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Description
Minimize false positives and leverage machine learning (ML) to effectively identify anomalies in business performance indicators. Investigate the underlying causes of these anomalies by clustering similar outliers together for analysis. Provide a summary of these root causes and prioritize them based on their impact. Ensure a smooth integration with AWS databases, storage services, and external SaaS platforms for comprehensive metrics monitoring and anomaly detection. Set up automated alerts and responses tailored to the detection of anomalies. Utilize Lookout for Metrics, which employs ML to both discover and analyze anomalies in business and operational datasets. The challenge of recognizing unexpected anomalies is compounded by the limitations of traditional manual methods that are prone to errors. Lookout for Metrics simplifies the detection and diagnosis of data inconsistencies without requiring any expertise in artificial intelligence (AI). Monitor irregular fluctuations in subscriptions, conversion rates, and revenue to remain vigilant about sudden market shifts, ultimately enhancing strategic decision-making capabilities. By adopting these advanced techniques, businesses can improve their overall performance management and response strategies.
Description
We've provided a few typical examples, yet the compilation is certainly not comprehensive. Our dedicated solution engineering team is ready to collaborate with you in tailoring Kolena to fit your specific workflows and business goals. Relying solely on aggregate metrics can be misleading, as unanticipated model behavior in a production setting is often the standard. Existing testing methods tend to be manual, susceptible to errors, and lack consistency. Furthermore, models are frequently assessed using arbitrary statistical metrics, which may not align well with the actual objectives of the product. Monitoring model enhancements over time as data changes presents its own challenges, and strategies that work well in a research context often fall short in meeting the rigorous requirements of production environments. As a result, a more robust approach to model evaluation and improvement is essential for success.
API Access
Has API
API Access
Has API
Integrations
AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon S3
Amazon Simple Notification Service (SNS)
Python
Integrations
AWS Lambda
Amazon CloudWatch
Amazon Redshift
Amazon S3
Amazon Simple Notification Service (SNS)
Python
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
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
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/lookout-for-metrics/
Vendor Details
Company Name
Kolena
Founded
2021
Country
United States
Website
www.kolena.io
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
