Algomox MLOps.


Develop, Integrate, Deploy, and Manage machine learning models all from a single platform. The Algomox MLOps Platform enables machine learning model management, automated machine learning model development, data pipeline management, and machine learning model performance monitoring with its three platforms - the Data Pipeline Manager, the Cognitive Modeling Studio and the Cognitive ModelOps Engine.



MLOps

Algomox MLOps Platform helps you to automate your feature engineering tasks, develop your machine learning and deep learning models with AutoML, handle the data management with DataOps and run and serve your AI pipelines with ModelOps.

How does

Algomox MLOps Platform

helps you?

Our AutoML, ModelOps, and DataOps capabilities free up considerable bandwidth of your data scientists, machine learning engineers, DataOps engineers, and AI reliability engineers, and they can focus on other priorities and innovation projects.


1

AutoML with CMS

Algomox Cognitive Modeling Studio builds better models faster. It uses advanced AutoML and hyperparameter tuning techniques to get your model ready for deployment in a day and save you up to 95% of your development and model training time.

The Algomox AutoML solution can build machine learning and deep learning models for any use case.
2

ModelOps with CME

Algomox Cognitive ModelOps Engine helps you to predict and analyze your data. This product enables you with an automated AI pipeline management capability with model performance monitoring and automatic retraining. This solution helps you save operational cost up to 80%.

ModelOps becomes easy with drift monitoring, easy pipeline management, and accuracy and performance.
3

DataOps with DPM

Algomox Data Pipeline Manager helps you to integrate your enterprise data from the myriad of batches and streaming sources to your AI pipeline with few clicks and simple configurations and save up to 60% of the time and effort compared with developing several modules for data collection.

Algomox brings the best in DataOps for efficient data integration.