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What is Senseye PdM?

Senseye PdM utilizes cutting-edge proprietary machine learning approaches to predict asset failures before they happen. By continuously assessing the operational performance of machinery, Senseye is able to provide precise forecasts on when maintenance should be conducted. This capability enables maintenance teams to focus their resources on the most critical assets needing immediate attention. With a straightforward implementation process, organizations can lower their maintenance costs while improving the accuracy of their downtime forecasts. Built with scalability in mind, Senseye PdM can support any number of connected devices, regardless of size. The automated condition monitoring delivers insights that spotlight only the most crucial data. Users are informed about the expected operational lifespan of their machinery prior to the need for maintenance. Moreover, the platform facilitates the analysis of thousands of assets, offering clear and continuous updates on which machines require intervention. In addition to minimizing machine downtime, Senseye empowers industrial companies to enhance their operational efficiency and overall productivity. Thus, through its innovative approach, Senseye PdM not only optimizes maintenance strategies but also supports long-term asset management goals.

What is OPUS?

OPUS stands out as a premier no-code AI platform designed specifically for the industrial sector, enabling users to effectively model both equipment and processes. By utilizing OPUS, organizations can access a wide array of benefits including insights for process optimization, predictive maintenance, reduced energy consumption, enhanced productivity, precise forecasting, greater asset reliability, diminished maintenance expenditures, improved planning capabilities, and valuable ESG reporting with carbon reduction insights. Teams can leverage this platform without needing any programming skills, allowing them to extract insights from their data and anticipate future scenarios effortlessly. Dive deeper into your asset's data like never before, revealing unforeseen correlations that may not have been immediately apparent. Conducting root cause analysis on specific components can help direct your efforts where they matter most, ensuring efficient use of resources. The automated AI predictive insights provided by OPUS enable strategic planning for interventions and empower you to make well-informed business decisions confidently. With the capability for rapid deployment and receiving AI model results in mere minutes after creation, organizations can harness the full potential of their existing operational data, leading to tangible returns on investment with the expertise of their current team of asset engineers, operators, and maintenance managers. Transform your entire facility, plant, or work site by tapping into the remarkable potential of automated AI and witness the significant improvements in operational efficiency and effectiveness. Seize the opportunity to elevate your industrial processes to new heights with OPUS.

Media

Media

Integrations Supported

Integrations Supported

AVEVA PI System
AWS App Mesh
Aspen HYSYS
Azure Industrial IoT
ControlST
FactoryTalk Historian
Microsoft Entra ID
PowerLogic ION EEM
Siemens APM

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

Competitive pricing structure based on number of sensors. Included unlimited users and AI model development.

Supported Platforms

SaaS
Android
iPhone
iPad

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Senseye

Date Founded

2014

Company Location

United Kingdom

Company Website

senseye.io

Company Facts

Organization Name

VROC

Date Founded

2016

Company Location

Australia

Company Website

vroc.ai/products/opus/

Categories and Features

Condition Monitoring

Not specified

IoT

Big Data Analytics
Data Management
Device Management
Performance Management
Visualization

Machine Monitoring

Not specified

OEE

Downtime Tracking
Historical Reporting
Real Time Reporting
Trend Analysis
Work Order Management

Preventive Maintenance

Condition Monitoring
Inspection Management
Maintenance Scheduling
Mobile Access
Predictive Maintenance
Purchasing
Reminders
To-Do List
Work Order Management

Categories and Features

Artificial Intelligence

Machine Learning
Predictive Analytics
Rules-Based Automation

No-Code Development

AI-Assisted Development
Data Aggregation and Publishing
Deployment Management
Drag & Drop
Integrations Management
Iteration Management
Performance Monitoring
Templates
Visual Modeling

Root Cause Analysis

Not specified

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