Loop builds AI systems for logistics and supply chain operations, with a tech stack spanning TypeScript, React, Node.js, PostgreSQL, Kafka, and ML frameworks (PyTorch, TensorFlow). The company is actively adopting Cursor and Codex—signals of AI-assisted development workflows—while scaling engineering-heavy hiring. Core projects center on production AI deployment, payment automation, and operational intelligence, suggesting a shift from data cleanup toward AI-driven workflows that unlock margin in physical logistics.
Loop develops verticalized AI for logistics operations, targeting companies managing supply chain workflows. The product surfaces as a full-stack application (TypeScript/React frontend, Node.js/NestJS backend, PostgreSQL data layer) with streaming capabilities (Kafka), ML inference (PyTorch/TensorFlow), and payment integration (Salesforce). Customers operate in the physical economy—freight, warehousing, last-mile delivery—where Loop addresses fragmented billing systems, cost leakage, and working-capital friction. The company is based in San Francisco and currently spans 201–500 employees.
Loop's primary stack is TypeScript, JavaScript, and Python. The backend runs Node.js with NestJS and Prisma; frontend uses React and GraphQL. ML workloads use PyTorch and TensorFlow. Infrastructure is AWS (Fargate, ECS, CDK).
Active projects include production AI deployment, financial automation (payments and audits), supply chain optimization, and internal systems rollouts. The product roadmap emphasizes operational intelligence and post-launch implementation support for logistics customers.
Loop'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.