Zipmend operates a fleet-based express delivery network handling 6,000+ urgent shipments monthly across the UK and Europe. The tech stack (Laravel, Vue, MongoDB, n8n, Zapier) reflects a operations-first engineering posture focused on booking automation and real-time tracking rather than deep ML or data infrastructure. Current hiring tilts heavily toward HR and sales roles with manager-level seniority, paired with active projects in sales process automation and market expansion into Italy and the Netherlands—suggesting the company is scaling operational capacity and GTM infrastructure faster than engineering headcount.
Zipmend provides time-critical direct transport services across the UK and Europe, with a fleet of over 8,500 courier vehicles. The business model centers on rapid pickup (60–120 minutes) and same-day delivery for parts, equipment, and logistics-dependent operations. Customers quote and book 24/7 through a web and API interface; the company manages fulfillment through a fleet-dispatch system and delivers real-time tracking to end users. Founded in 2015 and headquartered in Hamburg, the company serves mid-market industrial, automotive, and events sectors where delivery delays create production downtime or reputational damage.
Zipmend operates across the UK and Europe with a fleet of 8,500+ courier vehicles. Pickups are available within 60–120 minutes; the company handles 6,000+ urgent shipments monthly and offers same-day delivery as a core service.
Zipmend's primary stack includes Laravel (backend), Vue (frontend), MongoDB (database), Sentry (error tracking), n8n and Zapier (workflow automation), and Zendesk (customer support). The infrastructure supports 24/7 booking, API integration, and real-time tracking.
zipmend GmbH'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.