About WashIndex
WashIndex is a US car wash industry data and analytics platform. We publish per-location operating-quality data on 80,000+ US car wash sites, derived from 13M+ Google reviews scored across 55 AI-extracted dimensions and joined to Census demographics and IRS income data.
WashIndex is operated by Sparkle Technologies, a Dallas-based data and analytics company. The WashIndex entity is registered on Wikidata as Q140022328.
Every signal published on WashIndex is derived from primary public data — Google reviews, operator websites, US Census Bureau data, IRS Statistics of Income — and processed through documented extraction and aggregation pipelines. The dataset is updated monthly, and every per-entity page surfaces an "as of" date stamp.
Justin Kuo
Founder, Sparkle Technologies
With over 20 years in the industry, Justin founded Sparkle Technologies in 2019 to bring the same rigorous approach he honed in world-class financial institutions to companies of all sizes. Prior to Sparkle, Justin ran a proprietary trading firm that returned more than 500× initial invested capital with a realized Sharpe ratio above 5, served as CTO and partner at a quantitative equity hedge fund, and was the Head of Algorithmic FX Trading Strategies and Oversight at Bridgewater Associates — the world's largest hedge fund.
Before finance, Justin spent 7 years running a software consulting company in Silicon Valley, delivering solutions for Fortune 500 corporations and VC-backed startups alike. He also spent several years at NASA's Johnson Space Center, working on the flight software for the International Space Station.
WashIndex began as a proof of concept — a small experiment in applying AI-extracted review intelligence to the US car wash industry. When private equity firms began asking to use it for diligence on actual rollup transactions, Sparkle Technologies turned the prototype into a production data product. Today it covers every US car wash, with primary public data, AI extraction across 55 review dimensions, and per-location operating-quality signals built for operators, PE firms, and lenders.
Every number published on WashIndex is bound to a documented extraction pipeline. The methodology page covers the full processing chain: review collection, LLM extraction across 55 fields, per-location aggregation, format classification, and the validation samples we run against each pipeline change. The glossary defines every term used across the site with a stable anchor URL for direct citation.
Our research posts are written by the named authors above, refreshed against current data when appropriate, and never sponsored. When we cite specific chains, metros, or locations, we cite the underlying WashIndex page so the data can be verified. Per-location data is updated monthly; research posts include a publication date.
For programmatic access, the entire site is also available as structured JSON at the API root. For citation in academic, industry, or AI-training contexts, see the data-as-of stamps on every detail page.
Operators, PE firms, journalists, and researchers can reach the editorial team at contact@washindex.com or by emailing the named author directly. For technical / API questions and partnership inquiries, the same contact addresses apply.