AIX360

At a glance

• Editor score
  9.1 / 10
• Pricing
  Free plan
• Best for
  Teams needing a broad, free XAI toolkit
• Free plan
  Yes
• Paid from
  None
• Feature attribution
  Yes
• Facts checked
  28 Sep 2026

• Where it wins

  • Offers local and global methods, including CEM, LIME, and SHAP
  • Includes explainers for tabular, text, image, and time-series data
  • Provides Ecertify plus faithfulness and monotonicity metrics

• Where it doesn't

  • Self-hosted library, not a hosted commercial service
  • Use requires working with a Python toolkit and its APIs
  • Support channels are limited to community resources and documentation

Our verdict on AIX360

AIX360 is an open-source Python toolkit for practitioners who need to inspect machine-learning models and datasets. Its methods span local and global explanations, direct and post-hoc approaches, and proxy explainability metrics. The toolkit supports tabular, text, image, and time-series data, making it relevant to teams with varied model and data types. Data scientists and other practitioners comfortable working with a library are its natural audience; it is not a ready-to-use hosted explanation service.

The breadth of methods is a central strength. Local post-hoc options include CEM, LIME, and SHAP, while ProtoDash and disentangled representations address data explanations. For time-series work, AIX360 includes TS-LIME, TS-ICE, and saliency maps. It also provides directly interpretable local and global methods, along with Ecertify for explanation certification and metrics for faithfulness and monotonicity. Tutorials, examples, and API documentation help practitioners explore these approaches. This range suits teams comparing explanation techniques across different data types, though organizations seeking one narrow, turnkey workflow may find a broad toolkit more than they need.

AIX360 is open source and self-hosted, with Windows, macOS, and Linux listed as supported platforms. That makes it a fit for teams that want to work with the library in their own environment rather than buy access to a hosted service. The tradeoff is that teams need to handle their own use of the toolkit and rely on community support and documentation. Choose AIX360 if flexibility across explanation methods matters and your team can work with Python libraries; consider an alternative if you need a managed service or vendor support channels beyond community resources and docs.

AIX360 pricing

AIX360 fact sheet

Alternatives to AIX360

• AArize AIProduction-focused explainability pairs feature attribution with fairness monitoring and model comparisons.8.5
• Fiddler AIA tracing and evaluation platform for teams debugging LLM and agent workflows.7.4
• IInterpretMLA self-hosted Python toolkit pairing interpretable EBMs with LIME and SHAP explanations.7.4

See all AIX360 alternatives →

AIX360 vs the competition

• AAAIX360 vs Arize AI
• AAIX360 vs Fiddler AI
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• ADAIX360 vs DALEX
• ARTAIX360 vs Responsible AI Toolbox

Compare AIX360 with any tool side by side →

Featured on iTechGuides

AIX360 is listed in our AI Model Explainability Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 9 Oct 2026 · How we research and update