Alibi

Open-source library for ML model inspection and interpretation.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is Alibi?

Alibi is an open-source Python library that enables developers to inspect and interpret machine learning models, enhancing transparency and trust in AI systems.

Key differentiator

Alibi stands out as a comprehensive open-source library for enhancing the transparency and trustworthiness of machine learning models through advanced interpretability techniques.

Capability profile

Strength Radar

Model explanatio…Drift detection …Feature importan…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Model explanations using SHAP, LIME, and other techniques.

Drift detection for monitoring model performance over time.

Feature importance analysis to understand model decisions.

Fit analysis

Who is it for?

✓ Best for

Teams needing to understand the decisions made by their ML models.

Projects where model interpretability is critical for regulatory compliance.

Developers looking to monitor and maintain deployed machine learning systems.

✕ Not a fit for

Applications requiring real-time interpretation of large-scale data streams.

Use cases that do not require or benefit from model explainability.

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with Alibi

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →