Machine learning requires 'ready-to-use' data, collected from all assets and data sources at the edge

The biggest challenge Industry 4.0 companies face is access to the data they need to fuel machine learning and analytics models. Our edge platform is purpose-built to solve the complex challenge of connecting to any industrial asset or data source, and integrating data with enterprise, cloud and big data systems. OT and IT teams trust Litmus to deliver the critical data they need to enable machine learning to improve asset and process uptime, performance and quality.

  • One Platform to Collect, Process and Integrate Data from All Industrial Assets

    Litmus delivers unmatched time-to-value by connecting to any PLC, DCS, SCADA, Historian or sensor in just minutes. Our industry-leading, 250+ pre-loaded driver library connects and collects data out-of-the-box with no programming required. Litmus normalizes and structure the data into a standard format for immediate consumption by third party machine learning applications.

  • Integrate ‘Ready-to-Use’ Data with Any Cloud or Big Data Cloud System

    Normalized data is immediately made available to both OT and IT systems. Litmus provides pre-built, easy to configure connectors to Cloudera, Azure, Oden and others for rapid deployment. Use the critical and accurate asset data collected and normalized to deploy advanced analytics and machine learning models that lead to increased operational efficiency.

  • Deploy and Run Machine Learning Models at the Edge

    Litmus completes the continuous improvement loop by pushing machine learning models back to industrial assets at the edge, enabling true anywhere-to-anywhere data flow. Run machine learning models at the asset to deliver corrective actions in real-time.

The Edge Platform for Industry 4.0

Our flexible and scalable edge platform is built for any Industry 4.0 initiative or use case – from smart manufacturing and Industrial IoT to predictive maintenance and machine learning. Litmus provides the data collection, analytics, management and OT-IT integration necessary to increase asset visibility, performance and uptime at scale.

  • Predictive Maintenance

    Litmus for Predictive Maintenance provides the asset data collection, analytics and machine learning needed to reduce unplanned downtime and increase the efficiency of maintenance activities.

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  • Asset Condition Monitoring

    Litmus for Asset Condition Monitoring helps companies collect, analyze, manage and integrate asset data to take the guesswork out of asset condition and fully exploit equipment investment.

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  • OEE

    Litmus for OEE harnesses the critical data buried with assets at the edge to dramatically simplify the calculation of Overall Equipment Effectiveness and optimize throughput, increase quality and improve performance.

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  • Edge Computing

    Litmus for Edge Computing is purpose-built to connect to any industrial asset or data source, analyze and visualize data at the edge, and quickly and easily share valuable edge data with enterprise systems.

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  • Industrial IoT

    Litmus for IIoT allows manufacturers to connect to any asset, collect and analyze data, integrate with cloud and big data applications for advanced analytics, then run the models back at the edge for continuous improvement.

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  • Smart Manufacturing

    Litmus for Smart Manufacturing is an all-in-one edge platform deployed next to the assets to collect, analyze, manage and integrate real-time data from the factory floor to meet business needs across the organization.

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