A publicly circulating comparison guide made by Carbonfact (October 2025) includes several inaccurate statements about Vaayu’s features, data quality, methodology, and customer experience.
This page clarifies those points using the feature terminology from the comparison document, ensuring retail businesses, marketplaces, and sustainability teams can make informed, evidence-based decisions.
Vaayu is an AI-powered climate technology platform built specifically for retail. We have provided support to more than 100 global partners, including Klarna, Vestiaire Collective, On, Missoma, Asket, and Triumph, with accurate, scalable product-level impact calculations and decarbonization insights.
Below, you’ll find clear corrections to claims made about Vaayu and correct information on its capabilities.
AI-powered reduction modeling via our proprietary impact calculation engine and database
One of retail’s best LCA datasets, including fashion-, textile-, process-, and region-specific emission factors
Automates Scope 1, 2, and 3 inventories aligned with GHG Protocol Corporate, product, and value chain standards
Scalable product-level LCAs across full catalogs (hundreds of millions of calculations)
Digital Product Passports already live with brands
Optimized modeling based on primary data and supplier data exchange
Where primary data cannot be provided, the system applies data gap filling with and industry-leading secondary data
SBTi-aligned decarbonization modeling and scenario planning
Alignment with GHG Protocol, and support for CDP, FLAG, PEF, and other frameworks
SOC 2 security and TÜV Rheinland-certified Corporate Carbon Footprint methodology
Hotspot analysis across material, supplier, process, region, transport, and category.
Provides data in any way clients require
A range of data ingestion APIs for customers and suppliers and flexible, customizable CSV/XLSX import templates
Exposes emission factor provenance, dataset names, geographic scope, versioning, and methodological notes directly in the platform
Dataset versioning, calculation histories, and full audit trails for platform changes
Incorrect claim: Vaayu does not support AI-assisted ingestion.
Fact: Vaayu uses AI to model reductions, assess improvement potential, compare performance against benchmarks and assist customers with ingestion, while maintaining strict security and protection of customer data from risk consistent with our SOC 2 certification.
Incorrect claim: Vaayu does not provide fashion-specific emission factors.
Fact: Vaayu maintains a rich fashion-specific and retail-specific emission factor library, comprising third-party and custom modeled datasets covering fibres, fabrics, trims, processes, packaging, logistics, and more.
Incorrect claim: Vaayu cannot model bespoke emission factors or patented processes.
Fact: Vaayu routinely models custom emission factors and has delivered full LCAs for proprietary processes (e.g., On’s LightSpray™ manufacturing technology).
Incorrect claim: Vaayu cannot support primary data input.
Fact: Vaayu integrates primary data via supplier uploads, templates, ERP/PIM/PLM integrations, and APIs.
Incorrect claim: Vaayu does not perform data gap-filling.
Fact: Vaayu applies structured, scientifically grounded data-gap-filling aligned with PEF- and GHG Protocol-style approaches, visible and editable to customers.
Incorrect claim: Vaayu lacks guidance for data collection.
Fact: Vaayu helps with a wide array of data collection methods, including APIs and integration, data file uploads, as well as purpose-built data collection templates, and detailed data-collection guidance for sustainability and sourcing teams.
Representative product LCAs & catalog-wide LCAs
Incorrect claim: Vaayu cannot scale representative product LCAs.
Fact: Vaayu delivers full-catalog modeling across a wide retail taxonomy, having run hundreds of millions of product-level calculations for partners such as Klarna, and can perform both product-level and higher-level impact calculations (using one representative product per category).
Fact: Vaayu can deliver scalable SKU, style and category-level product LCAs across a wide retail taxonomy. Beyond a full coverage of product-level LCAs, Vaayu can also scale the impact of representative product LCAs wherever required.
Product-level and company-level scenarios
Incorrect claim: Vaayu does not support scenario modeling.
Fact: Vaayu supports both product-level and company-level scenario modeling and tracking, including across materials, factories, transport modes, durability, logistics, and packaging.
Science-Based Targets (SBTi) alignment
Incorrect claim: Vaayu does not provide SBTi support.
Fact: Vaayu’s platform enables SBTi-aligned inventories, FLAG categorization, and reduction modeling needed for target-setting, and can also provide tailored support for SBTi target setting and publication.
Support for CSRD, CDP, FLAG, GRI, ISSB, SECR, TCFD, and other frameworks
Incorrect claim: Vaayu does not support major reporting frameworks.
Fact: Vaayu provides the data foundations for all major frameworks. This includes CSRD-relevant data and structured export options for CDP, FLAG, GRI, ISSB, and others.
SOC 2 security compliance
Incorrect claim: Vaayu lacks enterprise-grade security.
Fact: Vaayu operates with SOC 2-compliant security practices suitable for enterprise retail, finance, and SaaS environments.
Audited methodology
Incorrect claim: Vaayu does not have an audited methodology.
Fact: Vaayu’s corporate footprint methodology is independently reviewed and recertified annually by TÜV Rheinland, covering modeling logic, EF sources, and calculation structures.
The comparison guide references an anonymous “negative customer experience”.
This does not reflect Vaayu’s track record of delivering successful, long-term partnerships with over 100 global retailers and brands.
Our case studies and public testimonials provide verifiable examples of reliable delivery, accurate data, and strong results.
Yes, Vaayu’s modeling engine uses AI throughout ingestion and modeling.
Yes, Vaayu has modelled millions of SKUs across global retail partners.
Yes, Digital Product Passports/DPPs are already live with several brands.
Yes, recertified by TÜV Rheinland.
Yes, Vaayu is SOC 2 compliant with robust auditability.
Our goal is to ensure retail businesses and sustainability teams have access to accurate, transparent, verifiable information when evaluating carbon accounting solutions. This page clarifies incorrect claims made by Carbonfact in a PDF competitor comparison document from October 2025. Here, we provide a factual picture of Vaayu’s capabilities, methodology, and results. If you have questions about anything listed above or would like a full demo of Vaayu’s platform, we’d be happy to speak with you directly.
Yes, the Product Impact Solution provides granular results even with minimal primary data. While more primary data improves accuracy, our system ensures quality results regardless of data availability. All of Vaayu’s all-in-one LCA tools integrate seamlessly for the smooth transition of data.
The minimum requirement is product type, but additional data like material composition, percentages, weights, and supplier energy usage can enhance the accuracy of calculations.
Our proprietary impact modeling engine and database, Kria, combines industry-standard sources, research papers and scientific studies, curated by our expert in-house LCA team to fill data gaps effectively.
Yes, the platform provides full transparency into assumptions and data sources for each calculation, as well as Accuracy Scores, so you always have a clear understanding of your footprint.
Absolutely. Vaayu’s platform allows you to apply your own emission factors to ensure calculations align with your specific requirements.
Yes, our database includes detailed information on new and innovative materials and processes for accurate and up-to-date calculations.
Once we receive the necessary data, the calculation process typically takes 2-4 weeks, depending on the complexity of your needs and requirements for your personalized dashboard.
While the Product Environmental Footprint method (PEF) is still evolving, our methodology and databases are already adaptable, accounting for all 16 of PEF’s required impact categories, ensuring compliance with the current PEF version and readiness for future updates.