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CrunchMetrics
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CrunchMetrics

Overview
Synopsis

CrunchMetrics is an advanced anomaly detection system, that leverages the combined power of statistical methods and AI-ML based techniques to sift through your data to identify incidents that are business critical in nature.

Category

Anomaly Detection System, Artificial Intelligence, Machine Learning, Deep Learning, Data Analytics, Business Intelligence

Sub Category

Telecommunications, Retail, E-commerce, Fintech

Features

Automated, real-time detection
Powered by AI,ML
Self-learning algorithms
Seamless integration
Flexible output channels
Vertical agnostic solutions

User Industry

Telecommunications,
Retail,
Fintech,
E-Commerce

Support

24/7 Chat Support,

Languages

English

Countries

North America, Europe, Africa, APAC, Middle East, Oceania

Company

CrunchMetrics is a division of Subex Digital LLP, a wholly owned subsidiary of Subex Limited.

URL

https://www.crunchmetrics.ai/

What is best?

Automated, real-time detection
Powered by AI,ML
Self-learning algorithms
Seamless integration

What are the benefits?

Identify anomalies that are hard to detect
Act on business-critical issues. Fast
Figure out newer areas to stay profitable

PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
8.5
Features & Functionality
7.6
7.9
Advanced Features
7.6
Integration
7.6
Performance
7.6
Customer Support
7.6
4.1
Implementation
Renew & Recommend
Bottom Line

CrunchMetrics examines historical data to understand and establish what is ‘normal’ behavior, and then constantly monitors data streams to single out ‘abnormal’ patterns, known as anomalies.

7.6
Editor Rating
6.8
Aggregated User Rating
1 rating
You have rated this

CrunchMetrics is an advanced anomaly detection system, that leverages the combined power of statistical methods and AI-ML based techniques to sift through your data to identify incidents that are business critical in nature. It examines historical data to understand and establish what is ‘normal’ behavior, and then constantly monitors data streams to single out ‘abnormal’ patterns, known as anomalies.

Further it analyses these anomalies in a contextual manner and correlates them with different data signals in the enterprise to understand if it is indeed a business-critical incident. Identified incidents are flagged in real-time, enabling stakeholders to act instantly, and thereby minimizing the potential impact on the business.

CrunchMetrics Pricing

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