AI security services

Data poisoning → Wrong business insights

When attackers manipulate training data, AI systems start producing biased or false results.

This can lead to incorrect decisions in pricing, hiring, or risk assessment, directly affecting revenue and compliance.

Model theft → Loss of competitive advantage

Unprotected AI models can be copied or resold, exposing proprietary algorithms and weakening your market position.

Adversarial attacks → Reputational damage

Subtle input manipulations can make your AI generate incorrect or harmful responses, which can harm customer trust and brand credibility.

Unauthorized access, prompt injections → Compliance risks

Unauthorized access and prompt injections can reveal confidential data, expose internal systems, or produce biased and non-compliant outputs, all leading to legal and reputational consequences.

Supply chain vulnerabilities → Business disruption

Third-party tools or APIs used in AI workflows can carry hidden threats. A compromised integration can halt operations and cause costly downtime.

Denial-of-Service (DoS) attacks → Operational downtime

Attackers can overload AI infrastructure, making systems unresponsive and interrupting customer-facing services.

Securing training data and models prevents leaks, theft, and misuse of sensitive or proprietary information.

Preventing breaches and system failures reduces recovery expenses and long-term maintenance costs.

Robust security supports compliance with data privacy and emerging AI governance standards.

A protected AI environment strengthens trust among customers, partners, and regulators.

Resilient AI infrastructure minimizes downtime and disruption caused by security incidents.

Protection against manipulation ensures AI models deliver accurate and trustworthy results.