How mylight150 Maps Emissions Across Their Supply Chain with Gardenia and AWS

Executive Summary

With Gardenia Sustainability Analytics, myLight 150 tracks their complex global carbon footprint down to the product-level.

mylight150 is a French leader in Europe’s energy transition, helping homeowners produce, optimise and monetise renewable energy. Through innovative technology and services, they enable customers to generate solar power, manage consumption through smart devices, and monetise surplus energy. They operate across France, Spain, Switzerland and Romania, and have connected over 30,000 homes.

The mylight150 team wanted to calculate a comprehensive GHG Inventory down to the component-level. With solar equipment sourced globally from >750 suppliers, they required an automated approach to track emissions at scale. With Gardenia, mylight150 has set up an automated carbon accounting workflow, providing a ‘live’ stream of high- quality data to monitor, manage and advance their sustainability performance.

Enabling Automated, High-Resolution Emissions Data with AWS

To deliver automated, product-level carbon accounting at scale for mylight150, Gardenia Technologies relies on a modern AWS cloud architecture. Each key AWS technology plays a distinct role in enabling granular, efficient, and secure ESG data management:

Data Storage and Security

Amazon S3 and Amazon RDS: All raw and processed emissions data is stored in encrypted Amazon S3 buckets and managed relational databases (Amazon RDS). This robust backbone allows mylight150 to securely retain hundreds of thousands of granular data points—such as every shipment, unit, or product variant—while ensuring reliable performance and data integrity as their supply chain and data volumes grow.
Private Networking and Access Controls: Gardenia uses AWS VPC and IAM (Identity and Access Management) so mylight150’s ESG data is isolated, network traffic is controlled, and access is strictly permissioned. This infrastructure meets requirements for data protection and regulatory compliance across multiple jurisdictions.

Scalable, Real-Time Data Processing

Serverless and Scalable Compute: By orchestrating workflows with AWS Lambda, and running containerized applications on Amazon ECS with Fargate, Gardenia is equipped to automatically scale data extraction, transformation, and emissions calculation processes up or down. This allows real-time data refreshes—so mylight150 can access a live, up-to-date view of their global emissions profile, even as reporting deadlines or product launches require rapid action.
Automated Data Integration: AWS enables direct connection via API or data replication to mylight150’s ERP and other internal systems. This means detailed operational data is extracted, unified, and standardized for emissions analysis, without additional manual effort from the mylight150 team.

Intelligence and Automated Matching

Machine Learning and AI on AWS: Gardenia’s intelligence layer—hosted on AWS—powers automated classification, enrichment, and emission factor matching for every unit and transaction across over 750 suppliers and 30+ product types. Proprietary NLP algorithms (run on AWS infrastructure) assign the right emission factors, whether from international datasets (like EcoInvent, DEFRA, or EXIOBASE) or supplier-specific data, ensuring the highest possible accuracy.
Real-Time Calculation and Scenario Modeling: Automated pipelines on AWS process and aggregate GHG data for both upstream and downstream activities, supporting daily updates and rapid scenario modeling for low-carbon strategies.

High-Resolution Visualization and Automated Reporting

Interactive Dashboards on AWS: The mylight150 team uses dashboards, securely hosted in the AWS cloud, to analyze GHG inventories at any level—by supplier, component, or shipment—and rapidly generate actionable insights. Audit-ready reports are generated via automated workflows and can be customized for compliance, investor, or internal stakeholder needs.
Audit Trails and Documentation: AWS supports detailed logging and transparent process documentation, making it easy to trace emissions data sources, calculation steps, and factor assignments for regulatory or assurance purposes.

A Complex Global Value Chain

Mylight150 had a significant data challenge as it aimed to comprehensively map its Scope 1, 2, and 3 carbon footprint. They required a solution capable of tracing their complex supply chain, highlighting the carbon impact of each individual component, and performing this assessment at scale against a large volume of components procured across the globe.

Sources of Complexity

mylight150’s operations presented several intricacies for accurate emissions calculation:

Volume: Procuring over 180,000 solar panel units annually, and components from over 750 suppliers, across Asia and Europe.
Variety of Products: Offering 30 different solar panel types, each with a unique emissions profile with variance of up to +/300 kgCO2/Wp, which is equivalent to a difference of 180%.
Global Transportation: Shipping solar panels from Asia and Europe, requiring processing of production and shipping locations, unit weights and quantities.
Extensive Upstream and Downstream Emissions Sources: Calculating emissions for 6 categories of upstream and downstream emissions, representing 99% of total emissions, requiring mapping of activities from purchasing of goods to their disposal.
Complex Energy Provider Vertical: Subsidiary operating as an Energy Provider required market and location-based emission calculations for various sources including grid, nuclear, and solar.

