ML CUBE PLATFORM
AI Supervision Tool to prevent AI Obsolescience
AI Supervision Tool to prevent AI Obsolescence
ML cube Platform is a B2B MLOps Tool for real-time life cycle optimisation of Artificial Intelligence applications designed to prevent algorithms obsolescence.
UNIQUE FEATURES
AI Supervsion and Observability
MONITORING
Monitoring activity means continuous analysis of data incoming from the production environment to assess the status of the application that uses Artificial Intelligence models.
THREATS
Because of the dynamic nature of the environment in which AI models operate, data are subject to changes and drifts lead to AI model performance degradation.
UP TO DATE
ML cube Platform monitors for data and model drifts, alerting users. The Retraining module selects the best retraining samples for drift management.
MONITORING
Monitoring activity means continuous analysis of data incoming from the production environment to assess the status of the application that uses Artificial Intelligence models.
THREATS
Because of the dynamic nature of the environment in which AI models operate, data are subject to changes and drifts lead to AI model’s performance degradation.
UP TO DATE
ML cube Platform monitors for data and model drifts, alerting users. The Retraining module selects the best retraining samples for drift management.
CONSTANT ANALYSIS
Tackling Drift with Precision
DEAL WITH DATA DRIFTS
Data drift can be a silent revenue killer. When your machine learning models deteriorate, your application’s performance and profits take a hit.
AVOID OUTDATED SOLUTIONS
Traditional solutions often involve defining custom thresholds with the risk of not detecting drifts in time or being sensible to outliers.
IMPROVE
Thanks to the collaboration with Politecnico di Milano, ML cube Platform always employs state of the art algorithms, leveraging on the latest research advances.
WE GOT YOUR BACK
Algorithms analyze production data as soon as it arrives in order to spot data distribution discrepancies or AI models inefficiencies immediately.
CONSTANT ANALYSIS
Tackling Drift with Precision
DEAL WITH DATA DRIFTS
Data drift can be a silent revenue killer. When your machine learning models deteriorate, your application’s performance and profits take a hit.
AVOID OUTDATED SOLUTIONS
Traditional solutions often involve defining custom thresholds with the risk of not detecting drifts in time or being sensible to outliers.
IMPROVE
Thanks to the collaboration with Politecnico di Milano, ML cube Platform always employs state of the art algorithms, leveraging on the latest research advances.
WE GOT YOUR BACK
Algorithms analyze production data as soon as it arrives in order to spot data distribution discrepancies or AI models inefficiencies immediately.
CONTINUOUS IMPROVEMENT
ML cube Platform Retraining:
The Ultimate Data Drift Solution
ADDRESS DATA DRIFT EFFECTIVELY WITH ML CUBE PLATFORM
Advanced data modelling and Transfer Learning techniques allow ML cube Platform to compute high quality Importance Scores over all the provided data, leveraging all the available information and reducing the time to have a consistent new retraining dataset.
ENCHANCE COST OPTIMIZATION WITH RETRAINING COST MODEL TOOL
Link your AI models performance with your KPIs to close the gap
between Data Science and Business. The Retraining Cost Model Tool provide a unique view on retraining and its implications allowing you to decide and to know the best timing to execute retraining, based on the quality the AI models will have.
ADDRESS DATA DRIFT EFFECTIVELY WITH ML CUBE PLATFORM
Advanced data modelling and Transfer Learning techniques allow ML cube Platform to compute high quality Importance Scores over all the provided data, leveraging all the available information and reducing the time to have a consistent new retraining dataset.
ENCHANCE COST OPTIMIZATION WITH RETRAINING COST MODEL TOOL
Link your AI models performance with your KPIs to close the gap
between Data Science and Business. The Retraining Cost Model Tool provide a unique view on retraining and its implications allowing you to decide and to know the best timing to execute retraining, based on the quality the AI models will have.
ACROSS YOUR ORGANIZATION
Pursue Business Excellence
Unlocking Data-Driven Decisions Across Your Organization
TAILORED DATA INTELLIGENCE
ML cube Platform isn’t just for Data Scientists; it’s designed with business-focused professionals in mind.
COLLABORATIVE ANALYTICS
Our Retraining Cost Model Tool helps you weigh the costs of a sub-optimal model against the benefits of retraining, empowering you to take informed decisions.
AIM TO THE TOP
Dive into your data’s impact on your business KPIs with our Business KPI Task Attribution tool. Understand which tasks drive success and where improvements are needed.
BEYOND MONITORING
Advanced Additional Features
Advanced Additional Features
Contact us to schedule a free call and learn more how to improve your AI models
Expert Learning: Precision in Model Inference
With the Expert Learning module, ML cube Platform elevates model inference to a new level of precision and adaptability.
NEW STANDARDS
In situations with multiple Artificial Intelligence models, ML cube Platform offers a game-changing solution combining their prediction according to their behaviour.
QUALITY CHECK
Expert Learning continuously monitors model performance, assigning quality weights to optimize predictions.
ALWAYS ON TOP
Utilize these quality weights to improve predictions or select the best model for the job, boosting overall performance.
Elevate Your Models with Active Learning
These options bring fresh data and insights to your models, enhancing their performance and predictive accuracy.
RELABELING
Do not waste your data when they become outdated. The Relabelling module selects old data to be relabelled allowing you to use them once again.
SYNTHETIC ACTIVE LEARNING
Ask the ML cube Platform to create and provide you synthetic data to use in the retraining dataset reducing costs to collect real ones.
CLUSTERED ACTIVE LEARNING
When real data are needed, ML cube Platform suggests you regions of the data space to reduce the AI model uncertainty.
MLOPS ECOSYSTEM
Seamless Integration
Seamless Integration
ML cube Platform is a multi-cloud product part of the MLOps Ecosystem allowing an easy integration with existing solutions in the MLOps world.
ML CUBE PLATFORM
Facts
We are integrated with all the MLOps Platforms and Data Storage Tools
We support any kind of Machine Learning model
ML cube Platform is part of the MLOps Ecosystem, providing you simple connectors to your data and MLOps platforms.
ML cube Platform does not need anything of your ML/AI Models but its predictions.
We care about the value of your data
Work with all Data types
ML cube Platform monitors for data deviations. It does not need context or meaning of your data letting you to anonymize them to use our services.
ML cube Platform has an extensive catalog of monitoring algorithms and retraining techniques that easily adapt with different data types.
ML CUBE PLATFORM
Facts
We are integrated with all the MLOps Platforms and Data Storage Tools
ML cube Platform is part of the MLOps Ecosystem, providing you simple connectors to your data and MLOps platforms.
We support any kind of Machine Learning model
ML cube Platform does not need anything of your ML/AI Models but its predictions.
We care about the value of your data
ML cube Platform monitors for data deviations. It does not need context or meaning of your data letting you to anonymize them to use our services.
Work with all Data types
ML cube Platform has an extensive catalog of monitoring algorithms and retraining techniques that easily adapt with different data types.