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features
design
support

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Write a Review

Description

Auger.AI delivers the most comprehensive solution for maintaining the accuracy of machine learning models. Our MLRAM tool (Machine Learning Review and Monitoring) guarantees that your models maintain their accuracy over time. It even assesses the return on investment for your predictive models! MLRAM is compatible with any machine learning technology stack. If your ML system lifecycle lacks ongoing measurement of model accuracy, you could be forfeiting profits due to erroneous predictions. Additionally, frequently retraining models can be costly and may not resolve issues caused by concept drift. MLRAM offers significant benefits for both data scientists and business professionals, featuring tools such as accuracy visualization graphs, performance and accuracy notifications, anomaly detection, and automated optimized retraining. Integrating your predictive model with MLRAM requires just a single line of code, making the process seamless. We also provide a complimentary one-month trial of MLRAM for eligible users. Ultimately, Auger.AI stands out as the most precise AutoML platform available, ensuring that your machine learning initiatives are both effective and efficient.

Description

Safeguard business service-level agreements by utilizing dashboards that enable monitoring of service health, troubleshooting alerts, and conducting root cause analyses. Enhance mean time to resolution (MTTR) through real-time event correlation, automated incident prioritization, and seamless integrations with IT service management (ITSM) and orchestration tools. Leverage advanced analytics, including anomaly detection, adaptive thresholding, and predictive health scoring, to keep an eye on key performance indicators (KPIs) and proactively avert potential issues up to 30 minutes ahead of time. Track performance in alignment with business operations through ready-made dashboards that not only display service health but also visually link services to their underlying infrastructure. Employ side-by-side comparisons of various services while correlating metrics over time to uncover root causes effectively. Utilize machine learning algorithms alongside historical service health scores to forecast future incidents accurately. Implement adaptive thresholding and anomaly detection techniques that automatically refine rules based on previously observed behaviors, ensuring that your alerts remain relevant and timely. This continuous monitoring and adjustment of thresholds can significantly enhance operational efficiency.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AXYVOR No 
Amazon Web Services (AWS) Yes 
BlueCat Gateway No 
CloudApper iPaaS No 
CloudFabrix No 
Evolven No 
Google Cloud Platform Yes 
Microsoft Azure Yes 
SAP Store No 
Splunk User Behavior Analytics No 
TensorFlow Yes 
The Galileo Suite No 

Integrations

AXYVOR Yes 
Amazon Web Services (AWS) No 
BlueCat Gateway Yes 
CloudApper iPaaS Yes 
CloudFabrix Yes 
Evolven Yes 
Google Cloud Platform No 
Microsoft Azure No 
SAP Store Yes 
Splunk User Behavior Analytics Yes 
TensorFlow No 
The Galileo Suite Yes 

Pricing Details

$200 per month
Free Trial Yes 
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 Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Auger.AI

Founded

2019

Country

United States

Website

auger.ai/

Vendor Details

Company Name

Cisco

Founded

1984

Country

United States

Website

www.splunk.com/en_us/products/it-service-intelligence.html

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

IT Alerting

Alert Noise Reduction No 
Alert Routing No 
Dynamic Notifications No 
Enriched Incident Context No 
Escalation Policies No 
Incident History Audit No 
Multi-User Alerting No 
Multiple Alert Types No 
On-Call Management No 
Rich HTML Email Notifications No 

IT Service

Contract Management No 
IT Asset Management No 
Incident Management No 
Knowledge Management No 
Release Management No 
Self Service Portal No 
Service Catalog No 
Service Reporting No 
Ticket Management No 

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