AI Red Teaming@@AI Red Teaming@@AI Security Audit@@AI SOC
AI will shape the world, Security will shape AI
AI Security
Building Trust in AI
AI Red Teaming
To ensure the robustness, dependability, and credibility of AI systems in real-world situations, adversarial attacks are simulated in order to find vulnerabilities, assess the systems’ resistance to threats, and verify the efficacy of security controls.
AI Security Audit
An analysis of an AI system to identify weaknesses, verify security controls, and ensure compliance with organizational and legal requirements, while focusing on the explainability and transparency of the AI model.
AI SOC
The ongoing monitoring of an AI system’s activities, inputs, outputs, and behaviors in order to guarantee performance, spot irregularities, spot security risks, and uphold policy compliance. It facilitates accountability, transparency, and quick incident response.
Impact by Sector
Defending AI Systems Across All Domains
Telecommunications
With 71% of telecom leaders reporting vulnerability in AI systems, threats to self-optimizing networks (SONs), chatbots, and predictive tools are escalating. We secure telecom AI by detecting tampering in SONs, safeguarding user data in customer-facing AI systems, and implementing privacy-preserving mechanisms across predictive maintenance and churn modeling platforms.
Banking
AI systems in banking are under growing threat, with over 50% of financial institutions reporting exposure to AI-specific attacks like model theft and data poisoning. We harden AI models against these threats, secure loan underwriting pipelines, and deploy adversarial testing to protect financial AI workflows from manipulation and intellectual property theft.
Oil and Gas
AI systems in banking are under growing threat, with over 50% of financial institutions reporting exposure to AI-specific attacks like model theft and data poisoning. We harden AI models against these threats, secure loan underwriting pipelines, and deploy adversarial testing to protect financial AI workflows from manipulation and intellectual property theft.
Market Intelligence
Investment in Securing AI is Inevitable
of enterprises suffered at least one AI-related security breach in the last year
of financial institutions experienced attempted AI prompt injection attacks
trillion estimated cost to global economy if current security trends don't improve
Product Development Process
Your Journey
to Digital
Excellence
Discover
We begin by engaging with your AI/ML teams to understand the purpose, design, and data flow of your models. This includes inventorying your training datasets, inference APIs, endpoints, and deployment environments. We also observe model behaviors and interaction patterns to baseline performance and detect potential exposure points. The outcome of this phase is a clear picture of your AI ecosystem, threat surface, and architectural context.
Assess
Next, we evaluate the security posture of your AI systems across multiple dimensions. This includes reviewing access control, prompt handling, API security, data sensitivity, and cloud configurations. Our AI Red Team then performs targeted adversarial testing, including prompt injections, hallucination attacks, RAG poisoning, and model leakage simulations, to uncover real-world exploitable weaknesses. This step ensures a clear understanding of model vulnerabilities and risk exposure.
Control
We implement AI-specific security controls to protect your models and data pipelines. These include input sanitization, output filtering, model access restrictions, runtime guardrails, and gateway protections. For cloud-hosted or containerized deployments, we secure the full MLOps pipeline, environment variables, and API layers. Data privacy is enforced through PII/PHI redaction, encryption, and policy-driven governance to ensure your AI systems operate safely and within regulatory bounds.
Report
Finally, we help you establish continuous monitoring, compliance tracking, and audit readiness. This includes maintaining logs, model cards, bias reports, and explainability documentation to support frameworks like ISO 42001, NIST AI RMF, and emerging AI regulations. We manage AI risk profiles over time, reviewing changes from model retraining, fine-tuning, or new plugin integrations. The result is an AI system that remains transparent, ethical, and compliant
Committed to Excellence
Our Value Chain Delivers
Core Tools
Our Technology Infrastructure
Built on a trusted AI security ecosystem, we combine advanced model protection, adversarial testing,
and secure MLOps pipelines to safeguard AI systems from evolving threats.
On Demand Talent Deployment
Flexible staffing solutions to quickly scale your team with pre-vetted, high-performance IT professionals.
Digital Solution Catalyst
Collaborative partnerships that address AI-specific risks, embedding security, compliance, and resilience
into every stage of the AI lifecycle.
Strategic Technology Architects
End-to-end digital transformation services that convert your strategic vision into measurable technological outcomes.
Tech Skills Optimization
Comprehensive upskilling programs designed to elevate your workforce’s technological capabilities and competitive edge.