Supply chain sustainability data platform for consumer goods brands
Worldly runs an ESG and supply chain data platform for consumer goods companies, built on an Angular/NgRx micro-frontend stack (NX, Module Federation) across both AWS and Azure. Its Python ML layer (PyTorch, spaCy, NetworkX) points to NLP and supplier-graph analysis on facility data. Hiring tilts toward senior engineering and marketing, while job posts flag friction in supplier onboarding and repeat audits as active pressures.
Worldly is a privately held company founded in 2019 and headquartered in Concord, California, with 51–200 employees. It gives brands, retailers and manufacturers in apparel, footwear, home furnishings and sporting goods visibility into environmental and social metrics such as carbon, water, chemicals and labor. Data is measured at the product, facility and value-chain level and is aligned with Cascale's Higg Index. Customers use the platform to manage supplier risk and respond to regulatory requirements. The company recruits across the United States, Latin America, Europe and Asia.
Worldly builds with Angular, NgRx, TypeScript, Node.js, Java and .NET on AWS and Azure. Its data layer uses PostgreSQL, MySQL and MongoDB, and its ML work runs on Python, PyTorch, spaCy and scikit-learn.
Worldly hires in the United States and across Latin America, including Uruguay, Colombia and Mexico. It also recruits in Europe, including Bulgaria, Portugal and Germany, and in Asia, including China and Vietnam.
Job posts point to sustainability data visualization, ESG supply chain data collection programs and a better supplier onboarding experience. They also mention AI-assisted content enablement and standardized customer success playbooks.
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Worldly's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.