AI Governance Solutions | Rivial Security

Cyber GRC partner for lean security teams

Stand up AI governance without stretching your team.

Rivial helps lean security teams build a NIST-aligned AI governance program in nine weeks. You stay focused on running the rest of your security program. We deliver the assessment, the documentation, and the workflows your Board, your business, and your auditors will accept.

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Data Breaches

Due to data poisoning, tampering, or bias.

Operational Failures

From model drift or lack of robust testing.

Regulatory Penalties

From privacy violations and biased AI outcomes.

Ineffective Risk Management

AI risks are not properly managed.

We Understand the Complexities of AI Governance & Risk Management

At Rivial, we’ve helped numerous highly regulated organizations integrate AI risk management into their existing cybersecurity frameworks. We understand that AI risk is unique and requires a specialized approach.

Our AI Risk Management solution combines the best practices from cyber risk management with the latest in AI-specific risk protocols. We’re here to help you navigate AI’s complexities, from compliance to security, so you can unlock AI’s potential with confidence.

Why this matters now

A policy is the tip of the iceberg. Building the rest takes time you don't have.

AI is already in your environment. It's embedded in vendor tools, used by business units who never filed a ticket, and quietly changing the risk profile of systems you assessed last year.
Most lean security teams already know an AI policy isn't enough.

The harder problem is finding the time to build everything underneath it: the inventory, the intake workflow, the vendor review process, the updated KRIs, the IR playbooks, the Board reporting. All on top of audit prep, vendor reviews, and the day job.

That's the gap we close.

Shadow AI

Business units adopting AI tools your security team has never seen.

Vendor Drift

Existing vendors quietly adding AI features that change your risk profile.

Model and Data Risk

Bias, drift, hallucinations, and data exposure that don't show up in a SOC 2.

Documentation Gaps

AI questions on questionnaires, audits, and Board agendas you don't yet have a documented answer for.

Ai Governance Advisory & Implementation Service

A practical AI governance program your team didn't have to build.

We work as an extension of your team. Over a nine-week engagement, we assess where your AI governance stands today, benchmark it against the NIST AI Risk Management Framework, and build the policies, workflows, and ongoing processes you need to govern AI use across the business.When we hand the program back to you, it's ready to run. No 80-page binder. No "phase two" you have to staff yourself.

What's included:

AI Adoption and Maturity Assessment

Where you actually are today, across internal use, vendor-embedded AI, and planned initiatives.

NIST AI RMF Gap Analysis

Govern, Map, Measure, and Manage, scored against the framework regulators are starting to cite.

Documentation Review

Existing policies, acceptable use, vendor management, IR, and risk procedures. We tell you what to keep, what to update, and what to build.

Stakeholder and Future-State

Sessions Working sessions with IT, risk, compliance, business owners, and leadership to define a governance model that fits your size and culture.

Policy and Procedure Development

AI governance policy, acceptable use, use-case intake and approval workflow, vendor AI review guidance, and roles and responsibilities.

Ongoing Governance Process Design

Repeatable processes for use-case tracking, risk reviews, issue escalation, periodic reassessment, and Board reporting.

What You Walk Away With

A governance package you can put to work on Monday.

Not a binder that lives on a shared drive. The documentation, workflows, and roadmap, in a format your team will actually use.

AI Governance Maturity Assessment results
NIST AI RMF Gap Analysis summary
AI Governance Roadmap with prioritized next steps
Updated or newly developed AI governance policies and procedures
AI vendor review guidance and questionnaires
Ongoing AI governance process recommendations
Executive summary of key findings, gaps, and next steps

Assess

(Weeks 1–3)

We start with a free IT Risk Assessment that puts dollar values on every risk — so you and your Board have a clear baseline from day one.

Analyze and  Build

(Weeks 4–7)

Gap analysis against NIST AI RMF, then development or refinement of your AI governance policies, procedures, intake workflows, and vendor review materials.

Roadmap and Operationalize

(Weeks 8–9)

Final recommendations, governance roadmap, executive summary, and an implementation discussion. Your team owns the program going forward, not us.

Governance

Policy Updates: Review and add AI-related content to existing policies, employee handbooks, and security protocols.
New AI Policy: Establish a dedicated AI risk management policy, including oversight teams, compliance processes, and data security measures.
Procurement & Change Management: Address AI in procurement, shadow IT risks, and assess third-party software updates introducing AI.
Issue Tracking: Update issue tracking systems to include AI- related risks and performance issues.

Risk Management

Risk Appetite: Adjust loss tolerance to accommodate AI- driven benefits and risks.
Data Types: Assess changes in data types and volumes due to AI integration.
Information Systems: Identify and track AI’s impact on existing systems and business processes.
Controls & Testing: Implement and regularly test AI-specific security controls, ensuring systems operate as intended without introducing new risks.

Compliance Management

Continuous Testing: Ensure ongoing evaluation of AI systems for model drift, bias, and other risks.
Streamlined Compliance: Use integrated platforms to manage cybersecurity and AI compliance efforts together, ensuring continuous oversight.

Vendor Security

Third-Party Monitoring: Enhance vendor security assessments with AI-specific safeguards and adversarial testing.
Data Security: Implement robust data access controls and secure storage practices for AI systems.
Model Governance: Ensure continuous AI model validation and governance in third-party solutions.

Incident Response

AI-Specific Playbooks: Develop tailored incident response plans for AI risks, including model drift and other AI-related failures.
Business Unit Involvement: Ensure business units play a key role in responding to AI-related incidents, alongside IT and Cyber teams.

Assess and Integrate AI Risk into Your Existing Cyber Risk Framework

Our solution integrates AI risk management directly into our current cyber risk model, ensuring consistency and reducing duplication. This allows you to manage AI risk with the same teams, processes, and tools you already use for cybersecurity.
Mitigate AI-Specific Risks
Manage Risk Ongoing

"You guys are cutting edge. If everybody was doing this, my job would be so much easier. Nothing I've seen comes close to what Rivial is doing."

Examiner

NCUA

"Rivial's solutions mean we spent fewer hours in audit preparation, saving us around 60% of our time."

Troy Taylor, CRI

SVP Cybersecurity Solutions

"The risk assessment was spot on perfect, thank you. Far more than anything our Board are used to seeing, but speaking their language."

$1 Billion Credit Union

Stand up AI governance without stretching your team.

Trusted by forward-thinking security leaders