Scrut helped our company navigate the complexities of SOC 2, ISO 27001, HIPAA, GDPR, CCPA, and PCI compliance with ease.”
NIST AI RMF
Boost AI Governance with NIST AI RMF in under 6 weeks
Achieve trustworthy and responsible AI swiftly with the Scrut Platform.
Mitigate AI-specific risks effectively
Reduce compliance efforts by 40%
Extensive support from NIST AI RMF specialists
“Scrut Automation is a G2 leader in Security Compliance“
Trusted by 1700+ customers
Faster, Easier, Affordable Compliance!
Minimize AI Risks
Mitigate AI bias, privacy, and security risks
Avoid revenue loss by managing critical AI risks
Improve productivity with continuous risk mitigation
Strengthen AI Governance
Create strong AI governance teams for compliance
Define comprehensive AI governance policies
Set up approval workflows for policy adherence
Boost Customer Trust
Monitor AI systems for performance issues
Communicate AI system limitations to users
Deploy ethical and fair AI policies and practices
8 simple steps for acing your NIST AI RMF implementation
What our customers say
.webp)
From day one, the Scrut team made our ISO, SOC 2, and GDPR journey seamless. They understood the complexities of our open-source setup and kept us on track with smart, timely support.
.webp)
Handling sensitive equity data means security and privacy are top priorities. Scrut Automation helped us to comply with the gold standard of privacy, GDPR, by providing real-time visibility into our security posture, enabling us to adequately protect the sensitive data that we hold for our customers.
Getting started with Scrut is easy
STEP 1
Plug Scrut into your tech stack with easy integrations
STEP 2
Lean back as Scrut's automated tests collect majority of the evidences
STEP 3
Quickly address gaps and deploy controls with our content libraries
STEP 4
Enjoy continuous control monitoring and 24/7 audit readiness
Frequently Asked Questions
What is the NIST AI Risk Management Framework (RMF)?
The NIST AI RMF is a set of guidelines developed by the National Institute of Standards and Technology to help organizations manage risks associated with AI systems. It focuses on enhancing the trustworthiness of AI through core functions: Govern, Map, Measure, and Manage.
How does The Scrut Platform help with NIST AI RMF compliance?
Our platform provides pre-built templates, automated workflows, and expert guidance aligned with the NIST AI RMF core functions. With over 1,200 controls and 70+ integrations, we streamline your compliance process, reducing manual efforts by 70%.
Can Scrut's platform help with compliance across multiple jurisdictions?
Yes, The Scrut Platform supports compliance with international regulations like GDPR, the EU AI Act, and ISO 42001. Our multi-entity support and customizable compliance spaces ensure you maintain compliance across all business units and jurisdictions.
How can organizations benefit from implementing NIST AI RMF?
By implementing NIST AI RMF, organizations can effectively manage AI-related risks while building trustworthy, responsible AI systems. Key benefits include:
- Proactive AI risk management: Address risks like bias, data privacy issues, and security vulnerabilities early.
- Enhanced transparency and accountability: Ensure that AI systems are transparent and accountable, building trust with customers and stakeholders.
- Continuous improvement: Regularly review and update AI governance practices to stay aligned with evolving risks and regulatory requirements.
How do NIST AI RMF and NIST CSF 2.0 work together?
NIST AI RMF and NIST CSF 2.0 can be used together to address different risk areas. While NIST AI RMF manages AI-specific risks, NIST CSF 2.0 focuses on cybersecurity for all systems, including AI. Combining both frameworks provides a comprehensive risk management strategy for organizations.
Is NIST AI RMF mandatory for organizations using AI?
No, NIST AI RMF is a voluntary framework. It provides guidelines for managing AI-related risks but is not required for compliance or certification. However, it’s highly beneficial for organizations seeking to build trustworthy AI systems and align with best practices in AI risk management.
