Product LCA Software for Fashion

Carbonfact uses a three-step approach to fill data gaps accurately and transparently. 

1. We rely on Carbonfact heuristics — smart estimates based on a proprietary database of more than 50 million LCAs built from our work with over 200 fashion brands. These estimates are far more precise than generic industry averages because they’re based on real, anonymized data from similar products. For example, for the yarn size (Dtex) heuristic for pants, Carbonfact analyzed 8,894 data points specifically for pants.If Dtex is missing, Carbonfact can automatically fill that gap using actual values from comparable products in our database.
2. You can easily fill data gaps using your own team’s knowledge — even if it’s not captured in your PLM or other internal systems. For instance, if you know that all your T-shirts are knitted but that information isn’t recorded in your product database, you can simply set that rule in the platform and apply it across your range. You can also turn supplier information — like answers from energy surveys — into enrichment rules that apply automatically across factories.
3. Finally, Carbonfact also uses trusted external databases such as Ecoinvent, EF 3.1, and Ademe.
4. And when none of those provide the needed data, our in-house science team can create custom emission factors based on the latest scientific research. 

1. We collect the data you already have.
   You don’t need to fill out templates. We connect directly to your systems (like PLM or ERP), or simply use Excel or CSV exports. Even if your data isn’t perfect, that’s okay — we start with what’s available.
2. We calculate product-level LCAs at scale.
   Carbonfact automatically calculates cradle-to-grave Life Cycle Assessments (LCAs) for 100% of your product catalog — including variations in size, color, material, and supplier. Calculations are aligned with ISO 14040 and the EU PEFCR, and we support all 16 environmental indicators, not just carbon.
3. We fill in data gaps intelligently.
   Missing data? No problem. We use fashion-specific heuristics (based on 50M+ real product LCAs), your own brand knowledge (even if it’s not stored in your systems), trusted databases like Ecoinvent and EF 3.1, and our in-house science team to fill gaps transparently.
4. We give you instant insights.
   You get dashboards showing emissions by material, supplier, factory, product category, and more. You can filter by brand, region, season — whatever makes sense for you.
5. You can simulate product changes.
   Want to test the impact of switching from conventional to recycled cotton? Or changing dyeing techniques or supplier location? Our eco-design simulation tools let you run “what if” scenarios in seconds.
6.  We support your compliance and reporting. Carbonfact is audit-ready and peer-reviewed. You can automatically generate reports for CSRD, French Eco-Score, DPP, CDP, SBTi, and more — without manually wrangling data. 

Yes! After working with 200+ fashion and footwear brands, there is nothing that we haven’t seen. Whether you’re managing data across 10 different Excel sheets or have a sophisticated ERP and data warehouse setup, we are confident in our ability to ingest your data.

Before we start working together, we will ask you for a small sample of your data, and our data team will have a look to be 100% sure.

Once we start working together, we clean your data and optionally build a custom connector that automatically imports data from your systems.

Getting started with Carbonfact is easier than you might expect. To begin calculating LCAs across your product catalog, we only need a few key data points.

In Phase 1 you’ll need to provide your product’s unique identifier (SKU), the product category,  and the composition as listed on the care label — like “80% cotton, 20% polyester.” We also need to know how many units were ordered and the dates of those orders. That’s all it takes to establish a solid foundation.

If possible, we also recommend including the product weight (excluding packaging). While not required, this helps improve accuracy from day one.

In Phase 2, we improve accuracy. We incorporate additional data such as bills of materials with component weights, factory locations and energy mixes, transportation methods, and manufacturing process details like dyeing or weaving.

Finally, in Phase 3, we reach advanced precision. Here we can include supplier-specific energy data, loss rates at various production stages, and even primary data from tier 2 or tier 3 suppliers.

This step-by-step approach helps you move fast, get results early, and improve over time — without needing to clean up everything upfront.

Carbonfact can integrate with various data sources, including ERPs, PLMs, traceability solutions, data warehouses (e.g., Snowflake, BigQuery), and structured files (.csv, .xls). The platform is flexible and can adapt to different data formats and systems, as long as the format is consistent and machine-readable.