
AIValidator
Automated suite for AI model tests ensuring fairness, interpretability, code quality, privacy, and compliance with regulatory standards.
Overview
The AIValidator® Validation Module from CIMCON Software is designed to support the creation of trustworthy AI models. It offers a comprehensive suite for testing, validation, and documentation, aligning with both business and regulatory standards. By drawing on 25 years of risk management expertise, it automates a broad range of AI model tests that assess factors such as fairness, interpretability, validity, code quality, privacy, and cybersecurity.
This automated solution identifies high-risk models by assigning risk scores, helping to cut down time spent on model development, testing, and validation. It features automated risk scoring, evaluates code quality, and assesses model dependencies with a no-code inventory and workflow management system. Moreover, it provides evidence controls and compliance through automated test results and supporting documentation and scans models for privacy concerns and vulnerabilities.
Benefits
- Automated risk scoring and code quality assessment
- No-code inventory and workflow management
- Comprehensive privacy and vulnerability scans
- Aligned with the NIST AI Framework
Key Features
- Code Quality: Details errors and warnings in AI files.
- Link Map: Visualizes file links with libraries, inputs, and outputs, highlighting vulnerabilities.
- Vulnerability Testing: Identifies vulnerabilities in AI libraries using CVE.
- Privacy Testing: Searches for privacy-related keywords in AI files.
- Risk Score Card: Enables analysis of attributes and risk factors in AI models.
- AI Content Detection: Detects if content is AI-based.
- Fairness Testing: Evaluates AI models for bias or discrimination.
- Interpretability Testing: Highlights the importance of input features in decisions.
- Validity & Reliability Testing: Assesses trustworthiness and robustness of models.
- LLM Risk Assessment: Identifies vulnerabilities in LLM-generated responses.
- LLM Hallucination and Source Attribution: Analyzes hallucination rates and data sources in LLMs.
Additional features aim to integrate with wider enterprise systems, offering visual insights into data flows and lineage, and providing risk management aligned with the NIST AI Framework. This module is key for firms seeking comprehensive AI risk management and compliance.
