• Maximise Yield and Profits

    Identify root causes and bottlenecks to improve plant performance

  • Reduce Energy Consumption

    Leverage AI to minimise your energy consumption

  • Optimise Product Quality

    Compare batches to uncover product quality issues in real-time

  • Optimise Utilities Consumption

    Sophisticated models that will reduce your utilities consumption

  • Predict Failures and Prevent Shutdowns

    Actionable real-time alerts and anomaly detection proven to predict failures

  • Improve Productivity

    Sophisticated analytics, customised for plant professionals, reduce troubleshooting from weeks to hours

  • Improve Health, Safety, and Emissions Compliance

    Leverage AI to monitor and manage your emissions

PRODUCT OVERVIEW

Industrial data analysis is a resource-intensive process that has a long lifecycle due to inefficiencies in all phases. These limitations lead to delays in obtaining actionable insights into any incident that may occur, resulting in production losses and increased costs.

EmpiricAI’s Industrial Analytics is a self-service advanced analytics solution that enables engineers to rapidly investigate and share insights from their OT and IT data. Connecting time series data with an Industrial Analytics is as simple as filling in a form.

Our product has been custom built for industrial plant professionals and what they need to do hourly, daily, weekly and monthly. Its advanced analytics engine enables process and asset experts to analyze, monitor, and predict the operational performance of their plant and assets in real-time and over time.
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VISUALIZE

Visualize months of process data instantaneously. Make projections and assessments of various asset and performance parameters, and filter and overlay data with the click of a button to identify opportunities.

DIAGNOSE

Quickly compare current and past process data to identify similarities in trends and behaviour. Perform a speedy root cause analysis by identifying how the parameters relate to each other. Integrate digital organization knowledge management with live process data to reduce breakdowns.

PREDICT

Our prediction features help users get a sneak peek of how different parameters are expected to behave under ongoing conditions in the future. This aids in decision support to run the plant at optimum levels and take corrective actions before incidents occur.

PRESCRIBE

Self-service analytics provide a robust framework that lets you deploy physics-based and AI/ML models on top of it to not only predict but prescribe for quick actions to save maintenance costs and increase efficiencies in the industrial space.

HAVE A QUESTION?

Office 1: +(03) 0106 387 4456
Office 2: +(03) 0106 387 4456

Email your query

info@empiric.ai

WE ARE OPEN ALL WEEK

From Mon to Fri 08:00 – 18:00
Sat to Sun 10:00 – 16:00

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  • Monitor data to increase reliability

    Monitor real-time data coming from multiple sources to ensure safe plant operations. EmpiricAI Industrial Analytics’ robust architecture ensures quick retrieval of years’ worth of historical data, and, its capability to provide rich context to data, helps process and operations experts in decision support.

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    Monitor data to increase reliability

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  • Optimize Production and Efficiency

    Improve product quality by timely detection of any deviation of process parameters, validated by historical data. Automatic timely alerts, enriched with contextual data from the past, enable process experts to take corrective action to ensure continuity. In batch processes, using ideal batch patterns to predict batch quality, can produce the desired output batch after batch.

    Optimize Production and Efficiency

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  • Predictive Maintenance

    Maximize asset availability and increase runtime by providing data driven decision support for maintenance planning. By identifying patterns of problematic behaviors validated from past failure instances, you can detect anomalies early and avert asset failure before it happens.

    Predictive Maintenance

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  • Manage Risk

    Minimize repeat incidents by creating digital footprint of past incidents and providing early warning by automated detection of any deviation. Reduce safety risks through early warnings. Monitor fugitive emissions and reduce environmental impact.

    Manage Risk

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