Model Guardian
- Visibility and control over public AI services
- Mitigate AI risks by enforcing guardrails with real-time inspection
The 4 Pillars of AI Firewall
Delivers the principles of AI TRiSM — Trust, Risk, and Security Management
Security
Prevent sensitive data from being exposed.
Risk Management
Proactively identify, classify, and neutralize AI risks.
Trust
Gain real-time insight into AI activity, uncover shadow use.
Governance
Define, enforce, and monitor responsible AI usage.
Model Guardian Core Features
Security
Sensitive Data Protection (DLP): Prevent PII, PHI, and IP from leaving your environment.
Data Taxonomy & Classification: Identify activities, topics, and sensitivity levels.
Prompt Injection & Jailbreak Protection: Stop malicious instructions from bypassing safeguards.
OWASP LLM Threat Coverage: Address top AI risks like insecure output handling.
Risk Management
Toxic Content Filtering: Block unsafe, harmful, or policy-violating prompts and responses.
Hallucination Reduction: Validate AI outputs against policy and fact-checking rules.
Risk Classification & Rules: Define and manage risky AI activities using natural language policies.
Trust
Output Validation: Ensure results are accurate, aligned, and reliable.
Policy-Based Enforcement: Translate company rules into automated safeguards.
Content Integrity Checks: Maintain tone, safety, and brand alignment.
Governance
AI Agent Activities: Visibility and control on what agents do.
Shadow AI Detection: Discover and audit unsanctioned AI usage.
AI Monitoring & Auditing: Map, log, and analyze AI interactions.
Usage Mapping: Track AI usage patterns, workflows, and operational exposure.
Model Guardian Key Benefits
Protect Sensitive Data
Prevent PII, PHI, financial, and proprietary content from leaving your environment with built-in data classification and leakage protection.
Block AI Threats
Stop prompt injection, jailbreaks, and malicious inputs while addressing OWASP LLM Top 10 risks.
Gain Full Visibility
Monitor, audit, and map AI usage in real time to uncover shadow AI and ensure transparency across teams.
Enforce Governance Policies
Apply company rules and compliance requirements with automated, role-based guardrails.
Reduce Business Risks
Mitigate harmful outputs, hallucinations, and reputational or financial damage caused by unsafe AI use.
Ensure Regulatory Compliance
Align AI usage with industry standards and regulations such as the EU AI Act, NIST AI RMF, HIPAA, and GDPR.
Model Guardian Use Case
Government & Public Sector
- Secure AI use in air-gapped environments.
- Monitor AI adoption across departments.
- Align with data sovereignty and governance rules.
- Block prompt injection and manipulation threats.
Legal & Professional Services
- Safeguard client files and contracts.
- Apply role-based AI usage policies.
- Maintain audit trails for accountability.
- Reduce liability from AI hallucinations.
Financial Services
- Block leaks of client data or trading strategies.
- Enforce compliance with GDPR, SEC, and FINRA.
- Detect shadow AI use in trading and advisory teams.
- Reduce risks from AI-generated financial advice.
Healthcare
- Protect PHI, PII, and patient records.
- Enforce HIPAA compliance in AI usage.
- Validate AI recommendations for accuracy.
- Prevent unsafe or biased patient communication.
Enterprise & Technology
- Stop IP and source code from leaking.
- Enforce AI usage policies by role or department.
- Audit and control shadow AI adoption.
- Validate chatbot and knowledge AI outputs.
Frequently Asked Questions
What is an Model Guardian?
Why do I need an Model Guardian if I already secure my network and data?
How does the Model Guardian protect sensitive data?
What types of risks can the Model Guardian prevent?
Prompt injection and jailbreaks (malicious instructions)
Hallucinations and unsafe outputs
Toxic or non-compliant content
Shadow AI usage (unsanctioned AI tools)
Sensitive data leakage
Can I set my own policies and rules?
Does the Model Guardian help with compliance requirements?
How does the Model Guardian give visibility into AI usage?
Where can the Model Guardian be deployed?
On-Premises (within your infrastructure)
Private Cloud
Air-Gapped environments (no internet)
SaaS (fully managed)
How is “AI Guardrails” different from features?
Who should use an Model Guardian?
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