Direct-to-consumer workwear brand scaling operations and customer intelligence
BRUNT is a 4-year-old workwear-focused apparel and footwear brand selling direct-to-consumer and wholesale. The tech stack reveals a company in operational scaling mode: they're layering data infrastructure (BigQuery, Fivetran, Looker Studio, Vertex AI) and AI experimentation (LangChain, LangGraph) on top of core commerce (Shopify, NetSuite, Stripe), while actively adopting dbt and Terraform to formalize data pipelines. Hiring has accelerated across marketing, support, and data—indicating a shift from bootstrap operations toward structured customer insight and retention.
Notable leadership hires: Customer Service Director
BRUNT designs and sells workwear, boots, and apparel for trade workers, offering both direct-to-consumer and wholesale channels. Based in North Reading, Massachusetts, the company operates Shopify storefronts, NetSuite ERP, and POS infrastructure, with payment processing via Stripe and email/SMS campaigns through Klaviyo and PostScript. Current operational focus spans product lifecycle management across bottoms, denim, and outerwear; customer support process improvement; and a formal voice-of-customer program. Recent pain points include scaling customer service operations cost-effectively, managing seasonal capacity, and expanding physical retail footprint.
Shopify (commerce), NetSuite (ERP), Stripe (payments), BigQuery + Fivetran + Looker Studio (data), Klaviyo + PostScript (email/SMS), Vertex AI (ML), Slack (communication), and GCP/AWS for cloud infrastructure.
Product lifecycle management for boots and apparel, customer support optimization, RAG pipeline development, customer feedback analysis, media outreach strategy, and a formal voice-of-customer program. Also implementing OKR frameworks and improving returns/warranty operations.
BRUNT Workwear'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.