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AI Security
Architecture & Assessment

Your staff are already building with AI, copilots, agents, and internal tools connected to real data. We design the safe environment for that building to happen in, and assess what gets created before it reaches production.

What We Deliver

Two problems, one engagement, a safe place for your team to build AI tools and agents, and a clear answer on whether what they build is secure.

AI Deployment Security Assessment

Security review of an existing copilot, chatbot, or agent against the OWASP LLM Top 10, covering prompt injection, insecure output handling, data exposure, and excessive agency.

OWASP LLM 10 Threat Model

Safe Sandbox Environment Design

Architecture for a contained space where staff can build and test AI tools and agents without touching production data, with clear boundaries on what is allowed to run unsupervised.

Sandbox Design Data Segregation

Agent & Tool Permission Review

Assessment of what each agent can actually reach, its data access, connected systems, and the identity it acts under, to close the gap between intended scope and real scope.

Excessive Agency Access Control

Human-in-the-Loop Guardrail Policy

Clear rules for what an AI agent may do without approval and what requires a person to check first, so speed and safety are not competing goals for your team.

Guardrails Human Oversight

Ongoing Build Assessment

A recurring review cycle for every new AI tool or agent staff create in the sandbox, so security keeps pace with a team that keeps building.

Continuous Review Quarterly Cadence

AI Risk Register & Executive Reporting

Findings mapped to NIST AI RMF and ISO/IEC 42001, tracked in a living risk register and reported to leadership in plain language, not vendor jargon.

NIST AI RMF Board Reporting

The Risks of Unsecured AI Building

Once staff can build with AI, the risk shifts from which tools you approved to what your own people connect those tools to.

Prompt Injection

Malicious instructions hidden in a document, email, or web page an agent reads can override its original task and trigger unintended actions.

Excessive Agency

Agents given broad permission to act, send, or write, with no check first, turn a small mistake or manipulation into a real incident.

Data Leakage Through Agents

An agent grounded on internal data can be tricked or misconfigured into surfacing information to a user who should never see it.

Unreviewed Shadow Builds

Tools staff build themselves, outside any sandbox or review, are the ones nobody in security knows exist until something goes wrong.

Build With AI.
Not Around Security.

Book a free consultation. We will look at what your team is already building, or wants to build, and design a way to do it safely.