portfolio company gets a full teardown — the same one we sell standalone. The firm gets this: a league table of where each company stands in AI answers, so capital and attention go where the recoverable demand is.

PORTFOLIO AI-VISIBILITY BASELINE · SERVICES PLATFORM ILLUSTRATIVE — FICTIONAL PORTFOLIO
Portfolio company Mentioned Recommended Citation share Who wins instead
Lakeland Pest SolutionsPest control · 11 branches 72% 41% 26% Holding — the playbook works here
Cedar Peak Heating & AirHVAC · 6 branches 58% 19% 14% A national franchise
Magnolia Dental PartnersDental · 9 practices 51% 12% 11% Two independents with deep reviews
TruShine Commercial CleaningFacility services 44% 16% 9% A regional rival, in every market
ClearFlow Plumbing CoPlumbing · 4 branches 39% 8% 7% Directory roundups
Ironwood RoofingRoofing 31% 6% 5% The firm with the billboards
Harbor Point Med SpaAesthetics · 3 locations 12% 0% 3% A competitor across town, 3/3 engines
BrightBay Pool CarePool service — renamed at close 8% 0% 2% Its own former brand name
Illustrative data — every name here is fictional. Behind each row sits a full per-company teardown like the published sample: verbatim AI answers, competitor counts, factual errors, and the technical causes.

Read the top and bottom rows together. One company proves the category is winnable; the renamed acquisition at the bottom is losing to its own former brand. That spread — which companies can recover the most demand, and why — is what the baseline is for.

02 — Why this is a PE problem specifically

Roll-ups create AI-visibility failures standalone businesses don't have.

AI assistants recommend businesses they can retrieve, verify, and disambiguate. Acquisitions break exactly those three things — usually silently, usually at close.

BRAND TRANSITIONS

The dead brand still gets recommended

A tuck-in gets renamed, but the engines keep citing the old brand's pages, reviews, and news — so AI recommends a business that no longer exists, or credits its former owner. Demand you paid for routes to a name you retired.

ENTITY CONFUSION

Thirty locations, four legacy brands, no clear entity

Inconsistent names, addresses, and structured data across legacy sites mean the engines can't resolve who you are. When an AI can't verify an entity, it hedges — and names the competitor it can verify instead.

INTEGRATION DEBT

Migrations quietly destroy earned visibility

Site consolidations and re-platforms drop redirects, structured data, and crawler access the acquired company had earned over years. The citations evaporate at close — and nobody notices, because nobody is measuring.

THE OWNERSHIP QUESTION

AI answers "is this company PE-owned?"

Customers increasingly ask it, and the engines answer from news coverage and databases — sometimes wrongly, rarely framed the way you'd frame it. It's a reputational surface across your whole portfolio that nobody is monitoring.

03 — The playbook

One methodology, applied portfolio-wide.

The same measure→fix→prove loop we run for every client — the difference is leverage. The methodology is published, the suites are fixed, and the numbers are comparable across companies and across months. That's what makes it manageable from the ops seat.

01 — BASELINE

Every portco, same yardstick

Each company's buyers' real questions run across the engines, multiple times per prompt. You get the league table; each portco gets its teardown: who wins instead, what AI gets wrong, and the technical causes.

02 — FIX

Capital where demand is recoverable

Scoped remediation for the companies the baseline flags: crawler and firewall repairs, entity and schema cleanup across legacy brands, service-level authority pages, and the citation work engines already trust.

03 — PROVE

A scoreboard the board can read

Monthly re-measurement of the same suites: mention rate, recommendation rate, citation share per company, against named competitors — rolled up quarterly at the portfolio level.

04 — Before the LOI

The diligence scan.

You diligence a target's financials, contracts, and churn. Almost nobody diligences what AI tells the target's customers — or what breaks the day you rebrand it.

A fixed-scope scan, delivered in days, that fits alongside your existing checklist.

  • Demand routing: where AI sends the target's customers today — to them, or to the competitors you'd be buying against.
  • Factual landmines: what the engines state about the business that's wrong, and how bad it is.
  • Inherited debt: crawler blocks, entity confusion, and structured-data gaps the platform absorbs at close.

FIXED SCOPE · PRE-LOI OR PRE-CLOSE · CONFIDENTIAL

05 — Who you'd work with

People who've sat on your side of the table.

GROWTH & PARTNERSHIPS

Jon Polenz

Built and sold his own commercial service business, helped scale the PE-backed parent past $120M through acquisitions, and still serves on its board. Certified M&A Advisor.

ENGINEERING

Cameron Cooper

Two-time acquired founder/CTO. Runs the engineering layer: crawler forensics, rendering, structured data, and entity cleanup across legacy brands.

STRATEGY & CLIENTS

Matt Hawkins

Startup CEO through Y Combinator and acquisition. Runs the measurement program and the scoreboard your ops team sees monthly.

More on the team — including the standard we hold our own site to — on the about page.

No one can guarantee your companies a spot in AI answers. Anyone who promises otherwise is selling something else.

What an honest firm can do is baseline every company against real buyer questions, systematically raise the probability each one is retrieved, understood, and recommended — and publish the scoreboard every month.

Questions

What ops partners ask before they book.

What does a portfolio baseline include?

Every portco gets the standard teardown — real buyer questions across ChatGPT, Claude, and Gemini, run multiple times and scored for mentions, recommendations, and citations, plus factual errors and technical causes. The firm gets the league table. Fixed scope, priced per company.

Can you assess a target before we buy it?

Yes — the diligence scan above is a pre-LOI version of the same measurement: demand routing, factual landmines, and the technical debt the platform inherits at close. Fixed scope, delivered in days, confidential.

Can you guarantee our companies show up in ChatGPT?

No — and anyone who promises otherwise is selling something else. We measure, fix the causes we find, and re-measure monthly so the movement (or lack of it) is visible per company.

How is this different from our portcos' SEO retainers?

SEO optimizes ranked link lists; this optimizes being one of the two or three names an assistant states with confidence. It adds the engineering layer most retainers don't touch — crawler access, rendering, structured data, entity clarity — and a fixed monthly measurement that's comparable across your whole portfolio.

Find out what AI is telling your portfolio's customers.

A 30-minute call. Bring your portfolio list — we'll run real customer questions for two or three of your companies through the engines, live, and show you exactly who gets named.

Book a call

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