Multimodal freight broker and 3PL platform serving enterprise shippers
Arrive Logistics operates a transportation brokerage and 3PL network spanning truckload, LTL, flatbed, intermodal, and drayage services. The tech stack—NetSuite + Snowflake + Python + scikit-learn/TensorFlow—points to a company scaling operational infrastructure while building analytical depth; the absence of any replacing activity suggests a disciplined, stable tech footprint rather than reactive retooling. Active hiring leans heavily sales-focused (sales roles outnumber engineering 5:1), which aligns with explicit projects around drayage revenue growth and open deck expansion.
Arrive Logistics is a freight brokerage and logistics platform founded in 2014 and headquartered in Austin, Texas. The company operates a network of approximately 4,000 customer accounts and 40,000 carriers, positioning it among the largest independent brokers. Service lines span multiple modes—truckload, LTL, flatbed, intermodal, and drayage—with a focus on custom solutions for enterprise shippers. Core infrastructure is built on NetSuite for enterprise resource planning, Snowflake for analytics, and Python-based tooling for data science and backend systems. The organization is mid-scale (1,001–5,000 employees) and actively hiring across sales, logistics operations, and engineering to accelerate growth in high-margin segments like drayage and oversized/heavy haul.
Arrive uses NetSuite and Oracle NetSuite for core operations, Snowflake for analytics, Python (with scikit-learn, TensorFlow, Pandas) for data science, AWS and Azure for cloud infrastructure, Slack and RingCentral for communications, and Jira + Azure DevOps for development workflows.
Arrive Logistics is headquartered in Austin, Texas, and was founded in 2014. The company actively hires in the United States, Peru, and Mexico.
Arrive Logistics'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.