AIValidator Validation Module

AIValidator® Validation Module, developed by CIMCON Software, is an automated test suite designed to deliver trustworthy AI models through comprehensive model testing, validation, and documentation. Drawing on 25 years of experience in Risk Management, CIMCON built AIValidator® to help organisations meet both business and regulatory requirements. The platform automatically identifies high-risk models by assigning a risk score to each model, covering a broad spectrum of tests from fairness, interpretability, and validity to code quality, privacy, and cybersecurity.

AIValidator® is suited for data science teams, model risk managers, and compliance professionals who need a no-code, structured approach to AI governance that aligns with the NIST AI Risk Management Framework.

Key Benefits

• Cut time spent on model development, testing, and validation through automation
• Automated risk scoring, code quality assessment, and model dependency analysis
• No-code inventory and workflow management for streamlined operations
• Evidence controls and compliance support through automated test results and supporting documentation
• Scan models and data for privacy risks and security vulnerabilities
• Aligned with the NIST AI Framework for responsible AI governance

Core Testing and Validation Features

• Code Quality: Identifies the details of errors and warnings generated for an AI file, helping users understand code health at a glance
• Link Map: Visualises the connections between an AI file and its libraries, inputs, and outputs, and surfaces Common Vulnerabilities and Exposures (CVE) for AI libraries
• Vulnerability Test: Finds CVE entries associated with AI libraries to highlight security weaknesses
• Privacy Test: Searches for privacy-related keywords within AI files to flag potential data protection concerns
• Risk Score Card: Enables users to analyse and review attributes, attribute types, attribute counts, attribute risk factors, and their respective risk contributions for each AI file
• AI Content Detection: Determines whether a given piece of content or model is AI-generated, supporting transparency and disclosure requirements
• Fairness Test: Evaluates whether an AI model's predictions or decisions exhibit bias or discrimination towards groups defined by sensitive attributes such as race, gender, or age
• Interpretability Test: Identifies the importance of input features in a model's decision-making process, highlighting which features have the most significant impact on predictions
• Validity and Reliability Test: Assesses the trustworthiness and robustness of AI models to ensure consistent and dependable outputs

Large Language Model (LLM) Testing Capabilities

• LLM Risk Assessment: Identifies vulnerabilities in LLM-generated responses to ensure reliable and trustworthy content
• LLM Hallucination Test: Measures the hallucination rate of custom LLMs trained on specific datasets, giving teams visibility into response accuracy
• LLM Source Attribution: Helps users understand where, within structured and unstructured data, an LLM is generating its responses to a given prompt

AI Risk Management Framework

• AIValidator® is aligned with the NIST AI Risk Management Framework, covering supervised, unsupervised, and deep learning model types
• Supports organisations in assessing and managing AI risk, cultivating a culture of risk awareness, and conducting periodic model testing
• CIMCON provides a downloadable AI Risk Management Policy guide as an essential toolkit for responsible and effective AI utilisation

AIValidator® is part of CIMCON's Enterprise Series and is designed to integrate into existing model risk and compliance workflows. The platform provides automated documentation and evidence controls to support audit readiness and regulatory submissions, making it a comprehensive solution for organisations operating under stringent AI governance requirements.