Secure AI architecture and engineering for agents, private LLM deployments, cloud AI services, and development workflows handling sensitive data.
AI Architecture & Engineering is design and hardening work, not testing. It covers agents that act on your behalf, models you host on your own hardware or inside a sealed network, and AI services you rent from a cloud provider. It also covers the pipeline that ships your AI features and the AI built into your own security tools. Each service produces a design or a set of applied changes with evidence, not a list of vulnerabilities; when you want the finished system attacked, our AI Security Testing core does that. We scope in writing, then review your architecture, code, and configuration by hand alongside your engineers, recording every decision and exact change with its owner named. We then confirm each change was made and package the evidence your customers, auditors, and contracts ask for. It is built for data that cannot leave: CUI, ITAR and EAR technical data, PHI, and the models, code, and trade secrets that are the product.
For CTOs, platform leads, and compliance owners building or operating AI on regulated data: defense contractors handling CUI, exporters with ITAR or EAR technical data, covered entities with PHI, and companies whose models, code, and prompts are the product. Engage before a design is committed, before a rented AI service goes live, or when a customer or assessor asks how the AI system is secured.
We start with the architecture you have or intend: agents, models, serving stack, rented AI services, pipelines, and their data class. We agree in writing which focused services apply, the environments and accounts we may read, and who holds write access. We name the rules that govern the design: the defense requirements for CUI, the export rules for ITAR and EAR, or health-data privacy.
The principal who scoped the work does the review and the design. We read your code, infrastructure definitions, and live configuration by hand, draw the data-flow and trust diagram, and write each control as a specific change: the role, the policy, the setting. Your engineers apply the changes with us on a call or from the written instruction; we never take standing administrative access.
You receive the design set, the change list with the exact change for each item, and a mapping of every control to the standard your contract names. After the changes land we confirm each with evidence, such as before-and-after output or screenshots, and file it in the compliance package your customers and auditors expect. Design work is readiness; an independent assessor performs the assessment.
Trust boundaries, tool permissions, approval points, and one identity per agent, designed for systems that act on your behalf.
From $6,000
Scope, pricing & FAQsModel and weight integrity, inference server hardening, GPU host isolation, segmentation, and access control for on-premises, private cloud, and air-gapped deployments.
From $7,200
Scope, pricing & FAQsIdentity and keys, private networking, guardrails, data use and retention, and logging for the AI services you rent from a cloud provider, setting by setting.
From $3,600
Scope, pricing & FAQsDesign-time requirements, AI-specific threat modeling, and automated and manual gates placed in the delivery pipeline you already run, each leaving an artifact.
From $7,200
Scope, pricing & FAQsAI models and agents integrated into your security monitoring, automation, and analyst workflows with least-privilege identity, human gates on write actions, and every action logged.
From $4,800
Scope, pricing & FAQsThe selected services, deliverables, access requirements, and any follow-up validation are agreed in your engagement scope.
A focused conversation. A clear scope. A practical path to stronger security.
