AI Security

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 Build trustworthy AI systems with structured governance, clear risk visibility, and a roadmap aligned to your business goals.

AI adoption is accelerating across every part of the organization - often faster than policies, controls, or workflows can keep up. The result: hidden data exposures, unapproved tools, unclear accountability, and inconsistent decision-making.

Our AI Gap Assessment gives you a complete, structured understanding of how AI is being used, where risk is introduced, and what improvements are needed to ensure safety, reliability, and responsible adoption.

We translate complex, organization-wide AI activity into a clear blueprint your leaders can act on.

 Our approach mirrors modern AI risk-management principles: understanding context, mapping system behavior, measuring risks, and implementing continuous governance. We evaluate how AI interacts with your data, employees, processes, and external services — then identify gaps across people, technology, workflows, and outcomes.

1. Governance Review

We evaluate how AI decisions are made, who is accountable, and whether your oversight processes support responsible adoption.

This includes:

• Roles & responsibilities for AI usage
• Policies, standards, and employee guidance
• Third-party oversight and procurement practices
• Data handling and lifecycle governance
• Alignment with your strategic and operational goals
   

2. Mapping AI Usage & Data Flows

We uncover the full AI landscape across your business — including areas that may not yet be documented.

This includes:

• AI systems currently in use (enterprise, shadow AI, custom models)
• Data sources, inputs, and processing pathways
• How decisions are generated and who relies on them
• Interactions between AI tools, users, and downstream systems
• Identification of sensitive or high-impact use cases
   

3. Measuring Risks & Performance

We analyze existing and potential risks through the lens of safety, security, reliability, and bias.

This includes:

• Vulnerabilities such as prompt misuse, data leakage, unsafe integrations
• Evaluation of model behavior and output reliability
• Risks related to training data, context windows, and user inputs
• Operational impacts and failure modes
• Current detection, monitoring, and incident-response capability
   

4. Managing AI Safely

We provide recommendations to ensure AI usage remains secure, effective, and aligned with business outcomes.

This includes:

• Technical guardrails and layered controls
• Workflow and automation enhancements
• Hardening guidance for applications, prompts, and pipelines
• Detection and response improvements
• Practical governance updates to sustain long-term AI safety

 Your assessment deliverables are tailored to your organization and built entirely from what we uncover in your environment. They are designed for executives, security teams, and operations leaders who need clarity, prioritization, and direction.

AI Gap Assessment Report

A full analysis of your current AI usage, governance, risks, and maturity — tied directly to business impact.

Includes:

• Comprehensive findings
• Risk themes and ranked priorities
• Maturity scoring across governance, usage, security, and reliability
   

AI Systems & Data-Flow Mapping

Visual diagrams illustrating:

• Where AI exists today
• How data moves through models, prompts, applications, and users
• Dependencies and exposed surfaces
   

Risk Register & Exposure Matrix

A structured view of identified risks — including severity, likelihood, affected systems, and business implications.

Secure AI Architecture Blueprint

Recommendations for strengthening your AI ecosystem, including:

• Guardrails for prompts, data, and model outputs
• Standards for integrating third-party AI tools
• Controls for internal and external AI consumption
• Governance and workflow improvements

Executive Summary & Roadmap

A clean, board-ready summary describing:

• What your organization is doing well
• Where gaps exist
• The prioritized path to safe and scalable AI adoption