Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Leverage machine learning on distributed datasets to achieve quicker insights and improved outcomes, all while avoiding the expenses, concentration risks, lengthy timelines, and privacy issues associated with centralizing data. The potential of machine learning algorithms is often hindered by the availability of a wide range of high-quality data sources. By unlocking access to a broader dataset and ensuring transparency regarding the impacts of various models, you can derive more meaningful insights. The process of securing approvals, consolidating data, and developing infrastructure can be time-consuming. However, by utilizing data in its original location and employing a federated and parallelized training approach, you can obtain trained models and useful insights at an accelerated pace. Furthermore, Devron's capability to access data in its original context eliminates the necessity for data masking and anonymization, significantly minimizing the burdens associated with data extraction, transformation, and loading. As a result, organizations can focus their resources on analysis and decision-making rather than infrastructure challenges.
Description
evoML enhances the efficiency of developing high-quality machine learning models by simplifying and automating the comprehensive data science process, enabling the conversion of raw data into meaningful insights in mere days rather than several weeks. It takes charge of vital tasks such as automatic data transformation that identifies anomalies and rectifies imbalances, employs genetic algorithms for feature engineering, conducts parallel evaluations of multiple model candidates, optimizes using multi-objective criteria based on custom metrics, and utilizes GenAI technology for generating synthetic data, which is especially useful for swift prototyping while adhering to data privacy regulations. Users maintain complete ownership of and can modify the generated model code, facilitating smooth deployment as APIs, databases, or local libraries, thereby preventing vendor lock-in and promoting clear, auditable workflows. Additionally, evoML equips teams with user-friendly visualizations, interactive dashboards, and detailed charts to detect patterns, outliers, and anomalies across various applications, including anomaly detection, time-series forecasting, and fraud prevention. With its robust features, evoML not only accelerates the modeling process but also empowers users to make data-driven decisions with confidence.
API Access
Has API
No
API Access
Has API
Yes
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Devron
Website
www.devron.ai/
Vendor Details
Company Name
TurinTech AI
Founded
2018
Country
United Kingdom
Website
www.turintech.ai/evoml
Product Features
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No