TrustyAI
Explainability, bias detection and monitoring for AI models in production.
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What is this technology for?
Its role in production environments and why it is taught in our curriculums.
TrustyAI brings explainability, bias detection and drift monitoring to AI models in production — building trust in ML decisions for regulated environments.
What you will learn
The hands-on skills you will gain on this technology in our curriculums.
- Generate model explanations and feature attributions
- Detect bias and fairness issues
- Monitor model drift in production
- Produce audit-ready AI reports
Latest News & Ecosystem Updates
Recent innovations, major releases, and key industry milestones in the ecosystem.
TrustyAI v1.6: Model Explainability & Real-Time Bias Detection
Native EU AI Act compliance monitoring delivering continuous fairness tracking, data drift, and LIME/SHAP explainability.
AI Guardrails & Hallucination Mitigation for Enterprise LLMs
Automated input/output verification guardrails ensuring safe, compliant, and fact-grounded agentic workflows.
Featured in the curriculum
Find this technology in the following modules of our Red Hat certified curriculums.
AS300 — AI Platform Engineer
View curriculum →
Red Hat OpenShift AI (RHOAI)
AI267 · Module 7 — AS300
