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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

LotusEye offers a cloud-based service for AI-driven anomaly detection that autonomously acquires knowledge of standard behavior from numerical or sensor data provided in CSV format and consistently computes anomaly scores to identify irregularities that could signify faults or unforeseen activities, delivering notifications and visual analytics without necessitating any machine learning expertise from users. The service accommodates both wide-format CSV files, where every row corresponds to sensor readings at specific timestamps, and long-format CSV files that include timestamp, sensor name, and value columns, allowing users to upload their data either through a simple drag-and-drop interface or via an API for automated processing on a scheduled basis. Once an AI model is trained using data from normal operations, users can then input test data to obtain calculated anomaly scores and view these results on dashboards featuring time-series graphs, threshold markers, and filtering options, which assist teams in identifying unusual trends and probing potential concerns swiftly. This streamlined process enhances operational efficiency and empowers teams to act on insights generated by the platform.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Azure AI Metrics Advisor
Bing
CTM360
Compliance Warden
Crestwood Cloud
Google Sheets
Microsoft Azure
Microsoft Excel
Microsoft Office 2021
Qualio
Rayven
groundcover

Integrations

Azure AI Metrics Advisor
Bing
CTM360
Compliance Warden
Crestwood Cloud
Google Sheets
Microsoft Azure
Microsoft Excel
Microsoft Office 2021
Qualio
Rayven
groundcover

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$13 per 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

Microsoft

Founded

1975

Country

United States

Website

azure.microsoft.com/en-us/products/ai-services/ai-anomaly-detector/

Vendor Details

Company Name

LotusEye

Country

Japan

Website

lotuseye.co.jp/

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