LITMUS + AWS INTEGRATION

Edge-to-Cloud Industrial Data for AWS

Connect industrial assets, structure OT data at the edge, and deliver trusted data into AWS services like IoT SiteWise, IoT Core, S3, SageMaker, and QuickSight.

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Trusted by manufacturers scaling industrial data and AI

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How Litmus integrates with AWS

AWS provides the infrastructure for industrial IoT, analytics, and AI. But most plant data isn’t ready to use. Litmus prepares OT data at the edge so AWS receives structured, contextualized data from day one.

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What you get with Litmus + AWS

Everything you need to turn plant floor data into trusted, AWS-ready data for operational intelligence.

Connect industrial assets for AWS-ready data

Connect PLCs, SCADA, historians, sensors, and machines—and prepare their data for AWS services.

  • 250+ native industrial drivers
  • Fast device and tag discovery
  • Consistent data foundation for AWS IoT SiteWise and AWS IoT Core
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Clean, contextualized data at the edge

Turn raw signals into structured operational data before sending it to AWS.

  • Normalize tags, units, and timestamps
  • Add asset, line, machine, and process context
  • Prepare data for AWS IoT SiteWise asset models, analytics, and AI
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Native integration with AWS IoT SiteWise

Move structured industrial data from Litmus Edge into AWS IoT SiteWise for monitoring, modeling, and analysis.

  • Support asset models, measurements, and hierarchies
  • Align with AWS IoT Greengrass for on-premise edge deployment patterns
  • Simplify plant-to-cloud deployment
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Seamless edge-to-cloud data flow

Run logic close to machines for faster response and lower cloud dependency.

  • Filter, enrich, and transform data locally
  • Run KPIs, alerts, thresholds, and event logic
  • Route only the data needed for each AWS use case
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Real-time processing at the edge

Run logic close to machines for faster response and lower cloud dependency.

  • Filter, enrich, and transform data locally
  • Run KPIs, alerts, thresholds, and event logic
  • Route only the data needed for each Azure use case
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Scalable multi-site deployment

Deploy and manage industrial data operations across multiple AWS-connected sites. 

  • Repeatable deployment patterns
  • Centralized configuration, updates, and workloads
  • Visibility into data flows, application status, and deployment health
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Secure and governed OT-to-Azure data flow

Control how industrial data moves into AWS, making trusted data accessible to OT, IT, data, and AI teams.

  • Role-based access control
  • Encryption in transit and at rest
  • Govern which data flows to AWS and how it is consumed
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Manufacturing use cases

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Predictive maintenance

Run AWS-based models using real-time equipment data.

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Asset condition monitoring

Track vibration, temperature, and machine health across sites.

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OEE & productive performance

Standardize availability, performance, and quality metrics.

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Predictive quality

Identify quality risks earlier using process and machine data.

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Digital twins

Power AWS IoT TwinMaker and visualization layers.

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Production Optimization

Improve throughput and reduce bottlenecks.

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Smart manufacturing data lake

Send trusted data to Amazon S3 for analytics and AI.

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Edge AI and ML

Support SageMaker workflows with structured industrial data.

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