When evaluating AI platforms for nuclear supplier auditing, one question often dominates the discussion: Does it understand NRC regulations? It's an important question, but it's not the only question that matters.

Nuclear supplier audits aren't conducted in a regulatory vacuum. While 10 CFR 50 Appendix B provides the foundational quality assurance criteria, every audit program operates within a broader compliance framework that includes utility-specific requirements, component-specific codes, and site-specific standards.

An AI platform that only knows NRC regulations isn't enough.

The Regulatory Complexity of Nuclear Auditing

Nuclear supplier compliance validation involves multiple layers of requirements:

• NRC Baseline Requirements: 10 CFR 50 Appendix B establishes 18 quality assurance criteria that form the regulatory foundation. These criteria are supplemented by Regulatory Guides such as RG 1.28 and 1.33, NUREG documents, and NRC inspection procedures.

• Utility-Specific Requirements: Each utility adds its own procurement requirements through purchase orders, technical specifications, and supplier quality expectations. These requirements build on NRC regulations but include utility-specific criteria for supplier qualification, documentation, and performance.

• Site-Specific Criteria: Individual plants may have unique requirements based on their licensing basis, operational history, or corrective action programs. These site-specific criteria must be incorporated into supplier audits for components destined for those facilities.

An AI platform that understands only the NRC baseline can't validate compliance with the full regulatory framework that governs supplier performance.

Why Generic AI Tools Fall Short

Public AI platforms like ChatGPT have broad general knowledge—but they lack the depth needed for nuclear compliance work. Ask ChatGPT about 10 CFR 50 Appendix B Criterion III, and you might get a reasonable summary. But ask it to validate whether a supplier's design control procedure meets a specific utility's procurement requirements, and the response will be generic at best.

The problem isn't just a lack of nuclear knowledge—it's a lack of customization capability.

Generic AI tools are trained on publicly available information. They can't incorporate:

• Your utility's internal QA procedures

• Your procurement department's supplier qualification criteria

• Your engineering organization's technical specifications

• Your site-specific licensing requirements

These documents aren't publicly available, and even if they were, public AI platforms don't provide mechanisms for customizing their knowledge base to include them.

What Customizable Regulations Look Like

A purpose-built AI platform for nuclear auditing must allow customization of its regulatory knowledge base. Here's what that means in practice:

Pre-Loaded NRC Foundation

The platform should come configured with core nuclear regulations out of the box:

• 10 CFR 50 Appendix B, all 18 criteria

• Key Regulatory Guides such as RG 1.28, 1.33, and others

• Relevant NUREG documents, such as NUREG-0800 sections

This provides the regulatory foundation without requiring users to manually enter basic NRC requirements.

Utility-Specific Additions

Users should be able to add their organization's unique requirements:

• Procurement specifications and purchase order requirements

• Internal QA manual procedures and work instructions

• Supplier qualification criteria and approved supplier list requirements

• Technical specifications for specific component types

These documents become part of the AI's knowledge base, allowing it to validate compliance against both NRC regulations and utility-specific criteria.

Site-Specific Criteria

For utilities with multiple sites, the platform should support site-specific requirements:

• Plant-specific licensing basis documents

• Site corrective action program requirements

• Unique inspection or testing criteria

• Local regulatory commitments

This ensures audits account for variations between different facilities within the same utility.

Evolution and Updates

Regulations change. Standards get updated. Procedures are revised. The platform must support ongoing updates to the regulatory knowledge base:

• Sync new regulation versions as they're approved.

• Update internal procedures when they're revised.

• Add new standards as they're adopted.

• Remove outdated requirements when superseded.

Without this capability, the AI's knowledge base becomes stale and unreliable.

How Customization Improves Audit Quality

Customizable regulations aren't just a nice-to-have feature—they fundamentally improve audit effectiveness:

• More Accurate Validations: When the AI understands both NRC requirements and utility-specific criteria, it can identify compliance gaps that generic tools would miss.

• Reduced False Positives: Validating against the correct regulatory framework reduces irrelevant findings that waste auditor time.

• Better Supplier Communication: Suppliers receive clear expectations based on the actual requirements that apply to their scope—not generic interpretations of regulations.

• Audit Defensibility: Complete documentation showing how findings map to specific utility requirements strengthens audit defensibility during regulatory scrutiny.

• Team Consistency: All auditors work from the same regulatory model, ensuring consistent interpretation and application of requirements across the team.

The Implementation Question

The challenge isn't just having a customizable regulations module—it's making customization practical for users who aren't AI experts.

Effective implementation requires:

• Simple Upload Process: Users should be able to upload regulatory documents through a straightforward interface without technical knowledge.

• Intelligent Parsing: The platform should automatically segment documents into searchable sections that the AI can reference accurately.

• Verification Capability: Users must be able to verify what the AI knows by viewing the regulatory content hierarchically and exporting sections for review.

• Controlled Updates: Changes to the regulatory knowledge base should require approval before the AI model is updated to ensure quality control.

• Citation Transparency: When the AI references a requirement, it should clearly indicate whether it's from NRC regulations, utility procedures, or other sources.

AuditLens AI: Built for Customization

AuditLens AI was designed from the ground up to support customizable regulations:

• Pre-Loaded NRC Content: The platform comes configured with 10 CFR 50 Appendix B, key Regulatory Guides, and NUREG documents—ready to use immediately.

• Regulation Sources Module: Upload your utility's procedures, procurement requirements, and site-specific criteria. These documents become part of the AI's knowledge base.

• Organized Sections: Regulations are automatically segmented into searchable sections, enabling accurate AI responses.

• Hierarchical View: Review all regulatory content in a structured hierarchy to validate what the AI knows.

• Sync Control: Approve and sync regulation updates to the AI model when you're ready—maintaining control over the knowledge base.

• Verified Citations: Every AI response includes clickable citations showing exactly which requirement applies and where it's documented.

The Bottom Line

Nuclear supplier audits require more than generic NRC knowledge. They demand a regulatory framework that reflects the full complexity of your audit program—NRC requirements, utility standards, component codes, and site-specific criteria.

An AI platform that can't be customized to your actual regulatory framework isn't truly built for nuclear auditing.

If you're evaluating AI tools for nuclear supplier compliance validation, ask these questions:

• Can I add my utility's internal procedures to the AI's knowledge base?

• Can the platform incorporate site-specific requirements?

• Can I update the regulatory content as standards evolve?

• Can I verify exactly what regulations the AI is referencing?

If the answer to any of these questions is "no," the platform isn't designed for the complexity of real-world nuclear auditing.

Join the Pilot Program

AuditLens AI was developed by a team that understands nuclear quality assurance requirements. We have worked with nuclear utilities for over 35 years, helping them modernize their technology infrastructure while ensuring regulatory compliance.

We are now using that same expertise for nuclear supplier audits.

If you're a NUPIC auditor, a utility audit team member, or a quality assurance professional looking to change how you verify supplier compliance, we invite you to join the AuditLens AI pilot program. Limited spots are available for auditors eager to shape the future of AI-assisted nuclear auditing.

Learn more and book a demo: https://www.ethany.com/auditlens_ai