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What is Fountain9 Kronoscope?

Stay ahead of the changing preferences of your clientele by utilizing accurate demand forecasts and stock-out predictions. Our innovative platform, Kronoscope, consistently tracks demand fluctuations, allowing for swift responses that prevent overstocking while guaranteeing that customers can always access the products they desire. By employing a blend of sophisticated machine learning and deep learning techniques, Kronoscope generates a customized model for each SKU across numerous stores, warehouses, or distribution channels. Our specialized algorithms identify diverse patterns, including seasonality, cannibalization, and substitution effects, which significantly improves the precision of our forecasts. There is no requirement for manual interventions, as the models independently retrain to adapt to new demand dynamics, detect anomalies, and reduce historical variability. Furthermore, Kronoscope provides natural language insights into unusual occurrences, major drivers of demand shifts, and high-impact products, among other critical data. You can also refine your demand predictions by analyzing how promotions, marketing efforts, and various other operational factors influence customer demand. This all-encompassing strategy ensures that your inventory management practices stay in sync with the most current market trends and consumer behaviors. Ultimately, Kronoscope empowers businesses to make informed decisions, fostering a more responsive and efficient supply chain.

What is Auger.AI?

Auger.AI offers a robust solution aimed at ensuring the accuracy of machine learning models. Our Machine Learning Review and Monitoring (MLRAM) tool plays a crucial role in keeping your models' precision consistent over time. It also evaluates the return on investment for your predictive analytics efforts! MLRAM's compatibility with any machine learning technology stack enhances its flexibility and adaptability. Failing to regularly assess the accuracy of your machine learning system lifecycle could lead to financial losses due to inaccurate predictions. Additionally, the ongoing requirement for model retraining can be expensive and may not resolve issues related to concept drift. MLRAM provides substantial advantages for both data scientists and business stakeholders, including features such as accuracy visualization graphs, performance alerts, anomaly detection, and automated optimized retraining. The process of integrating your predictive model with MLRAM is incredibly straightforward, requiring just a single line of code. We also offer a free one-month trial of MLRAM for qualifying users. With Auger.AI, you can leverage the most reliable AutoML platform available, empowering your organization to enhance its predictive capabilities to the fullest. This comprehensive approach ensures that your machine learning initiatives remain efficient and cost-effective over time.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
TensorFlow

Integrations Supported

Amazon Web Services (AWS)
Google Cloud Platform
Microsoft Azure
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$200 per month
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

Fountain9

Date Founded

2019

Company Location

India

Company Website

www.fountain9.com

Company Facts

Organization Name

Auger.AI

Date Founded

2019

Company Location

United States

Company Website

auger.ai/

Categories and Features

Demand Planning

Capacity Planning
Data Visualization
Historical Reporting
Inventory Optimization
Planned vs Actual Tracking
Product Introduction Planning
Promotions Management
Replenishment Management
Sales Forecasting
Supply Forecasting

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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