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Description
Enhancing reliability, performance, and safety stands as a primary focus for industrial enterprises and businesses in the current landscape. Organizations are channeling their resources and efforts into managing expenses effectively while striving to maximize value from their existing assets. AVEVA Predictive Analytics empowers these organizations to achieve optimal returns on essential assets by facilitating predictive maintenance (PdM) initiatives. The AVEVA Predictive Analytics solution offers advanced early warning notifications and diagnostics for equipment problems, potentially identifying issues days, weeks, or even months before they lead to failures. This proactive approach allows asset-heavy organizations to minimize equipment downtime, boost reliability, and enhance performance, all while decreasing operational and maintenance costs. Furthermore, AVEVA Predictive Analytics seamlessly integrates with various control and monitoring systems and supports deployment either on-premises or in a cloud environment. Its highly scalable architecture enables the monitoring of anything from a single asset to entire plants or even hundreds of remote assets spread across multiple locations, ensuring comprehensive oversight and management capabilities. Ultimately, this solution aids organizations in navigating the complexities of asset management in an increasingly competitive market.
Description
Vaeqor is an innovative, cloud-based platform that harnesses the power of AI for industrial maintenance and asset management, specifically tailored for businesses that depend on essential machinery and infrastructure. This comprehensive application integrates intelligent troubleshooting, predictive analytics, visual AI diagnostics, maintenance oversight, and asset monitoring into a single user-friendly interface.
Applicable across various sectors such as manufacturing, mining, aviation, aerospace, oil and gas, utilities, food and beverage, rail, maritime, pharmaceuticals, and data centers, Vaeqor empowers maintenance teams to minimize downtime, enhance equipment reliability, and expedite maintenance decision-making processes.
In contrast to conventional CMMS software, Vaeqor goes beyond merely documenting maintenance tasks; it actively assists teams in diagnosing issues, uncovering root causes, anticipating failures, and optimizing maintenance strategies through advanced artificial intelligence techniques.
As a Progressive Web App (PWA), Vaeqor provides seamless functionality across desktop, tablet, and mobile devices, eliminating the need for installation from an app store, which makes it even more accessible for organizations. With its user-centric design and robust features, Vaeqor aims to transform how industries manage their maintenance processes and asset health.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$29/month
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
Aveva
Founded
1967
Country
United Kingdom
Website
www.aveva.com/en/products/predictive-analytics/
Vendor Details
Company Name
Vaeqor
Founded
2026
Country
South Africa
Website
vaeqor.com
Product Features
Predictive Analytics
AI / Machine Learning
Benchmarking
Data Blending
Data Mining
Demand Forecasting
For Education
For Healthcare
Modeling & Simulation
Sentiment Analysis
Product Features
CMMS
Asset Tracking
Calibration Management
Inventory Control
Key & Lock Management
Mobile Access
Preventive Maintenance
Purchasing
Scheduling
Service History Tracking
Technician Management
Work Order Management