Loop builds domain-specific AI for logistics, targeting the messy billing, invoicing and audit workflows behind freight operations. Its stack pairs a TypeScript/NestJS/GraphQL product layer on AWS Fargate and ECS with PyTorch, TensorFlow and a Snowflake-dbt-Dagster data pipeline, and the team is adopting Cursor and Codex for AI-assisted development. Accelerating hiring skews toward senior and lead roles spread across engineering, ops, finance and legal.
Notable leadership hires: Tech Lead
Loop is a privately held company headquartered in San Francisco, California, with 201–500 employees. It develops verticalized AI for the logistics sector, including data models, domain intelligence and infrastructure aimed at operational inefficiencies in the physical economy. Its focus areas include carrier billing discrepancies, invoice management, audit workflows and reducing manual review across operations pipelines. Hiring is currently concentrated in the United States across engineering, operations, data, finance, legal, HR and marketing.
Loop runs TypeScript, React, Node.js, NestJS, GraphQL and Prisma on AWS (CDK, Fargate, ECS) with PostgreSQL, Kafka, Redis and Elasticsearch, plus Python, PyTorch, TensorFlow, Snowflake, dbt and Dagster for data and ML.
Job posts point to an AI harness, privacy and AI compliance, operational models for throughput and cycle time, audit workflows and reporting, and carrier billing discrepancy resolution.
Loop is headquartered in San Francisco, CA, and is currently hiring in the United States across engineering, operations, data, finance, legal, HR and marketing.
Other companies in the same industry, closest in size
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.
