Holistic AI Governance for the Modern Enterprise
Modern AI provides a comprehensive framework to govern every facet of your AI ecosystem. From securing AI users and shadow applications to managing autonomous agents, complex APIs, and data integrity through the Model Context Protocol (MCP), we ensure compliance, safety, and transparency at scale.
Users & Access
Monitor and secure employee interactions with public and private LLMs, preventing sensitive data leaks through identity-centric controls.
APIs & Connectivity
Continuous discovery and securing of AI-specific APIs, monitoring traffic for prompt injection and security vulnerabilities.
Agents & Automation
Govern autonomous agentic workflows with behavioral monitoring, policy enforcement, and audit logs to prevent hallucination-driven errors.
AI Applications
Full visibility into shadow AI applications used across the company, enabling informed sanctioning or remediation.
Data & MCP
Manage data connectors and context retrieval via the Model Context Protocol, ensuring models only accessauthorized internal data.
Global Compliance
Stay compliant with EU AI Act, NIST RMF, and ISO 42001 through automated assessments and continuous monitoring.
Real-Time AI Maturity Assessments
Modern AI empowers enterprises to measure and track AI maturity in real time, ensuring strict alignment with NIST AI RMF and ISO 42001 risk management standards. Our automated assessment engine provides continuous visibility into your AI risk posture, enabling proactive governance and sustainable innovation.
Maturity Scorecard
NIST AI RMF Alignment
ISO 42001 Compliance
AI Maturity Assessment Results
The NIST AI Risk Management Framework (RMF) and ISO/IEC 42001 provide the global blueprint for AI security and ethical governance. NIST emphasizes a lifecycle approach to managing risks—focusing on reliability, safety, and security—while ISO 42001 establishes the requirements for an Artificial Intelligence Management System (AIMS).
NIST AI RMF & ISO 42001 Standards
68%
Baseline Score
Assessment Summary
The enterprise demonstrates a solid foundational understanding of AI risk, currently aligned with Level 2 of the Maturity Model. While initial policies exist, significant gaps remain in continuous monitoring and automated security controls. Focus is required on maturing the Governance and Security layers to ensure full compliance with ISO 42001 and NIST standards.
Governance
Established principles. Need to formalize AI Ethics board and cross-functional oversight.
Status: Emerging
Security
Critical gaps in adversarial robustness testing and model monitoring.
ACTION REQUIRED
Data
Strong inventory. Need to automate lineage mapping and bias detection at scale.
Status: Competent
Operations
Standardized workflows are in progress. Focus on integrating risk triggers into CI/CD.
Status: Advancing
Together, these frameworks ensure that AI implementations are not only innovative but also resilient against emerging threats, requiring robust controls for data privacy, model integrity, and continuous monitoring of risk-posture.
Technology Partners
