The independent AI intelligence layer for golf equipment decisions.
GPIP is a software and data company. Our recommendations are grounded in proprietary performance data we manufacture ourselves in the GPIP Performance Lab. We don’t scrape it, we don’t license it, and no manufacturer supplies it.
What This Is — And What It Is Not
A software and data company. Not a fitting studio.
GPIP is
- An AI platform that turns a golfer’s data into brand-agnostic equipment recommendations
- A proprietary data asset, manufactured through controlled testing
- Independent of every manufacturer
- Built to be licensed by retailers, facilities, and the industry
GPIP is not
- A club fitting shop or retail storefront
- An aggregator of public specs and reviews
- A sales channel for any brand
- A single-location service business
The Performance Lab is private R&D infrastructure. It exists to manufacture and validate the data. Most golfers who use GPIP will never set foot in it.
The Problem
Most golfers buy equipment with almost no objective guidance.
Hundreds of head options. Thousands of shaft combinations. Brand-specific fitting environments that can’t recommend a competitor’s product. Golfers spend thousands of dollars without knowing whether their equipment actually fits their swing, their launch conditions, or their goals.
The Market
A large market with no independent source of truth.
- active U.S. golfers
- 48.1Mactive U.S. golfers
- U.S. golf equipment market
- $2.7BU.S. golf equipment market
- core golfers driving 90%+ of equipment spend
- 13.1Mcore golfers driving 90%+ of equipment spend
How It Works
From a golfer’s data to a recommendation they can trust.
- 01
Intake
A guided assessment for casual golfers; direct data upload from TrackMan, Foresight, FlightScope, and Rapsodo for advanced users.
- 02
Intelligence
The recommendation engine evaluates clubhead design, stock shafts, and no-upcharge options across every major manufacturer, grounded in Lab-validated performance data.
- 03
Confidence
Every recommendation carries a confidence score, with human review and concierge advisory protecting trust while the engine matures.
- 04
Outcome loop
Results feed back into the platform, so the data asset compounds with every golfer and every test.
Recommended Stock Configuration
IllustrativeLow-spin driver head
Stock mid-launch shaft — Stiff, no-upcharge · 10.5°, stock — lowers spin and raises launch into the optimal window versus the current driver, at no added cost.
| Metric | Current | Recommended |
|---|---|---|
| Carry | 228 yds | 241 yds |
| Spin | 3,150 rpm | 2,650 rpm |
| Launch | 11.2° | 12.8° |
Ranked Options · Confidence
Confidence reflects how closely the golfer’s profile matches Lab-validated test data. Lower-confidence results route to human review.
The Moat
Manufactured, not sourced.
Anyone can scrape specifications and reviews. GPIP generates its own ground-truth performance data through a controlled testing matrix in the GPIP Performance Lab, across brands, under one consistent protocol. It is a data asset competitors cannot shortcut, and it is the reason GPIP’s recommendations can be independent: the evidence belongs to us.
Enterprise
Intelligence the industry can license.
Retailers and facilities
Brand-agnostic recommendation intelligence for retail floors, simulator venues, and golf facilities.
GPIP Validation Lab
Independent testing and validation services for manufacturers, media, and marketing firms.
GPIP Certified
A credential and licensing program for professionals and organizations delivering GPIP-backed recommendations.
Founder Advantage
Built from inside the industry it is designed to fix.
GPIP’s founder brings 25+ years of club fitting, equipment optimization, retail golf operations, and OEM product work. A former PGA of America member, the founder built GPIP to be independent by design: no brand affiliation, no sales incentive, and no institutional methodology to defend. GPIP isn’t an AI wrapper on a fitting shop. It is an intelligence platform built by someone who has done the fitting, run the retail floor, and sat across the table from the manufacturers.
Roadmap
A 12-month build.
Foundation
Platform architecture and the initial recommendation engine.
Performance Lab
Lab built and the stock / no-upcharge testing matrix executed. Lab operational by Month 6.
Validation
Beta validates recommendation accuracy and willingness to pay; enterprise conversations begin.
Scale
Recurring engagement proven; first enterprise pilots underway.
Contact
Investors, partners, and enterprise inquiries.
Tell us who you are and what you’d like to see. We respond to every qualified request personally.