Azuga operates a multi-layered fleet telematics stack built on AWS microservices (Node.js, Kafka, Lambda, RQS) and Salesforce for customer-facing workflows, now adopting Salesforce DevOps Center. Active projects center on data ingestion standardization, firmware reliability, and device-agnostic driver scoring—indicating a shift from siloed hardware integrations toward unified telemetry pipelines. Pain points around firmware escalations and device upgrade success rates reveal scaling friction in the hardware-software boundary.
Azuga, a Bridgestone subsidiary founded in 2012, builds an end-to-end fleet management platform serving commercial fleets, government agencies, insurance companies, and automotive suppliers. The product integrates hardware (OBD-II devices), cloud applications (GPS tracking, driver monitoring, video telematics), and analytics to improve fleet safety, visibility, and operational efficiency. The platform powers over 13,000 commercial fleets globally. Engineering is distributed across the US and India, with current hiring focused on backend development, customer support, and product roles.
Azuga's backend runs on AWS (Lambda, SQS, EventBridge, RDS) with Node.js and Java microservices, event streaming via Apache Kafka, and databases including MySQL, MongoDB, and DynamoDB. Customer operations use Salesforce (Lightning, Flow, Apex) with MuleSoft for integrations and AutoRabit/Gearset for deployment automation.
Current projects include a next-generation data logger roadmap, telemetry signal ingestion and backend normalization, firmware upgrade strategy with OTA reliability improvements, and automation workflow enhancements—addressing challenges in device compatibility, firmware escalations, and multi-vendor driver scoring standardization.
Azuga, Inc.'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.