Why did we build this product?

The rise of AI regulations globally (EU AI Act, U.S. Executive Order, state-level laws) is creating urgent demand for organizations to identify and manage their AI-related risks. Our customers need a way to evaluate their AI systems and ensure compliance across jurisdictions, frameworks, and internal policies, while also ensuring a defensible audit trail. AI Risk is our response to that need.

What problem is AI Risk solving?

AI Risk provides a structured and defensible assessment process to identify and document risks tied to the use of AI systems. It supports organizations in evaluating regulatory exposure, applying consistent risk frameworks, and establishing AI governance across legal, privacy, security, and compliance teams.

Who will use this product?

AI Risk is intended for cross-functional teams that include Compliance, Legal, AI Governance, and Risk Management. AI Steering committees and their component members. AI steering committees and executives responsible for AI governance risk and compliance will find this especially valuable.

What makes this different from other AI governance tools?

Unlike general-purpose risk registers or generic GRC tools, AI Risk: Codifies regulatory guidance (e.g., EU AI Act, NIST RMF) into configurable assessments. Supports multi-framework alignment and documentation. Provides built-in auditability and traceability.

What are the top use cases?

Regulatory Alignment: Mapping AI systems to the EU AI Act or NIST AI RMF. Pre-Deployment Review: Assessing risk before releasing a model or tool. Cross-Functional Collaboration: Legal, compliance, and AI teams jointly evaluating risk. Audit Trail: Documenting decisions and rationale for audits and regulators.

Will this tie into incident workflows?

Yes. Incidents involving AI system misuse or harm can trigger assessments. Likewise, risk findings can link back into Compliance or Privacy obligations when thresholds are met.

Can I see reporting by risk level or framework coverage?

Yes. Assessments will support: Risk distribution by system | Framework coverage dashboards | Gaps or missing documentation

Can AI Risk handle multiple systems or models at once?

Yes. Assessments are per system/model but the interface will support a portfolio-level view.

Is this built to scale with new regulations?

Yes. New frameworks, jurisdictions, or internal review processes can be added via configuration. We plan to provide prebuilt updates for major regulatory shifts post-GA.

How does AI Risk integrate with existing AI governance software?

Radar AI Risk connects seamlessly with other AI governance tools, enabling centralized oversight without the need to replace existing systems.

Can AI Risk support high level reporting for executives and boards?

Yes. The platform offers high level dashboards and scorecards designed for leadership to quickly assess organizational AI risk posture.

How does AI Risk help with training data compliance?

AI Risk tracks and documents training data quality, provenance, and use, ensuring compliance with privacy and ethical guidelines.

Is Radar AI Risk suitable for organizations just beginning to adopt AI?

Absolutely. Whether you are starting small or scaling enterprise-wide, Radar AI Risk provides the structure to manage compliance from the beginning of development and deployment.

Responsible AI at RadarFirst

Explore how RadarFirst integrates AI responsibly in regulatory risk management—balancing automation with expert oversight to help organizations navigate evolving compliance landscapes.

AI-Powered Automation for Regulatory Risk Management

RadarFirst uses artificial intelligence and machine learning to enhance the efficiency and accuracy of risk classification and regulatory obligation detection under laws such as the EU AI Act, GDPR, and U.S. state-level frameworks. AI is employed to:

Automatically classify AI systems into risk tiers (e.g., prohibited, high-risk, minimal-risk)
Recommend applicable regulatory obligations and mitigation actions
Identify similarities with known regulatory precedents to surface reporting thresholds

While our models are trained to support high accuracy, outputs may vary based on context, data quality, and regulatory interpretation. AI-generated results are intended to assist—not replace—professional judgment and legal review. Users remain responsible for verifying final actions taken within their organization.

AI Addendum

AI Use & Limitations

RadarFirst incorporates AI technologies to assist with regulatory risk classification, obligation detection, and workflow automation. These features are designed to support—but not replace—professional expertise and legal judgment.

AI capabilities are:

Non-deterministic: AI-generated outputs may vary based on context, input data, and evolving regulatory interpretations.
Advisory in nature: All outputs (e.g., risk classifications, obligation recommendations) are intended to inform and support decision-making but are not legally binding.
Subject to human review: Users are responsible for validating outputs before taking action or submitting reports to regulators.

