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Description
Anticipate issues before they arise by utilizing an Azure AI anomaly detection service. This service allows for the seamless integration of time-series anomaly detection features into applications, enabling users to quickly pinpoint problems. The AI Anomaly Detector processes various types of time-series data and intelligently chooses the most effective anomaly detection algorithm tailored to your specific dataset, ensuring superior accuracy. It can identify sudden spikes, drops, deviations from established patterns, and changes in trends using both univariate and multivariate APIs. Users can personalize the service to recognize different levels of anomalies based on their needs. The anomaly detection service can be deployed flexibly, whether in the cloud or at the intelligent edge. With a robust inference engine, the service evaluates your time-series dataset and automatically determines the ideal detection algorithm, enhancing accuracy for your unique context. This automatic detection process removes the necessity for labeled training data, enabling you to save valuable time and concentrate on addressing issues promptly as they arise. By leveraging advanced technology, organizations can enhance their operational efficiency and maintain a proactive approach to problem-solving.
Description
Prequel is a collaborative platform focused on identifying and managing issues, specifically crafted for fast-paced engineering teams aiming to deliver more dependable software. By harnessing collective failure insights from various platforms such as GitHub discussions, Discord conversations, and post-mortem analyses, Prequel converts this data into a versatile repository of problem detectors that address open-source bugs, configuration errors, and software design flaws. The system boasts accurate, deterministic detection capabilities, minimizing dependence on unreliable threshold or anomaly-based notifications while functioning in real-time to pinpoint problems at their inception. With a rapid installation time of just ten minutes that avoids the need for intricate integrations or code changes, Prequel fits effortlessly into current workflows. Its architecture operates within the cluster, utilizing community knowledge to process a continuous influx of detailed data, all while maintaining the confidentiality and integrity of the information within the cluster. This approach not only enhances security but also streamlines the identification of potential issues, allowing teams to focus on improving their software development processes.
API Access
Has API
API Access
Has API
Integrations
Microsoft Azure
Amazon Web Services (AWS)
Azure AI Metrics Advisor
Bing
CTM360
Compliance Warden
Crestwood Cloud
Discord
GitHub
Google Cloud Platform
Integrations
Microsoft Azure
Amazon Web Services (AWS)
Azure AI Metrics Advisor
Bing
CTM360
Compliance Warden
Crestwood Cloud
Discord
GitHub
Google Cloud Platform
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
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/products/ai-services/ai-anomaly-detector/
Vendor Details
Company Name
Prequel
Website
www.prequel.dev/
Product Features
Product Features
Bug Tracking
Backlog Management
Filtering
Issue Tracking
Release Management
Task Management
Ticket Management
Workflow Management