Koch-Chemie Gentle Snow Foam
$30.99
pH-neutral snow foam shampoo that delivers dense pre-wash foam cleaning while safely maintaining wax, sealant, and ceramic-coated vehicles
10 in stock
Koch-Chemie Gentle Snow Foam is a pH-neutral car wash foam designed for safe pre-wash cleaning and contact washing. This high-foaming automotive shampoo removes dirt while protecting waxes, sealants, and ceramic coatings. The formula produces dense foam that softens contamination before hand washing. It helps reduce swirl marks and paint damage during routine maintenance washes.
The advanced surfactant system creates stable, long-dwelling foam coverage across painted surfaces. The pH-neutral formula cleans effectively without stripping existing protection layers. Gentle Snow Foam works through encapsulation technology that loosens road film, dust, and light grime. The foam rinses clean with minimal residue and supports efficient wash workflows. Users can adjust dilution ratios to increase cleaning power or enhance foam thickness depending on equipment and conditions.
This snow foam works with foam cannons, foam guns, pump sprayers, and traditional bucket washing methods. Professional detailers use it for maintenance washes, pre-wash stages, and coated vehicle care. Automotive dealerships, fleet operators, ceramic coating installers, and enthusiast detailers rely on it for safe exterior cleaning. The shampoo performs well on paint, glass, plastics, trim, wheels, and wrapped vehicles. It suits commercial detailing environments where consistency and surface safety matter.
Gentle Snow Foam improves wash efficiency by reducing mechanical contact during cleaning. The thick foam layer lifts contamination before agitation begins. This process lowers the risk of micro-marring and maintains high-gloss finishes longer. Regular use supports easier drying, improved coating longevity, and professional wash results. Shop more professional shampoos in our Wash & Prep category. Product information aligns with guidance from Koch-Chemie manufacturer recommendations.