Limitations:

AI features do not constitute legal advice.
AI-generated outputs should not be the sole basis for regulatory reporting or incident escalation.
RadarFirst does not guarantee 100% accuracy of AI-based recommendations and disclaims liability for outcomes based solely on automated assessments.

We reserve the right to update, enhance, or restrict AI functionality in accordance with emerging regulatory requirements or ethical guidelines. Users will be notified of material changes affecting AI system behavior.

Data Use and Privacy Addendum for AI

Data Use and Privacy in AI

RadarFirst is committed to protecting the privacy, security, and integrity of your data in all aspects of our AI feature set.

Our AI systems are designed to function within strict privacy boundaries. Specifically:

Customer data is never used to train generalized AI models without explicit, informed consent.
All AI processing occurs within the secure boundaries of our infrastructure, with safeguards in place to prevent unauthorized access, leakage, or unintended retention.
We apply principles of data minimization and purpose limitation, ensuring that only the data necessary for each AI-assisted task is used, and only for that task.
No customer data is shared with third-party model providers or external systems as part of RadarFirst’s AI processing pipeline.
Our AI systems are subject to regular privacy and security reviews, including controls for access logging, encryption, and audit readiness.

RadarFirst’s AI capabilities are built in alignment with our overarching Privacy Policy and reflect our commitment to compliance with frameworks including GDPR, CCPA, and the EU AI Act. Customers retain full control over their data, and we are transparent about where and how AI is applied within our platform.

Generative AI Notice

Content generated using our AI assistant may be synthetic and is produced based on the prompts and context you provide. You are responsible for reviewing AI-generated content for accuracy and appropriateness before publication or submission.

Export Controls & Jurisdictional Restrictions

Access to certain AI capabilities may be restricted based on your location in accordance with applicable export control regulations. By using this product, you agree to comply with all relevant U.S. and international laws governing technology exports.

RadarFirst AI Use Summary & Commitment to Responsible Deployment

At RadarFirst, we integrate artificial intelligence (AI) thoughtfully and transparently to enhance the efficiency and quality of our secure regulatory risk management platform, Radar^™. Our deployment of Claude 3.5 Sonnet, a large language model developed by Anthropic and delivered through Amazon Bedrock, is guided by clear principles of ethics, safety, privacy, and human oversight.

Purpose and Use

We are currently developing AI-enhanced features on Radar in two main ways:

Comparing AI use cases to regulations: The AI chatbot helps analysts structure and assess AI use cases across the organization, suggesting possible mitigations to reduce regulatory risk.

Providing documentation of AI use compliance: The platform creates an auditable record of AI use cases, risk mitigations, and cross-functional approvals.

Our Commitment to Responsible AI

Ethical Foundations: The Claude model is aligned with Anthropic’s Constitutional AI principles, designed to reduce bias and avoid harmful or discriminatory output. We further enforce ethical boundaries through system prompts and access controls.

Privacy Protection: AI interactions do not train the model. No data is stored or reused by Anthropic. All transmissions are encrypted, and processing occurs in a secure, isolated cloud environment.

Security Measures: We implement prompt injection filtering, content moderation, and audit logs to detect and prevent misuse or unsafe behavior.

Additionally, the platform benefits from the comprehensive privacy and security measures that are already enabled on the Radar^™ Regulatory Risk Management Platform. More information is available at the Radar Trust Center hosted on Whistic.com.

Oversight and Transparency: Users can override assessed risk. Human validation is required for all critical output. We continuously monitor AI performance for safety and accuracy.

Limitations and User Responsibility

While our AI tools are designed to assist professionals, they remain experimental. The model may occasionally produce incorrect or misleading output (“hallucinations”) or misinterpret ambiguous input. Therefore:

AI-generated content should not be solely relied upon. All outputs are subject to user review, and final responsibility lies with the human analyst.

We encourage users to treat AI as a productivity-enhancing assistant, not a substitute for expert judgment.

Looking Ahead

RadarFirst remains committed to improving our AI capabilities responsibly. We continually monitor safety practices, assess emerging risks, and remain open to user feedback as we evolve our systems.

For more details or to share feedback on our AI feature, please contact our team.

Adan Perez, VP of Product, [email protected]

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