AI Tools·Standings
AI Model Explainability Software
AI model explainability software helps people examine how a model reaches its outputs; compare the signal score and the tools’ fit with your needs.
The board shows API, open-source and free-tier marks. Compare tools by feature attribution, counterfactual explanations, fairness analysis, audit reports, deployment options and supported model types.
- 29 platforms
- 23 with a free tier
- Checked 9 Oct 2026
- 1 AAequitasdssg.github.io
A free bias-audit toolkit compares model outcomes across groups and visualizes disparities.
- 2 AAIX360aix360.res.ibm.com
AIX360 is an open-source Python toolkit for interpreting and explaining datasets and machine-learning models.
- 3 CCaptumcaptum.ai
A free, open-source PyTorch library shows which features contribute to a model's output.
- 4 FA
Fiddler AIfiddler.aiAn AI monitoring platform evaluates models and agents and tracks more than 100 diagnostics and metrics.
- 5 A
Arthurarthur.aiA hosted or self-managed platform traces AI agent activity and checks it against safety policies.
- 6 Aauditormodeloriented.github.io
A free R package compares models, checks fit, and finds outliers with diagnostic scores and plots.
- 7 AAlibigithub.com
A Python library offers local and global explanations for classification and regression models.
- 8 AAArize AIarize.com
An AI monitoring service explains model outcomes and tracks feature importance and fairness metrics.
- 9 EExplainerDashboardexplainerdashboard.readthedocs.io
A free dashboard explains scikit-learn-compatible models with feature attribution.
- 10 VA
Vertex AI Vector Searchcloud.google.comA search service for finding similar items, with numeric and text filters and Google Cloud connections.
- 11 DDiCEinterpret.ml
- 12 EELI5eli5.readthedocs.io
- 13 Ffastshapbgreenwell.github.io
- 14 IInterpretMLinterpret.ml
A free tool explains glass-box and black-box models and supports feature attribution and fairness analysis.
- 15 OOmniXAIgithub.com
- 16 PPDPboxgithub.com
- 17 RAResponsible AI Toolboxresponsibleaitoolbox.ai
- 18 Ttreeshapmodeloriented.github.io
A free, self-hosted tool for showing feature effects in tree models.
- 19 SA
SAS Advanced Analyticssas.comSAS Viya is a cloud-native data and AI platform for connecting data, building and governing models, and operationalizing decisions.
- 20 MmodelStudiomodelstudio.drwhy.ai
A free web tool provides feature attribution for model explanations.
- 21 SShapashshapash.readthedocs.io
A free, self-hosted web tool for feature explanations and audit reports.
- 22 WIWhat-If Toolpair-code.github.io
A free web tool for feature explanations, counterfactuals and fairness analysis.
- 23 ZZenozenoml.com
- 24 FFairlearnfairlearn.org
A free tool checks fairness in binary and multiclass classification and regression models.
- 25 DDALEXdalex.drwhy.ai
Places #1, #2, #3, #4, #5 on this board are open to sponsors. Take #1 · Other ways to advertise
How to choose
Which platforms does it need to run on?
Start with where you plan to run the software: Linux, macOS, Windows, the web, an API or a self-hosted setup. Compare the platform marks with your existing environment.
An API is a way for software to communicate with other software. Self-hosted means running the tool on infrastructure you manage.
Which kinds of explanations do I need?
Choose based on the questions you need to answer. Compare feature attribution, counterfactual explanations, fairness analysis and audit reports.
Feature attribution shows how features contributed to an output. Counterfactual explanations describe what could change an outcome. Check the listed capabilities rather than assuming a tool covers every analysis type.
How should I compare free plans and paid pricing?
Check the free-plan mark and the paid-from price, then confirm the terms with the provider. Pricing on request means a listed starting price is not available in the supplied details.
Arize AI lists a free plan and paid pricing from $50 per month; Arthur lists a free plan and pricing from $60 per month.
Which model types does it support?
Compare the supported model types against the models you need to explain. The category comparison includes this field, but the supplied details do not name specific supported types.
Questions
What does AI model explainability software do?
It helps examine how a model reaches its outputs. Compare feature attribution, counterfactual explanations, fairness analysis and audit reports.
How do I choose explainability software for my platform?
Check the platform marks for Linux, macOS, Windows, web, API or self-hosted use against where you plan to run it.
Is AI model explainability software free?
The board compares free plans and paid-from pricing. Confirm current plan terms with the provider.
What is a counterfactual explanation?
It describes what could change an outcome. The board compares this capability alongside feature attribution, fairness analysis and audit reports.
Some top positions on this board can be paid placements, standing where they were sold. The facts on each platform are not for sale. How we rank · Disclosure