Overview

Agent Trust Score is a comprehensive framework for evaluating both data integrity and model performance across the AI lifecycle. It measures systems across eight dimensions — diversity, timeliness, security, discoverability, consumability, accuracy, fairness, and explainability — and generates a quantifiable trust score (0–100). Based on this score, AI systems are classified from Not Trustworthy to Excellent, helping enterprises benchmark and continuously strengthen trust in AI.

Key Capabilities

Continuous Trust Assurance – Always-on monitoring of AI systems across data and model dimensions.
Bias & Fairness Audits – Detect, measure, and mitigate biases in datasets and models.
Explainability & Transparency – Provide interpretable insights into model decision-making.
Regulatory Compliance – Built-in alignment with Microsoft RAI, EU AI Act, and GDPR standards.
Audit-Ready Reporting – Instantly export compliance and risk assessment reports.
Azure Native Integration – Seamless monitoring across Azure Machine Learning, Data Lake, DevOps, and Arc in hybrid or multi-cloud environments.

Business Impact

Improved AI Reliability – Quantifies system trustworthiness to reduce risks.
Regulatory Confidence – Ensures compliance with global AI governance standards.
Operational Efficiency – Automates audits and risk assessments, saving time and resources.
Enterprise Trust Building – Enhances transparency, accelerating enterprise-wide AI adoption.

Intended Users

AI/ML Teams & Data Scientists
Responsible AI Officers
Risk & Audit Teams
Compliance Managers
Product Owners & Executives

Industries

Agent Trust Score is valuable for sectors where AI accountability, transparency, and compliance are critical:

Financial Services
Healthcare
Government & Public Sector
Retail & E-Commerce
Technology & Cloud Providers

Agent Trust ScoreXenonStack

Agent Trust Score

XenonStack

Agent Trust Score

XenonStack

Agent Trust Score
XenonStack