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Average Ratings 0 Ratings

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features
design
support

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Description

Deep Text Inspection encompasses anomaly detection and clustering, utilizing advanced AI to analyze all log data while providing real-time insights and alerts. With machine learning clustering, it identifies emerging errors and unique risk KPIs, among other metrics, through effective pattern recognition and discovery techniques. This solution offers robust anomaly detection for data risk and content monitoring, seamlessly integrating with platforms like Logstash, ELK, and more. Deployable in mere minutes, AiOpsX enhances existing monitoring and log analysis tools by employing millions of intelligent observations. It addresses various concerns including security, performance, audits, errors, trends, and anomalies. Utilizing distinctive algorithms, the system uncovers patterns and evaluates risk levels, ensuring continuous monitoring of risk and performance data to pinpoint outliers. The AiOpsX engine adeptly recognizes new message types, shifts in log volume, and spikes in risk levels while generating timely reports and alerts for IT monitoring teams and application owners, ensuring they remain informed and proactive in managing system integrity. Furthermore, this comprehensive approach enables organizations to maintain a high level of operational efficiency and responsiveness to emerging threats.

Description

In response to the stringent quality requirements set by the automotive sector, semiconductor manufacturers are increasingly adopting Part Average Testing (PAT) to bolster the reliability of their products. This method focuses on identifying and eliminating "outlier" components that may pass conventional testing yet display unusual traits, thereby mitigating long-term quality and reliability concerns. By performing statistical analyses on a range of devices and modifying the pass/fail thresholds, PAT enables the early detection of these problematic parts, ensuring that only the highest quality components are included in production shipments. While Part Average Testing (PAT), as outlined in the Automotive Electronics Council AEC-Q001-Rev C specifications, primarily addresses DPM techniques for normal (Gaussian) distributions, many real-world scenarios involve distributions that do not conform to this norm. Consequently, it is essential to employ tailored PAT outlier detection strategies to prevent significant yield losses or erroneous identifications of outliers. To meet these challenges, PAT-Man emerges as a robust solution for implementing effective Part Average Testing (PAT). This innovative tool not only enhances the reliability of semiconductor components but also streamlines the testing process, ultimately benefiting manufacturers and consumers alike.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Elastic Cloud Yes 
Logstash Yes 

Integrations

Elastic Cloud No 
Logstash No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

XPLG

Founded

2005

Country

United States

Website

www.xplg.com/aiopsx-log-intelligence-for-application-monitoring/

Vendor Details

Company Name

Galaxy

Country

United States

Website

www.galaxysemi.com/products/pat-man

Product Features

Application Performance Monitoring (APM)

Baseline Manager No 
Diagnostic Tools No 
Full Transaction Diagnostics No 
Performance Control No 
Resource Management No 
Root-Cause Diagnosis No 
Server Performance No 
Trace Individual Transactions No 

IT Infrastructure Monitoring

Alerts / Notifications No 
Application Monitoring No 
Bandwidth Monitoring No 
Capacity Planning No 
Configuration Change Management No 
Data Movement Monitoring No 
Health Monitoring No 
Multi-Platform Support No 
Performance Monitoring No 
Point-in-Time Visibility No 
Reporting / Analytics No 
Virtual Machine Monitoring No 

Product Features

Engineering

2D Drawing No 
3D Modeling No 
Chemical Engineering No 
Civil Engineering No 
Collaboration No 
Design Analysis No 
Design Export No 
Document Management No 
Electrical Engineering No 
Mechanical Engineering No 
Mechatronics No 
Presentation Tools No 
Structural Engineering No 

Alternatives

Alternatives

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Elastic APM

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