Stream Industrial Data From the Edge to Message Brokers

Connect plant-floor systems and prepare operational data for event-driven industrial architectures.

• Connect PLCs, SCADA, historians, sensors, CNCs, and industrial systems
• Use 250+ native drivers to reduce custom connectivity work
• Discover and organize devices, tags, and operational metadata

Publish industrial data from Litmus Edge into Kafka-based architectures for real-time analytics, AI, and enterprise workflows.

• Publish machine data, events, and contextualized tag streams into Kafka topics
• Support scalable, high-throughput industrial data movement
• Connect Litmus Edge data with cloud, analytics, and enterprise platforms

Support secure, queue-based industrial messaging between edge systems and enterprise applications.

• Send and receive data through AMQP messaging patterns
• Support reliable broker-based communication between OT and IT systems
• Enable secure edge-to-enterprise data movement

Publish and subscribe to industrial data across distributed edge and cloud-connected environments.

• Send and receive industrial data through MQTT brokers and clients
• Support lightweight publish / subscribe architectures
• Enable efficient communication across distributed assets and systems

Reduce unnecessary data movement and publish only what downstream systems need.

• Filter noisy or unnecessary tag streams before publishing
• Run KPIs, alerts, thresholds, and event logic locally
• Publish relevant data, events, or summaries into Kafka, AMQP, or MQTT

Protect OT systems while making operational data available to the right teams and applications.

• Apply role-based access controls across users and systems
• Govern how data is published, routed, and consumed
• Support encrypted, auditable industrial data movement across edge, IT, and cloud