Data Requirements

To calculate a comprehensive inventory, Gardenia needed:

Data Points: to extract 760,000+ data points, primarily from mylight150’s ERP system.
Emissions Factors: to apply 445 Emission Factors (EFs), including product-specific EFs sourced from suppliers.
Transportation API: Use of a proprietary API to automatically calculate route distances, for tens of thousands of start/end location combinations across several modes of transport.

Automated Data Extraction: Unlocking Insights in Client Data

Gardenia connected to mylight150’s ERP system, allowing for the matching of line-item data to emission factors to calculate emissions from direct and indirect sources.

Supplemental data was also provided to enable unit-based calculations. mylight150 chose to partner with Gardenia because of its ability to set up emissions tracking without increasing the data collection or workflow burden, through automated data extraction, processing and enrichment capabilities.

Enabling Unit-Based Calculations at Scale

Unit-based calculations apply emission factors that are specific to the unit being measured, taking into account factors like size, weight, materials, production processes, and geographic location. This method provides a more accurate picture of a product's emissions profile compared to spend-based calculations, which estimate emissions based on the monetary value of goods and services purchased.

The Data Requirements

Implementing unit-based calculations at scale can be challenging due to the need for high-quality data for each unit. The breadth and depth of data required can be time- consuming and resource-intensive to collect and manage without automation. Gardenia’s built-in 'Data Factory' enables automated data collection from all sources.

Connectors integrate with Systems of Record using native methods, ensuring audited data retrieval without manual effort. The transformation engine then unifies data into a standardised format, ready for matching with emission factors.

Emission Factors

Gardenia’s proprietary emission factor matching algorithm, driven by NLP, automatically matches each data point to the right emission factor, sourced from internationally recognised sources like EcoInvent, DEFRA, EXIOBASE, EPA, and BEIS. Our automatic process identifies the most suitable EF for all the data, with safeguards to sense-check matches. Our process prioritises matching to product-specific emission factors, accounting for differences in manufacturing processes and energy mixes across regions.

Results: Achieving a Complete Product Carbon Footprint

By partnering with Gardenia, mylight150 obtained a full emissions inventory and a detailed view of each product from cradle to grave. The mylight150 team accesses a set of dashboards to explore their emissions profile, assess reduction strategies, and generate reports. Live visualisations of emissions across the value chain allow teams to respond to emerging trends based on supplier information. One such example where live views help customers reduce scope 3 emissions is through Gardenia’s automated process to calculate shipping distances. With an API call, emissions can be calculated based on a proposed shipping route, using distance and transportation mode.

Next Steps

Track Sustainability Performance

Automated data integration from all sources with daily data refreshes
Set of dashboards to explore and track emissions across operations

Guide and Prioritise Decarbonisation Efforts

Product and Supplier-level emissions insights
Reduction Strategy Scenario Modelling dashboard

Jumpstart Global Regulatory Compliance

Generative AI-powered report preparation tool
Audit-ready methodology documentation

Powering Efficient ESG Reporting with Report GenAI

Through the first stage of our partnership with mylight150, their team has achieved a complete GHG inventory and are well prepared for reporting with various regulatory and voluntary frameworks. The next step will be setting up an efficient reporting workflow using Gardenia’s Report GenAI.

About Report GenAI

Gardenia’s Report GenAI tool can answer sustainability questions based on available organisational data, such as GHG Inventories or company policy documents. The tool can batch fill and do a ‘first-run’ at all questions for a selected report; then users can iterate answers with the help of AI to finalise the report. The tool can be configured to a wide range of reports, including major regulatory and voluntary reports (e.g. CSRD, CDP, PRI) as well as custom reports to investors, suppliers, and other stakeholders. If it is a survey with conditional logic and no full print-out of questions is available, the agent can be prompted with each question and used to iterate your answer.

Report GenAI has enabled our clients to prepare their ESG reports up to ~75% faster.

Preparing Reports for EcoVadis and CSRD

The mylight150 team is already reporting with EcoVadis, and they plan to use Report GenAI to complete their next round of reporting. They also plan to expand their reporting to other frameworks, including the Corporate Sustainability Reporting Directive (CSRD). We look forward to continued work with the mylight150 team to automate the collection and reporting of high quality ESG data, and to support them in their mission to empower homeowners to lead the way in the solar energy transition.

How mylight150 Maps Emissions Across Their Global Supply Chain with Gardenia

About The Client

Key Results

Executive Summary

Challenge

Solution

Results

Comments from The mylight150 Team