Source available Python libraries for performance model monitoring

Enable your MLOps team with two powerful source available Python libraries for post-deployment monitoring to ensure better reliability in your applications. 

Alibi Detect helps ensure confidence with performance monitoring

Alibi Explain helps teams gain ‌richer insights with model explainers and predictions

MLOps shouldn't stop at deployment

Make your machine learning efforts more reliable and build confidence in your deployed models with tools like enhanced outlier, adversarial and drift detection.

Take control of model performance with advanced drift detection

Notice changes in data dynamics & define whether detected drift will cause a decrease in model performance.

Discover critical anomalies in input and output data using outlier detection

Alert business units and users when seeing unexpected behavior.

Adversarial detection ensures that models perform consistently

Return the score that indicates the presence of features & instances that trick the model outcome.

Start Now

Start using Alibi Detect today through GitHub. You’ll only need a license for production use. It’s free for all non-production and academic uses. 

Features

Workflows

Workflows

Front-end deployment of models, explainers and canaries means non-Kubernetes experts can deploy ML models and testing can be done in live environments.

Model management

Model management

Metrics and dashboards can monitor models to improve performance and rapidly communicate errors for easy debugging.

Model confidence

Model confidence

Model explainers mean you can understand and adjust what features are influencing the model and anomaly detection can flag drifts in data and alert users to adversarial attacks.

Stack stability

Stack stability

Backwards compatibility, rolling updates and full SLA alongside maintained integrations with all frameworks and clouds means a seamless install and reliable infrastructure.

MLOps shouldn't stop at deployment

Get the most out of your deployed models with added transparency and control over model decisions, fostering trust and understanding through clear explanations for predictions.

Ensure stability of model performance

When your data changes so can your models predictions. Ensure accuracy by monitoring alteration.

Strengthen intuition for feature selection

Gain insights into how features influence model performance.

Derive a set of features and attributes for consistent prediction

Return the score that indicates the presence of features & instances that trick the model outcome.

Start Now

Start using Alibi Explain today through GitHub. You’ll only need a license for production use. It’s free for all non-production and academic uses. 

Highlights

Feature Alteration

Feature Alteration

See how prediction changes and ensure stability of model performance against changing data.

Feature Impact

Feature Impact

Alibi indicates how features influence model performance, strengthening intuition for feature selection.

Necessary Features

Necessary Features

Focus on critical data attributes and features by deriving a set of features and attributes for consistent prediction.

Feature Attribution

Feature Attribution

Build confidence in integrity of model performance when Alibi illustrates prediction dynamics when features change

Join our Community

Meet MLOps experts, access support, and stay ahead of the AI curve.

Try before you buy

Explore how Alibi will improve your MLOps projects for free before putting anything into production.

Do you require a commercial license?

Take our quick 10-second survey to discover if your organization requires a commercial license for Seldon Alibi. Gain clarity into licensing obligations and ensure compliance with just a few simple questions.

Click below to take the survey.

Maximize the potential of your MLOps

Ready to put to put Alibi’s Python libraries to work? Any in-production use of Alibi requires the purchase of a business source license.

Alibi is available to purchase with credit card or invoice for production access to the entire Alibi Detect and Explain Python library. 

£15,000 / €17,250  / $18,000 paid annually