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What is evoML?

evoML significantly boosts the development efficiency of high-quality machine learning models by streamlining and automating the entire data science workflow, allowing the transformation of raw data into actionable insights in just days instead of weeks. It manages essential functions such as automated data transformation, which detects anomalies and corrects imbalances, implements genetic algorithms for effective feature engineering, runs simultaneous assessments of various model alternatives, optimizes using multi-objective criteria tailored to specific metrics, and leverages GenAI technology for the creation of synthetic data, proving invaluable for rapid prototyping while ensuring compliance with data privacy laws. Users retain full ownership and the ability to adjust the generated model code, which supports the seamless deployment of models as APIs, databases, or local libraries, thereby avoiding vendor lock-in and fostering transparent, traceable processes. Moreover, evoML equips teams with intuitive visualizations, engaging dashboards, and comprehensive charts that help in identifying trends, outliers, and anomalies across different contexts, such as fraud detection, time-series forecasting, and anomaly detection. By incorporating these powerful features, evoML not only speeds up the modeling journey but also empowers users to confidently engage in data-driven decision-making. Ultimately, this innovative platform fosters a more efficient and effective approach to leveraging data for strategic insights.

What is IBM Z Anomaly Analytics?

IBM Z Anomaly Analytics is an advanced software tool that identifies and categorizes anomalies, allowing organizations to tackle operational challenges proactively. By harnessing historical log and metric data from IBM Z, the tool creates a model that encapsulates standard operational behavior. This model is used to evaluate real-time data for any discrepancies that suggest abnormal activity. Subsequently, a correlation algorithm methodically organizes and assesses these anomalies, providing prompt alerts to operational teams about potential problems. In today's rapidly evolving digital environment, ensuring the availability of critical services and applications is vital. Businesses employing hybrid applications, particularly those running on IBM Z, face the growing challenge of pinpointing the root causes of issues due to rising costs, a lack of skilled labor, and changing user behaviors. By identifying anomalies within both log and metric data, organizations can proactively detect operational issues, thus averting costly incidents and facilitating smoother operations. Moreover, this robust analytics capability not only boosts operational efficiency but also fosters improved decision-making processes across organizations, ultimately enhancing their overall performance. As such, the integration of IBM Z Anomaly Analytics can lead to significant long-term benefits for enterprises striving to maintain a competitive edge.

Media

Media

Integrations Supported

IBM Z

Integrations Supported

IBM Z

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

TurinTech AI

Date Founded

2018

Company Location

United Kingdom

Company Website

www.turintech.ai/evoml

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/z-anomaly-analytics

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Categories and Features

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