Home/Services/AI Governance/AI Product Security and Assurance
AI Governance
AI Product Security and Assurance
Assess the AI features in your product for prompt injection, data leakage, output handling, access control, tenant isolation, and evaluation practice.
What it covers
The engagement in detail
Assessment of artificial intelligence capability embedded in a client's own product, covering prompt injection and manipulation, training and inference data protection, output handling and downstream trust, model access controls, tenant and customer data isolation, evaluation and red teaming practice, and the disclosures the product owes its users.
Who it is for
Designed for growth-stage and venture-backed companies building the security program enterprise customers require, and software and SaaS companies, and organizations running business-critical in-house applications.
What you receive
Deliverables from this engagement
- Threat assessment
- Control findings
- Evaluation program design
- Remediation plan
Terms
How an engagement works
Every engagement is scoped individually and conducted under a nondisclosure agreement and a master services agreement, beginning with a scoping conversation and a written statement of work that defines scope, deliverables, and sequence. The four steps this practice follows are set out in full on the AI Governance page.
- Secure a product, application, or cloud
- Establish governance and policy
- Growth-Stage & Startup Companies
- Software and SaaS Companies
AI Governance
Other services in this practice
Govern the AI you build, buy, and use, against ISO 42001, the NIST AI Risk Management Framework, and emerging state law.
- AI Governance Program DevelopmentDesign an AI governance program on the NIST AI RMF and ISO/IEC 42001: decision rights, policy, use case intake, risk assessment, oversight, and monitoring.Governance
- AI Regulatory Readiness AssessmentGap assessment against the EU AI Act, the Colorado AI Act, the Texas Responsible AI Governance Act, and sector expectations for AI accountability.Regulatory
- AI System Inventory and Use Case Risk ClassificationDiscover and catalog the AI systems in use across your organization, whether built, bought, or embedded, and classify each use case by risk.Governance
- Shadow AI Discovery and GovernanceFind unsanctioned AI use, measure the data exposure it creates, and replace it with sanctioned tools, acceptable use standards, and technical controls.Governance
- AI Vendor and Model AssessmentEvaluate AI providers and models for data handling, training provenance, security, reliability, contract protections, and regulatory obligations.Transactions
- AI Risk Assessment and Ongoing MonitoringRecurring assessment of deployed AI systems for fairness, reliability, transparency, security, and regulatory fit, with the documentation regulators expect.Risk and maturity
Start with a confidential conversation
Thirty minutes on whether this is the right engagement for the question you have been asked, and what it would take to answer it.