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CarbonMatch

AI-Powered Emission Factor Matching for Product Carbon Footprints

Match Your Bill of Materials to Verified Emission Data

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Try it with a sample BOM (10 components)

arbonMatch software for automated emission factor matching and carbon footprint component management, displayed on a laptop screen.

CarbonMatch is an AI-driven emission factor matching tool, built upon a collaboration with the German Research Center for Artificial Intelligence (DFKI), that automatically connects your Bill of Materials (BOM) components to trusted lifecycle assessment (LCA) datasets like Ecoinvent – enabling fast, consistent, and auditable Product Carbon Footprint (PCF) calculations.

 

The Problem CarbonMatch Solves

Accurate PCF calculation requires reliable emissions data for every component.
While supplier PCFs are improving, many components still lack primary data.
As a result, sustainability teams must manually match BOM components to secondary LCA datasets
– a slow, inconsistent, and unscalable process.

Manual searching through environmental datasets for each BOM component is time-consuming and labor-intensive
Manual dataset search requires significant effort per component

Emission factor matching accuracy varies based on individual knowledge and experience with environmental databases
Matching quality depends on individual expertise

Carbon footprint calculations produce inconsistent results when different teams and products use varying matching approaches
Results vary across teams and products

Identical components appearing across multiple bills of materials require repeated manual emission factor matching
Repeated work for identical components across BOMs

 

How CarbonMatch Works

  1. Upload Your BOM
    Upload your Bill of Materials (XLSX). CarbonMatch extracts component IDs, names, and -if available- descriptions and material data.

  2. AI Context Enrichment
    The AI builds a clear component understanding by combining your BOM data with automated web research (e.g. technical datasheets and specifications), generating a robust semantic component description.

  3. Emission Factor Matching
    CarbonMatch performs a AI-based similarity search across verified LCA databases such as Ecoinvent and returns up to 5 ranked dataset matches per component.

     

  4. Review, Confirm, or Rematch
    Review suggestions, compare alternatives, or add missing information. If needed, trigger a rematch using your additional input to improve accuracy.

  5. Reuse & Calculate
    Confirmed matches are stored in a reusable component library. Existing components are matched automatically in future BOMs, enabling fast, consistent PCF calculation and audit-ready reporting.

Core Features

AI-driven matching of BOM components to environmental datasets
AI-Driven Emission Factor Matching

 

Semantic matching beyond keywords for more accurate results

Confidence score indicating reliability of dataset matches
Confidence & Transparency Scores

Understand match quality at a glance

Central library for reusing matched components across products
Reusable Match Library

No repeated matching work across products

Global and regional emission factor datasets for accurate supply chain carbon footprint calculations
Global & Regional Emission Factors

Choose the dataset that fits your supply chain geography

Detailed information describing each environmental dataset
Dataset Detail Panels

Clear context for every match

Direct link to the original environmental data source
Direct Source Links for Auditability

Trace back all matches to original emission factor sources

 

Who CarbonMatch Is For

Manufacturing & Consumer Goods

Scale carbon matching across complex assemblies.

Automotive & Mobility

Handle complex, multi-material component structures at scale.

Fashion & Textiles

Match fabrics, dyes, coatings, and trims to LCA datasets reliably.

Why Teams Choose CarbonMatch

  • Reduce emission factor matching from weeks to hours

  • Ensure consistent PCF methodology across all products

  • Build long-term matching knowledge within your organization

  • Create audit-ready, traceable PCF inputs

CarbonMatch product carbon footprint management dashboard displaying total products, components, and CO₂e emissions with interactive donut charts for emissions by product and by component.
CarbonMatch emission factor matching interface suggesting database matches for a product component, showing match confidence scores, PCF values, and geographic scope with step-by-step matching progress.
Product list view in CarbonMatch software showing products with weight, production location, supply chain emissions in kg CO₂e, and number of unique components per product.
Component detail view in CarbonMatch showing a calculated assembly with PCF calculation details, subcomponent breakdown with individual carbon footprint contributions, and linked product usage.
Component library in CarbonMatch carbon footprint software listing components with weight, PCF values, production location, linked products, and emission factor matching status.
Product detail view in CarbonMatch PCF software showing product information, total product carbon footprint, and a component list with individual PCF values, quantities, and matching status.

FAQ

What is emission factor matching?

Emission factor matching is the process of connecting components from a Bill of Material (BOM) to verified environmental datasets in lifecycle assessment (LCA) databases like Ecoinvent. This is necessary when primary supplier data is not available and teams need to rely on secondary data for their Product Carbon Footprint (PCF) calculations – a process that is traditionally done manually, making it slow, inconsistent, and hard to scale.

Which LCA databases does CarbonMatch support?

CarbonMatch currently supports verified LCA databases including Ecoinvent, with the ability to select emission factors based on global and regional geography to match your specific supply chain. Additional database integrations are continuously being expanded.

How accurate is AI-based emission factor matching?

CarbonMatch uses semantic AI matching developed in collaboration with the German Research Center for Artificial Intelligence (DFKI), going beyond simple keyword matching. Each suggestion includes a confidence and transparency score so you can evaluate match quality at a glance and rematch with additional input if needed.

Can CarbonMatch handle multi-material assemblies?

Yes. CarbonMatch is built for complex product structures across industries like automotive, manufacturing, consumer goods, and fashion. It processes entire BOMs at once and supports multilevel BOMs with subcomponent breakdowns.

How does CarbonMatch differ from manual LCA matching?

Manual emission factor matching requires deep material and production process expertise, produces inconsistent results across teams, and means repeated work for identical components. CarbonMatch automates this process using AI, stores confirmed matches in a reusable component library, and reduces matching time from weeks to hours – while ensuring audit-ready, traceable results.

Ready to Automate Emission Factor Matching?

Upload your BOM and see AI-powered matching in action.

 

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