Our scientific expertise

Fairglow’s algorithmic engine generates accurate emission factors for cosmetic ingredients, even when no reliable data exists in current databases. Validated on 130 INCI in collaboration with a major French research lab, the system demonstrated strong reliability, with most results falling within the “Good” accuracy range (<20% deviation). When discrepancies appeared, they were driven by real-world uncertainties such as transport assumptions, process variability, or coproduct allocation.

By minimizing the need for proxies, Fairglow provides the cosmetics industry with a precise, scalable solution for conducting Life Cycle Assessments. In a sector responsible for 1.5% of global carbon emissions, Fairglow fills a critical data gap—empowering brands and suppliers to measure, compare, and reduce the environmental impact of their ingredients. As the platform evolves, it will integrate broader processes and continuously refine its boundaries to deliver even greater accuracy and versatility.