Governance & Reporting

Highflame’s Governance & Reporting capabilities are designed to help organizations operate AI systems responsibly at scale. As AI becomes embedded in critical workflows, teams need more than just security controls—they need the ability to demonstrate compliance, support audits, and provide clear evidence of responsible usage to internal and external stakeholders.

Highflame brings together long-term data retention, structured reporting, and access controls into a single governance layer. This allows security, legal, compliance, and platform teams to work from a shared source of truth, rather than stitching together evidence from disparate systems.

Audit Archive

For organizations with strict regulatory, compliance, or data retention requirements, Highflame provides an Audit Archive that captures a complete, immutable record of AI interactions.

Audit archiving can be enabled at the route level, allowing teams to selectively preserve traffic for sensitive applications or regulated workflows. Once enabled, Highflame records every request and response that flows through the route, including model inputs, outputs, and associated metadata. This creates a durable audit trail that supports internal reviews, regulatory inquiries, and third-party audits.

To support enterprise data workflows, Audit Archive data can be automatically exported to external data warehouses such as Snowflake or Redshift. This enables the integration of AI audit records into existing compliance pipelines, retention systems, and analytics environments without manual intervention.

Reporting

Capturing data is only part of governance—organizations also need to understand and communicate what the data means. Highflame’s reporting features transform raw observability and audit data into clear, concise summaries of AI usage, security posture, and compliance status.

Reports can be used to answer practical questions such as how AI resources are being used across the organization, which applications generate the most traffic, where security policies are being enforced, and how often violations occur. These summaries are designed to be consumable by both technical and non-technical stakeholders, making them suitable for leadership reviews, risk assessments, and compliance reporting.

Controls

Governance is reinforced through a set of granular controls that manage access, enforce policy boundaries, and reduce operational risk across AI resources.

Highflame supports role-based access controls that allow teams to assign precise permissions to users and groups, ensuring that only authorized individuals can modify routes, policies, or providers. Sensitive credentials, such as provider API keys, are protected in the Secrets Vault, preventing accidental exposure and enforcing secure handling by default.

Routing controls further strengthen governance by allowing teams to restrict access to specific models or capabilities for certain applications or users. This enables tighter controls on high-risk models or sensitive workloads while maintaining flexibility elsewhere.

End-to-End Governance

Together, Audit Archive, Reporting, and Controls form a cohesive governance layer that supports both operational oversight and regulatory compliance. By combining durable records, clear insights, and enforceable boundaries, Highflame enables organizations to deploy AI with confidence—knowing they can demonstrate accountability, transparency, and responsible use at every stage.