Tamats vs Good Face Project

The nearest neighbour in category: cloud formulation software built around a proprietary ingredient ontology, sold across the whole value chain.

What Good Face Project says it does

Good Face describes itself as “the software for cosmetic product innovators, powered by AI and the industry's best data”.
Four capability areas are named on the home page: Formulation, Regulatory Compliance, Claim Validation and Predictive Modeling.
It is sold to four audiences: formulators and manufacturers, ingredient suppliers, brands, and retailers.
Named features include a private raw materials catalog, a partner portal described as protecting formula IP, and a public trade name library.
The data claim is “the largest proprietary ontology of cosmetic ingredients graded across dimensions of safety, sustainability, and efficacy”.
Published customer testimonials include regulatory and R&D staff at e.l.f. Beauty, Odele Beauty, Sula Labs, Salvona Technologies and Federal Package.

Read from thegoodfaceproject.com on 2026-08-03

Pricing is not published — the call to action is “Book a Demo”.
Their site does not enumerate which regulatory markets or retailer clean standards are screened, so we do not characterise that coverage.
The ingredient ontology is described as proprietary and graded, but the grading methodology and its sources are not published, so we cannot compare it to a citation-per-rule corpus.

Ingredient data model: TamatsA compiled rule set where each entry names the regulation or retailer standard it came from, plus a CosIng-derived ingredient reference. You can read the citation before you trust the finding.; Good Face ProjectA proprietary ontology grading ingredients on safety, sustainability and efficacy. Graded scores answer a different question than “which regulation says so”.
Retailer clean standards: Tamats13 retailer programmes — Clean at Sephora, Ulta, Target, Credo, Whole Foods, Walmart and others — checked in the same pass as the legal rules, and browsable publicly.; Good Face ProjectRetailers are named as a customer segment; the standards screened are not enumerated publicly.
Evaluating it: TamatsFree tier, published pricing, and an ungated regulatory index you can check before talking to anyone.; Good Face ProjectBook a demo.

Choose Good Face Project when

You want an established platform with named enterprise beauty customers and a supplier/partner network already on it — that network effect is real and we do not have it.
Claim validation and predictive modelling on graded ingredient attributes is the specific job you are buying for.

Choose Tamats when

You want to see the regulation behind a finding rather than a graded score, and you want that visible before you buy.
Retailer clean-standard screening is the thing blocking your launch and you want the list you are being screened against to be public.