The challenge
Beauty is a market full of marketing claims and very little objective signal. Shoppers who care about what they put on their skin are left decoding Latin ingredient names alone, and the apps that promise help often score products through opaque rules that no one can defend.
The brief was a scanner people could actually trust: grounded in a real ingredient database, transparent about why a product scores the way it does, and free at the point of use.
What we built
We built GlowLens on Next.js through our custom SaaS development practice, with the analysis engine scoped by our machine learning and AI integration consulting teams. A curated ingredient database sits under a deterministic scoring core, so identical inputs always yield the same grade, while AI handles the messy job of reading and normalising label text.
The database draws on recognised references such as EU SCCS opinions and CIR reports, and the whole product ships in four locales with a Swiss, FADP-aligned privacy posture.
The result
GlowLens launched as a free, four-language scanner that turns an ingredient list into a clear, explainable grade - reasoning the team can defend to a sceptical shopper or a brand owner.
Try the live scanner at GlowLens.
Stack highlights
Scope
Design, engineering and launch - owned end to end by AETHER Digital.