How to keep audit-ready logs of every LLM call: Retention, export, and compliance

Standard logging practices for Large Language Models (LLMs) often fall short during audits due to incomplete records, short retention periods, editable logs, difficult export processes, and broad access, which compromise the ability to provide proof of specific interactions. Audit-ready LLM logs must capture comprehensive details such as the full prompt and response, tool activity, model versions, timestamps, user identifiers, metadata, and ensure records are tamper-evident. Braintrust offers solutions by structuring these logs into spans that include tool calls, responses, and metadata for easier inspection and compliance. It supports custom retention policies, immutability features, and export paths to streamline audit and incident review processes. Access control is managed through role-based permissions and hybrid deployments, enabling organizations to maintain data within their own infrastructure, which is crucial for adhering to regulations like HIPAA, SOC 2, and GDPR. The platform provides flexibility in deployment and retention settings to meet varied compliance needs while ensuring data security and audit readiness.

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