Security Services

AI Vendor & Model Review

Evaluate the security, privacy, and operational risk of AI vendors, models, and third-party AI services before they become embedded in your business workflows.

Overview

AI vendor risk is different from traditional software vendor risk. Model training data provenance, data retention and usage policies, output ownership, subprocessor chains, model update cadence, and the distinction between hosted and on-premise deployment all affect your risk posture in ways that standard vendor review processes don't cover.

This engagement evaluates specific AI vendors, models, or third-party services against your data classification, regulatory, and operational requirements. The output is a structured risk assessment that supports procurement decisions, contract negotiation, and ongoing vendor governance — not a generic vendor questionnaire response.

What This Covers

Vendor data retention, training-data usage, and subprocessor chain assessment

Model capability, limitation, and output-ownership evaluation

Privacy and regulatory alignment review against your specific obligations

Deployment architecture review — hosted vs. on-premise vs. hybrid implications

Structured risk assessment supporting procurement and contract decisions

Operational Outcomes

What gets clearer once AI vendor risk is assessed independently.

Procurement decisions are informed by independent risk assessment, not just the vendor's marketing materials and self-reported questionnaires.
Data retention, training-data usage, and subprocessor exposure are evaluated against your actual regulatory and contractual obligations.
Contract negotiation starts from a position of informed risk rather than default acceptance of vendor terms.

You're evaluating AI vendors or models for business use and need a risk assessment that goes beyond the vendor's self-reported security questionnaire.

Engagement Flow

Scope, validate, and follow through.

Security work should prove something useful, document it clearly, and make the next move easier to execute.

Scope & authorize

Clarify environment, boundaries, timing, and who sees results.

Test & document

Evidence gathered deliberately, findings written for operators and leadership.

Remediate & retest

Fix guidance, retest support, and recurring ownership when needed.

Remediation can cycle back to scope for periodic reassessment

Pressure Profile

Pressure patterns that usually point here.

You're evaluating AI vendors or models for business use and need a risk assessment that goes beyond the vendor's self-reported security questionnaire.

Scoping Conversation

Define the right depth, timing, and follow-through.

Discovery should clarify scope, environment, timing, reporting needs, and whether the next move is testing, recurring leadership, or a compliance engagement.

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