machine learning health monitoring

Monitor the health and fairness of all your live machine learning models from a central dashboard

ML models die quietly

Machine learning model predictions become less accurate over time due to unexpected changes in the real world. This can negatively affect your business KPIs and customer experience, resulting in churn.

It is difficult to measure the true accuracy of a model in production. Less than 5% of companies that employ AI technologies have solutions to monitor the health and performance of their models.

Sanau ML Analytics

Sanau ML Analytics monitors your machine learning models in production and notifies you if there are any factors that degrade their performance.

With the Sanau ML dashboard you can track all the metrics related to the health of your model.

It integrates into any existing infrastructure and runs either on cloud or on premises.

Track model impact on KPI with built in integrations with your existing tools

AI health management

Secure and centralized AI health management

Manage the quality, robustness and trustworthiness of all your machine learning models in production in one place

One central platform

Get a single dashboard that monitors the health of all your deployed machine learning models in production

Trustworthy and fair AI

Monitor your ML models for bias and prejudice and comply with regulation

Get alerted

Know when your ML model is due for retraining or if your model accuracy falls below a threshold

Fair AI

Comply with directives and regulation

There’s an increasing pressure from vendors supplying automated decision systems or products to comply.

Provide audit trail

Log ML predictions, model versions

Test predictions for bias

Understand how your models impact specific groups of users to reduce bias

Transparent AI

Explain models decisions and trace data used for predictions

Keep your machine learning models healthy

Monitor the health of your ML models in production from a central dashboard