Multi-Cloud AI Service Consumption Auditing

We parse AWS Cost and Usage Reports, Azure Cost Management, and GCP Billing data to attribute every dollar of AI service spend (e.g., Amazon Bedrock, Azure OpenAI, Vertex AI) to specific teams, projects, and individuals. This enables precise internal showback, eliminates cost sprawl, and provides the data foundation for FinOps initiatives.

Our audit correlates API logs with your internal AI usage policies to flag violations in real-time. We detect unsanctioned model usage, data exfiltration to external AI services, and usage that breaches data residency or compliance rules (e.g., GDPR, HIPAA), triggering automated alerts to security teams.

Beyond identification, we provide a technical roadmap for cost optimization. This includes rightsizing underutilized instances, identifying opportunities to switch to reserved capacity or committed use discounts, and recommending more efficient model choices based on actual usage patterns, typically identifying 15-30% in potential savings.

We deliver a single pane of glass for all AI consumption across AWS, Azure, and GCP. This eliminates the manual reconciliation of disparate cloud consoles, providing CTOs and engineering leads with consolidated views of spend, usage trends, and risk exposure across their entire hybrid environment.

We engineer immutable logs that trace AI service usage back to individual API calls and user identities. This creates a defensible audit trail essential for internal audits, external compliance demonstrations (e.g., for ISO/IEC 42001, SOC 2), and post-incident forensic analysis following a security event.

By continuously monitoring consumption, our audit acts as a primary control for Shadow AI Detection and Security Posture Management (AI-SPM). It provides the quantitative evidence needed to justify policy enforcement, guide secure AI-SPM Integration with SIEM/SOAR, and remediate high-risk deployments identified during a Shadow AI Risk Assessment.

Audit AI usage across trading desks, research teams, and customer operations to detect policy violations, prevent data leakage of PII/PHI, and optimize multi-million dollar cloud AI bills. Essential for FINRA, SOX, and PCI-DSS compliance.

Learn more about our approach to shadow AI risk assessment for financial services.

Identify unsanctioned AI tools processing Protected Health Information (PHI) across research, clinical, and administrative teams. Our auditing provides the granular attribution needed for HIPAA compliance audits and prevents costly data breach incidents.

Our expertise in privacy-preserving AI computation complements this auditing layer.

Gain visibility into AI service consumption across engineering, product, and sales teams to implement showback/chargeback, prevent credential sprawl, and secure proprietary code and customer data from exfiltration via AI copilots.

Directly integrate findings with AI Copilot and Assistant Usage Fencing.

Monitor AI tool usage by legal teams to ensure client confidentiality is maintained and billing for AI-assisted research is accurate. Detect usage of unsanctioned models that could compromise attorney-client privilege or lead to malpractice risks.

Map and audit all AI service consumption in environments requiring CMMC, ITAR, and FedRAMP compliance. Provide evidence that no sensitive data is processed by unauthorized, external AI models, closing a critical attack vector.

This service aligns with our work in sovereign AI infrastructure.

Audit AI usage from R&D to factory floor operations, attributing cloud costs to specific product lines and preventing IP leakage through AI-powered design and diagnostic tools. Essential for securing trade secrets in global supply chains.

Connect audit data to smart manufacturing AI copilots.