In the age of artificial intelligence, there are more and more players competing for the most accurate predictive models, able to forecast various trends in retail. However, when it comes to their implementation on a industrial scale, managing lots of predictive models can become one of the major challenges.

If you are a large retailer, it is imperative that you make daily predictions of sales of hundreds of products per store, in a number of stores. In order to achieve the highest prediction accuracy, you must build a separate predictive model for every product in each store, until you get stuck with tons of models you are no longer able to manage.

To tackle these issues, we have developer Foxtail MLOps, an automated machine learning system for production, management, and deployment of predictive models on an industrial scale.

Foxtail MLOps enables you to automatically create and maintain a large number of machine learning models in a reasonable timeframe and with minimal engagement.

Thousands of predictive models
Challenges in retail


Overstocks and out-of-stocks cost retailers $1.1 trillion globally.
One way you can tackle this problem is by using Artificial Intelligence for predictive purposes.
However, this approach is connected to a number of challenges.
Building a ML models is radically different from building traditional software applications.
It involves different activities, different workflows, and different skillsets than a traditional software development.

Primary activities become the preparation of datasets, the establishment of the overall parameters, and the evaluation and monitoring of the model's performance, once deployed.
At present, ML practitioners generally manage their workflows in adhoc ways.
This approach is not sustainable or scalable for the production-grade machine learning deployments.

BlackFox solution


Foxtail MLOps is a platform that consists of two modules:

  • the module for the distributed large-scale model creation, and
  • the user application for simple and intuitive management of predictive models.
The automatically created predictive models are stored in the model storage and are periodically updated with newly acquired data, ensuring that the models always reflect the actual market situation.

This approach drastically reduces the time and the effort required to develop and manage machine learning models and ensures that the most accurate predictions are continuously available.

Foxtail MLOps platform helps you bypass the most significant obstacles in implementing machine learning in your business. It empowers you to fully automate production, management, and deployment of predictive models streamlined to serve your needs.