Alibi Detect

Outlier and drift detection library for machine learning models.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is Alibi Detect?

Alibi Detect is an open-source Python library that provides tools for detecting outliers, adversarial attacks, and data drift in machine learning models. It helps maintain model performance by identifying anomalies in real-time.

Key differentiator

Alibi Detect stands out by offering a comprehensive set of tools for detecting outliers, adversarial attacks, and data drift in machine learning models, all within an open-source framework.

Capability profile

Strength Radar

Outlier detectio…Adversarial atta…Data drift detec…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Outlier detection for identifying unusual data points

Adversarial attack detection to protect models from malicious inputs

Data drift detection to monitor changes in input data distribution

Fit analysis

Who is it for?

✓ Best for

Teams that need to monitor their machine learning models for data drift in real-time.

Developers who want to protect their models from adversarial attacks.

Organizations requiring robust outlier detection capabilities.

✕ Not a fit for

Projects with very limited computational resources, as Alibi Detect requires significant processing power.

Applications where real-time anomaly detection is not critical.

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 Detect

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

View Setup Guide →