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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Analyze and utilize your data at the Edge to transform Big Data into manageable, pertinent insights. Gather sensor information from all your equipment and establish connections with various devices like sensors, PLCs, DCS, MES, or historians. Implement condition monitoring for assets located remotely, aligning with Industry 4.0 standards for effective data collection and integration. Merge real-time streaming data with enterprise data for seamless data flows, and utilize your preferred Cloud Provider or your own data center for data storage solutions. Leverage Crosser Edge's MLOps capabilities to bring, manage, and deploy your custom machine learning models, with the Crosser Edge Node supporting any machine learning framework. Access a centralized library for your trained models hosted in Crosser Cloud, and streamline your data pipeline using a user-friendly drag-and-drop interface. Easily deploy machine learning models to multiple Edge Nodes with a single operation, fostering self-service innovation through Crosser Flow Studio. Take advantage of an extensive library of pre-built modules to facilitate collaboration among teams across different locations, effectively reducing reliance on individual team members and enhancing organizational efficiency. With these capabilities, your workflow will promote collaboration and innovation like never before.

Description

Senseye PdM employs advanced proprietary machine learning techniques to anticipate potential asset failures before they occur. By automatically evaluating the performance of your machinery, Senseye can accurately forecast when maintenance should be performed. This allows maintenance teams to prioritize their efforts on the assets that require the most urgent care. With an easy-to-implement solution, organizations can reduce maintenance expenses while enhancing the accuracy of downtime predictions. Designed for scalability, Senseye PdM can accommodate any number of connected machines, whether large or small. The automated condition monitoring provides insights that emphasize only the most pertinent information. Users gain an understanding of how long their machinery is expected to operate before maintenance is necessary. The platform allows for the seamless analysis of tens of thousands of assets, providing a clear and ongoing indication of which machines need attention. Furthermore, Senseye ensures that industrial companies experience significant reductions in machine downtime, ultimately leading to enhanced operational efficiency and productivity.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Advantech WebAccess/CNC
Azure Stream Analytics
Barracuda PST Enterprise
Google Cloud Platform
Microsoft Azure

Integrations

Advantech WebAccess/CNC
Azure Stream Analytics
Barracuda PST Enterprise
Google Cloud Platform
Microsoft Azure

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Crosser Technologies

Founded

2016

Country

Sweden

Website

www.crosser.io

Vendor Details

Company Name

Senseye

Founded

2014

Country

United Kingdom

Website

senseye.io

Product Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

IoT Analytics

Activity Dashboard
Activity Tracking
Analytics
Asset Tracking
Data Collection
Data Synchronization
Data Visualization
ETL
Multiple Data Sources
Performance Analysis
Real-Time Analytics
Real-Time Data
Real-Time Monitoring
Status Tracking

Product Features

IoT

Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
Visualization

OEE

Benchmarking
Cost Tracking
Downtime Tracking
Historical Reporting
Performance Metrics
Quality Control
Real Time Reporting
Root Cause Analysis
Trend Analysis
Work Order Management

Preventive Maintenance

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

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Alternatives

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