Fairglow Raises €3M for Low-Carbon Beauty Supply Chain Tech
The cosmetics industry can’t cut emissions it hasn’t learned to count.
The cosmetics industry is responsible for roughly 1.5% of global CO2 emissions, a figure that approaches the 2 to 2.5% attributed to commercial aviation. The difference is that airlines have spent decades building the infrastructure to measure and report their footprint. Beauty brands, for the most part, have not. Fairglow, a Paris-based startup founded in 2023, just closed a €3 million seed round on the premise that the sector’s data problem is also its biggest commercial opportunity.
The round was co-led by Ternel, a Paris venture capital firm whose €120 million fund backs climate and regenerative technology, and SWEN Capital Partners. Kima Ventures, the prolific seed vehicle co-founded by Xavier Niel, also participated. The capital will fund an expansion of the company’s emissions database, AI-driven data modelling, and a push into new European markets ahead of incoming regulatory deadlines.
Fairglow was started by three co-founders with overlapping but distinct skill sets. Quentin Carayon, the CEO, is an ESCP Europe graduate who spent over a decade in tech and environmental companies before deciding the cosmetics sector was being chronically underserved by existing carbon accounting tools. Evan Peters, the Chief Product Officer, came from a data science and environmental regulation background spanning the UK and the US. Jason Melbourne, the Chief Data Officer, built his career in data engineering and predictive modelling. The company grew out of a shared frustration: the beauty industry talks constantly about sustainability but lacks the basic measurement infrastructure to back any of it up.
That frustration is grounded in a structural reality. More than 90% of the sector’s emissions sit in Scope 3, buried deep in supply chains across raw material sourcing, ingredient processing, packaging and distribution. A single cosmetic formula averages 21 ingredients, pulled from a fragmented network of suppliers whose ability to provide environmental data ranges from sophisticated to nonexistent. The industry uses around 30,000 distinct ingredients globally, and until recently, the vast majority had no modelled emission factors at all. Traditional life cycle assessment tools, built for heavy industry, were never designed to handle this kind of complexity at the product level. Conducting a single product-level LCA using conventional consultancy methods can take weeks and cost thousands of euros, making portfolio-wide analysis a practical impossibility for all but the largest players.
Fairglow’s pitch is that its SaaS platform can close that gap, and the way it works is more straightforward than the underlying data science might suggest. A brand or contract manufacturer connects its formulation and packaging data. The platform ingests that information and cross-references every ingredient and material against a proprietary database of more than 30,000 emission factors built specifically for the cosmetics sector. Unlike generic carbon databases, these factors distinguish between production methods and geographical origin, so a shea butter sourced from West Africa and one synthesized in a Dutch lab are not treated as interchangeable. Within hours, the platform returns a full environmental profile for each product in the portfolio, scored across more than 150 criteria and six dimensions of life cycle assessment. The output is not an estimate or an industry average. It is a product-level carbon footprint tied to that brand’s actual supply chain.
The more interesting technical claim, and the one investors appear to be underwriting, is around what happens when the data is incomplete. Suppliers in cosmetics vary enormously in data maturity. Some can provide detailed emissions breakdowns; many cannot. Fairglow uses AI-based reconstruction and conditional interpolation algorithms to fill those gaps, producing audit-ready results even when raw supplier data is patchy. The company says this is what allows it to process thousands of LCAs in hours rather than the weeks a traditional consultancy engagement would require. Its methodology has been certified by KPMG and Bureau Veritas, which lends credibility, though it remains to be seen how regulators will treat AI-reconstructed data as enforcement of the EU’s Green Claims Directive and Digital Product Passport requirements picks up in practice.
Where the platform becomes most useful is not in the measurement itself but in what comes after it. Once a portfolio is mapped, Fairglow surfaces the emission hotspots, showing a formulator exactly which ingredients, packaging components or manufacturing steps are driving the biggest share of a product’s footprint. Its eco-design simulation tool then lets that formulator ask “what if”: swap a synthetic emulsifier for a plant-derived alternative, switch from virgin glass to recycled PET, shift a supplier from one region to another, and see the projected carbon impact of each change before a single production order is placed. For a product development team choosing between three packaging options or two fragrance compounds, that is a tangible working tool, not a compliance checkbox. By aggregating these results across its growing client base, Fairglow is also building sector-wide benchmarks, a dataset that becomes more valuable the more companies use the platform.
Early traction is notable for a company at the seed stage. By the end of 2025, Fairglow had analysed more than 10,800 products covering over 543 million manufactured units, with the aggregate footprint crossing one million tonnes of CO2 equivalents. A partnership with ANJAC Health and Beauty, one of Europe’s largest contract development and manufacturing organizations, saw Fairglow become the first environmental measurement platform embedded directly into a major CDMO’s operations. That collaboration expanded from a 2024 pilot to more than 2,700 SKUs in 2025, with the company claiming it can onboard a new client and deliver initial results within a month, requiring less than an hour of user training.
None of this means the path forward is uncomplicated. Horizontal players like Watershed, Sphera and Quantis are all active in adjacent markets. Fairglow’s bet on vertical specialization gives it depth but limits its addressable market in the near term. Scaling a database that depends on primary supplier data also means navigating thousands of relationships with ingredient and packaging providers, many of whom have little incentive to share proprietary information.
The regulatory tailwind, however, is real. The EU’s Corporate Sustainability Reporting Directive is already in force, the Green Claims Directive will tighten the rules around unsubstantiated environmental marketing, and the Digital Product Passport framework is approaching. Fairglow is positioning itself to help brands meet all three. Juliette Huot, principal at lead investor Ternel, framed the investment around that convergence, noting that the companies best placed to win will be those turning environmental performance into a strategic advantage rather than treating compliance as a cost to be minimized. The immediate roadmap reflects that bet: deepen the emissions database, scale the AI reconstruction engine, and build out DPP infrastructure before Brussels’s deadlines arrive.
Whether the beauty industry’s sustainability moment produces lasting structural change or fades into another cycle of well-meaning commitments remains an open question. The startups that build the measurement layer stand to benefit regardless of how sincere the industry’s green ambitions turn out to be.
