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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 Crosser?

Harness the power of Edge computing to transform large datasets into actionable insights that are easy to manage. Collect sensor data from all your machinery and create connections to various devices such as sensors, PLCs, DCS, MES, or historians. Adopt condition monitoring for assets situated in remote locations, effectively adhering to Industry 4.0 standards to ensure optimal data collection and integration. Combine real-time streaming data with enterprise-level information for smooth data transitions, utilizing either your preferred Cloud Provider or an in-house data center for storage needs. Take advantage of Crosser Edge's MLOps features to implement, manage, and deploy your tailored machine learning models, while the Crosser Edge Node accommodates any machine learning framework. You can access a centralized repository for your trained models hosted in Crosser Cloud, and simplify your data pipeline with an intuitive drag-and-drop interface. Easily deploy your machine learning models across multiple Edge Nodes in a single action, enabling self-service innovation through Crosser Flow Studio. Benefit from an extensive collection of pre-existing modules that enhance collaboration among teams in different locations, significantly decreasing dependency on specific team members and boosting overall organizational productivity. By leveraging these advanced capabilities, your operational workflow will not only enhance collaboration but also drive innovation to unprecedented levels, paving the way for future advancements.

Media

Media

Integrations Supported

Integrations Supported

Advantech WebAccess/CNC
Azure Stream Analytics
Barracuda PST Enterprise
Google Cloud Platform
Microsoft Azure
SIGNL4

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Online Training

Company Facts

Organization Name

Senseye

Date Founded

2014

Company Location

United Kingdom

Company Website

senseye.io

Company Facts

Organization Name

Crosser Technologies

Date Founded

2016

Company Location

Sweden

Company Website

www.crosser.io

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

Condition Monitoring

Not specified

IoT

Not specified

IoT Analytics

Not specified

IoT Development

Not specified

Machine Monitoring

Not specified

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