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AI Security & Governance
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AI Security & Governance

Securing your AI models, data pipelines, and preventing adversarial attacks.

AI Security & Governance secures your AI models and data pipelines while preventing adversarial attacks. NexWEB red-teams your AI applications, deploys data-loss-prevention guardrails through a governed AI gateway, and creates immutable audit logs of AI decision rationales. We provide defense-in-depth against prompt injection and model poisoning, keeping proprietary data inside the boundary and making automated decisions defensible for highly regulated industries adopting generative AI.

The Challenge

Enterprises frequently face severe operational and technical blockers when trying to scale or modernize in this domain. Typical issues include:

  • Fear of proprietary data leaking through public LLMs
  • Compliance requirements for automated decisions
  • Vulnerability to prompt injection and model poisoning

What We Deliver

Red Teaming

Adversarial testing of your AI applications.

Data Loss Prevention

Guardrails preventing sensitive data from leaving the boundary.

Auditability

Creating immutable logs of AI decision rationales.

Industry Use Cases

Financial Services

Governed AI gateways and audit trails that satisfy regulators for automated decisions.

Healthcare

Data-loss-prevention guardrails that keep protected health information inside the boundary.

Enterprise IT

Red-teaming and guardrails that harden generative AI against prompt injection at rollout.

Our Approach

1

Threat Assessment

We map the attack surface across models, data pipelines, and integrations.

2

Guardrail Design

We deploy DLP, governed AI gateways, and policy controls at the boundary.

3

Adversarial Testing

We red-team applications against prompt injection, leakage, and model poisoning.

4

Audit & Monitor

We establish immutable logging and continuous monitoring for compliance.

Why NexWEB Technologies

  • Defense-in-depth against prompt injection and model poisoning.
  • Data-loss-prevention guardrails governed through an AI gateway.
  • Immutable audit trails that make automated decisions defensible.

Frequently Asked Questions

What is prompt injection?
It is an attack where malicious inputs cause an AI to bypass its instructions. We build defense-in-depth to mitigate this.
How do you stop proprietary data leaking through LLMs?
We deploy data-loss-prevention guardrails through a governed AI gateway that prevents sensitive data from leaving the boundary. Combined with policy controls at the boundary, this addresses the fear of proprietary information leaking through public LLMs, keeping regulated data inside your environment.
What does an engagement to secure AI involve?
We start with a threat assessment mapping the attack surface across models, data pipelines, and integrations, then design guardrails, run adversarial red-team testing against prompt injection, leakage, and model poisoning, and establish audit and monitoring. The result is defense-in-depth applied across the full AI stack.
How do you make automated AI decisions defensible?
We create immutable audit trails that log AI decision rationales, so every automated decision can be reviewed and justified. This auditability supports compliance requirements for automated decisions in regulated settings such as financial services, where regulators expect a clear record behind each outcome.
How do you test AI applications for weaknesses?
We red-team your AI applications, running adversarial testing against threats such as prompt injection, data leakage, and model poisoning. This proactive testing surfaces vulnerabilities before attackers do, and pairs with guardrails and monitoring so weaknesses are found and closed as part of a defense-in-depth approach.

Technologies Used

NVIDIA NeMo GuardrailsMicrosoft PurviewAI GatewaysZero TrustOAuth 2.0Splunk

Ideal For

Highly regulated industries adopting generative AI.

Related Services

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