Litmus sells an edge data platform that pulls machine data from PLCs and industrial protocols (OPC UA, Modbus, Ethernet/IP, DNP3, MQTT) and routes it into AWS, Azure, GCP, Databricks and Snowflake. Its Go, C++ and Yocto Project stack points to embedded edge software, and Playwright adoption lines up with test automation work on Litmus Edge Manager. Hiring is accelerating and weighted toward engineering and customer support, which signals a push to scale production deployments.
Litmus is a privately held company founded in 2014 and headquartered in Santa Clara, California, with 51–200 employees. It builds software that collects, normalizes and contextualizes operational technology data from industrial equipment such as PLCs, SCADA, MES systems, historians and sensors. Manufacturers in automotive, food and beverage, energy and advanced manufacturing use it for predictive maintenance, asset monitoring, quality analytics and industrial AI. The company has teams across North America, Europe and APAC and is hiring in the United States, Germany, Japan and Canada.
Litmus uses Go, C++, Java and the Yocto Project, with Kubernetes and Azure Kubernetes Service. It works with industrial protocols such as OPC UA, Modbus, MQTT and DNP3, and integrates with AWS, Azure, GCP, Databricks and Snowflake.
Litmus is hiring in the United States, Germany, Japan and Canada. Hiring is accelerating and concentrated in engineering, support and sales roles, mostly at the senior and mid levels.
Current work includes test automation for Litmus Edge Manager, southbound connectors for PLCs, real-time data infrastructure for AI, a cloud-native product strategy, and OEM partnership development.
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Litmus'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.