Core Features

A deep dive into the technology shaping the future of fair and transparent AI.

Real-Time Bias Detection

Go beyond simple post-deployment checks. Fairmind integrates directly into your data pipelines to analyze model behavior in real-time. Our system detects subtle and emergent biases across multiple protected attributes (e.g., race, gender, age) using a suite of advanced statistical tests. Receive instant, actionable alerts with root-cause analysis, allowing you to mitigate fairness issues before they impact users or lead to regulatory penalties.

  • Real-time stream processing for immediate feedback
  • Support for 20+ fairness metrics including Disparate Impact and Equalized Odds
  • Automated audit trails and one-click compliance reports (GDPR, AI Act, etc.)
  • Slice-based analysis to identify bias in specific data segments
Real-time bias monitoring simulation

Watch our bias detection system in action - real-time monitoring and alerts
Bias detection alert

Bias detection alert

Detailed fairness report

Detailed fairness report

Advanced Explainability (XAI)

Turn your AI's black box into a transparent glass box. Fairmind provides a powerful, interactive suite of Explainable AI (XAI) tools. We go beyond basic feature importance by offering local (per-prediction) and global (whole-model) explanations through techniques like SHAP, LIME, and Integrated Gradients. The interactive dashboards allow both technical and non-technical users to explore 'what-if' scenarios, understand decision drivers, and build genuine trust in your AI systems.

  • Native support for SHAP, LIME, and Integrated Gradients
  • Interactive 'what-if' analysis and counterfactual explanations
  • One-click export of visual and text-based explanation reports
  • Model-agnostic architecture for any framework (TensorFlow, PyTorch, etc.)
Feature importance visualization

Feature importance visualization

Model decision explanations

Model decision explanations

Continuous Monitoring & Drift Detection

A model's performance on day one is not guaranteed on day 100. Fairmind offers robust, continuous monitoring to ensure your models remain accurate, fair, and reliable in the wild. We automatically track a full spectrum of metrics, including data drift (changes in input data distribution), concept drift (changes in relationships between inputs and outputs), and operational health. Proactive alerts give you a heads-up on performance degradation, allowing for timely retraining and preventing silent model failure.

  • Holistic performance monitoring (Accuracy, Precision, Recall, F1, AUC)
  • Advanced statistical methods (e.g., Kolmogorov-Smirnov, PSI) for drift detection
  • Customizable alert channels (Slack, Email, Webhooks) and retraining triggers
  • Comparison dashboards to track model performance across versions
Performance monitoring dashboard

Performance monitoring dashboard

Drift detection metrics

Drift detection metrics