HITRUST’s AI Risk Management Assessment shifts healthcare compliance from policy checklists to continuous model monitoring. Learn why metrics like bias, drift, and explainability now matter—and how TRACE helps map these metrics directly to HITRUST controls for real-time, audit-ready evidence.
TRACE is an open assurance framework that turns Responsible AI from intent into evidence. It links model metrics to legal clauses, automates controls, and delivers audit-ready proof—without black-box platforms.
Radiology AI tools are powerful—but are they provably safe? This post explores how TRACE transforms performance metrics into HIPAA-compliant audit logs and factsheets for patients and clinicians alike.
AI metrics are necessary—but not sufficient—for compliance. Learn how TRACE adds purpose, risk, and impact metadata to generate audit-ready evidence that meets EU AI Act and ISO 42001 expectations.
Learn how pairing Deepeval with the TRACE framework turns raw fairness, privacy, and robustness metrics into audit-ready evidence that satisfies EU AI Act, NIST RMF, and ISO 42001 requirements.
AI teams track metrics. Regulators want evidence. TRACE transforms fairness scores, privacy metrics, and model evaluations into audit-ready proof—automatically. Learn how it bridges the Metrics-to-Evidence Gap and helps you comply with EU AI Act, NIST AI RMF, and ISO 42001.
AI governance demands more than metrics—it needs evidence. Learn how CognitiveView’s TRACE Framework bridges the gap between evaluation and audit-ready compliance aligned with EU AI Act, NIST, and ISO 42001.
In 2025, transparency is a must. Learn how healthcare startups can publish a patient-facing AI factsheet in 30 days to meet EU AI Act, NIST, and ISO 42001 standards—while building trust with patients and payers. Includes examples, KPIs, and a free template.
Discover a clear, standards‑aligned path to Responsible AI. Learn how CognitiveView’s 3‑step Governance, Risk, and Compliance (GRC) journey helps you assess, monitor, and comply with frameworks such as NIST, the EU AI Act, and ISO 42001—while growing at your own pace.
Use Deepeval to build a continuous quality gate for LLMs that blocks hallucinations, bias, and drift. This guide shows how to integrate it with GitHub Actions and your risk framework—aligning AI deployments with NIST and ISO standards using open-source tools.
AI isn’t replacing your workforce—it’s becoming part of it. In this recap of my conversation with Dr. Ranjan Data, we break down how to move from AI fear to fluency with practical steps for reskilling, governance, and designing a truly hybrid workforce.
Discover how Cognitiveview empowers Agile teams to integrate AI safety into every sprint—managing risks, automating compliance, and connecting seamlessly with observability tools like MLflow and SageMaker. Make compliance effortless, proactive, and audit-ready.
