OPUS - Condition Monitoring, Predictive Maintenance & Process Optimization No-code AI Platform

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Deployed by 2 companies

No-code AI predictive insights for complex processes. Improve asset reliability and uptime

Page last modified
April 11 2024

OPUS allows you to predict what, when and why your equipment will fail, long before it does, providing accurate root cause analysis insights so you can plan and implement interventions to avoid downtime and production loss. Use no-code AI to uncover the most efficient operating settings to reduce material and power costs.  Discover opportunities to optimize processes, implement predictive maintenance and reduce emissions.

Spend less time analysing data and more time acting on it. OPUS is built to seamlessly integrate with your existing infrastructure and be used by your existing Engineering, Operations and SME team to quickly build, train and maintain AI models of your assets without programming or coding experience.

Pros & Limitations
Improve asset reliability, integrity and lifecycle
Build no-code AI modells without programming or coding experience
Uncover rapid real-time insights for improved decision making
Reduce unplanned shutdowns and downtime
Remote live condition monitoring of your assets health, anywhere, anytime
Increased production, safety and environmental performance
Enterprise wide solution
Retain data ownership, privacy and security
Rapid root cause analysis
If the quality of data received from the asset is poor then the AI accuracy will be reduced
Predict asset failures in advance for predictive maintenance
Reduce OPEX costs with predictive maintenance insights
Holistic analysis of all available plant data reveals un-foreseen correlations and causations to incidents
Rapid deployment - deploy in just weeks and start generating business value
Specification Title Specification Description
Areas of Application
Oil and Gas, Mining, Power Generation and Utilities, Water, Maritime, Facilities, Smart Cities.
Predictive Analytics
no-code AI can predict future incidents and failures weeks in advance by continuously analysing historical and live data.
Machine Learning
Auto Machine Learning technology continuously learns how your plant operates under different conditions.
Asset Life Extension
Critical insights to assist with extending the useful life of assets.
99.9% AI model accuracy (based on sufficient quality data) for accurate predictions on future faults and failures.
Easy to use drag and drop web based platform. Customise your own dashboards, build your own AI models without programming experience
Reduce operating costs, improve efficiencies and increase production with optimization insights.
Cloud Platform
VROC cloud based platform allows any-where access to monitor your plants assets and operations.
Software as a service annual subscription allows unlimited users and unlimited prediction models to be generated by the existing client team.
Customer retention of data ownership, security and privacy.
Predictive Maintenance
Predict future asset degradation and deviation and plan interventions to avoid asset failure and downtime


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Technology Readiness Level

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Development Technology demonstration Mature / Proven
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VROC believes in unleashing the power of your big data, through data connection and storage. Our Auto AI platform provides customers with critical predictive insights to optimize productivity, safety and sustainability.


We are committed to tackling the most formidable AI adoption challenges around connected industries and data science, such as:

  • Real-time integration with operational technologies for enterprise scale analytics;
  • Rapid model deployment at scale;
  • Sustainability and maintenance and;
  • Whole of life cost effectiveness.

With a vision of a world where industries are connected, integrated, and fully automated. We are on a mission to create a truly efficient and productive industrial ecosystem through AI-powered end-to-end automation.

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