We are a team of fashion supply chain experts, environmental specialists and tech wizards.

Our vision

Enable brands to measure the impact of all their products at all times, in a transparent, trustworthy and easy manner.

Environmental indicators must become the common language of the product, sourcing and marketing departments.

We developed different solutions that allow brands & suppliers to measure and accelerate reduction of their impact on people and the planet.

We come from the industry, we worked for fashion brands and their production partners.

We know that no one has time and everybody is under constant stress. That is why our solutions are seamless and intuitive, in other words they do the work for you. If you share our vision or would like to learn more, contact us.

Leading Team

Meiling Shi

CSO
Environmental

Renewable energy market & water depletion expert, Postgrad of Duke university

Tal Shogol

CEO
Management

16 years of experience in senior executive positions across different industries

Atnyel Guedj

CPO
Fashion Industry

20 years of experience in fashion supply chains and production

Carlo Casorzo

Tech Lead

Complex data models specialist with 10 years experience managing dev teams

Advisory Board

Mark Harrop

CEO of Whichplm
ex: Gerber, PTC

Michael Sadowski

Senior Consultant at WRI
ex: PWC, Nike

Stephane Popescu

Co-founder and CEO at COSE361
ex: Groupe Beaumanoir

Krishna Manda

VP Sustainability at Lenzing Group & Board of Directors at the SAC
ex: Policy Hub

Ivo Mersiowsky

Director at Quantis International
ex: Dekra

Partners

Methodology

01
Product
Data Stream

Data from the BOM, Tech-pack, Line sheet, etc.

Facility
Data Stream

Existing data from transaction and scope certificates, FEM, ZDHC, etc

02
Data
Validation

Measuring the accuracy rate for each data point to ensure that only credible validated data is used

03
Data
Gap Analysis

Studying existing data (unvalidated + unutilized), identifying gaps. Normalize data to SKU level.

04
Automated Data Completion

Completion of data using a multiple source approach (primary & secondary data)

Data
Gathering

Automated data collection directly from the supply chain (tiers 1-4)

05
Impact
Indicators

Calculating & benchmarking environmental indicators such as GHG, water depletion, land use etc, according to the Life Cycle Assessment methodology

See the solutions

How do we ensure data credibility

The Made2flow solutions are based on our proprietary machine learning based technology

R&D

AI-Platform, Matching Algorithms and workflow control have been supported by the Land of Brandenburg / ILB within the Program BIG FuE: "Development of an AI-based control of the workflow engine"

Methodology

01
Product
Data Stream

Data from the BOM, Tech-pack, Line sheet, etc.

Facility
Data Stream

Existing data from transaction and scope certificates, FEM, ZDHC, etc

02
Data
Validation

Measuring the accuracy rate for each data point to ensure that only credible validated data is used

03
Data
Gap Analysis

Studying existing data (unvalidated + unutilized), identifying gaps. Normalize data to SKU level.

04
Automated Data Completion

Completion of data using a multiple source approach (primary & secondary data)

Data
Gathering

Automated data collection directly from the supply chain (tiers 1-4)

05
Impact
Indicators

Calculating & benchmarking environmental indicators such as GHG, water depletion, land use etc, according to the Life Cycle Assessment methodology

Book a demo

technology

Automated Traceability

Automated Data Gathering

Automated Data Validation

Automated Data Completion

Automated Impact Calculation

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