AIoT SaaS for fleet telematics, video safety and industrial asset data
Powerfleet sells AIoT software for mobile assets, from vehicle telematics to forklifts and in-warehouse systems, with Vision AI and fatigue monitoring at the product core. Its data layer mixes Kafka, Azure Event Hubs, Spark and three lakehouse formats (Hudi, Delta Lake, Iceberg) alongside a legacy SQL Server BI suite, a footprint consistent with the post-merger integration pressure its job posts repeat. A parallel push toward an enterprise AI center of excellence and governance is underway.
Powerfleet is a public company founded in 1993 and headquartered in Woodcliff Lake, New Jersey, with 1,001–5,000 employees. It provides SaaS that ingests and unifies data from mobile assets such as fleet vehicles and forklifts, covering telematics, logistics, video-based safety and analytics. Customers are operators of vehicle fleets and industrial equipment who need operational and safety insights. The company runs offices internationally and hires across the United States, Canada, Mexico, Argentina, the United Kingdom, Greece and Australia. Internal operations run on Microsoft Dynamics 365, Salesforce and BambooHR.
Powerfleet uses Python, C#, JavaScript, Kafka, Azure Event Hubs, Apache Spark, Snowflake, PostgreSQL, AWS Aurora, Delta Lake, Apache Iceberg and Apache Hudi, plus SQL Server, Power BI, Salesforce and Dynamics 365.
Powerfleet hires in the United States, Canada, Mexico, Argentina, the United Kingdom, Greece and Australia, with roles spread across engineering, support, sales, HR and operations.
Job posts point to installing Vision AI, fatigue monitoring and in-warehouse systems, developing VisionAI safety applications, building an AI center of excellence and governance framework, and large-scale deployments.
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Powerfleet'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.