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Enterprise-Grade AI Governance

Advanced AI Governance Platform

SHAP + LIME + Neo4j Knowledge Graph for comprehensive bias detection and compliance tracking

Advanced AI explainability and bias detection platform with SHAP, LIME, and Neo4j Knowledge Graph integration for comprehensive model transparency and governance.

SHAP
Feature Importance
LIME
Local Explanations
Neo4j
Knowledge Graph

Enterprise AI Governance

Comprehensive tools and frameworks for responsible AI deployment

SHAP Feature Importance

Advanced SHAP (SHapley Additive exPlanations) analysis for global feature importance and bias contribution across all model types.

LIME Local Explanations

LIME (Local Interpretable Model-agnostic Explanations) for instance-specific explanations and decision transparency.

Neo4j Knowledge Graph

Neo4j-powered causal relationship analysis and bias propagation tracking through complex model interactions.

Multi-Dimensional Analysis

Comprehensive bias detection across geographic, demographic, temporal, and cultural dimensions.

Model Transparency

Complete model lineage tracking and inheritance pattern analysis for regulatory compliance.

Real-time Monitoring

Live bias detection alerts and drift monitoring with automated compliance reporting.

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Join leading enterprises already using Fairmind to ensure their AI systems are fair, transparent, and compliant with regulatory standards.

Development Roadmap

Our journey to advance AI explainability and bias detection

Q1 2024

Completed

  • SHAP integration
  • Basic bias detection
  • Core dashboard

Q2 2024

Completed

  • LIME integration
  • Real-time monitoring
  • Advanced analytics

Q3 2024

Current

  • Neo4j Knowledge Graph
  • Multi-dimensional analysis
  • Enterprise deployment

Upcoming Features

Q4 2024

Advanced causal inference and automated bias mitigation

Q1 2025

Federated learning support and edge deployment

Q2 2025

AI model marketplace and collaborative governance

Q3 2025

Quantum-resistant explainability and advanced privacy