Yes. Brilo AI provides Audit Logs that capture performance logs and event-level telemetry so customers can review how the Brilo AI voice agent behaved during calls and background processing. Audit Logs record key events (for example: call start/stop, model decisions, routing changes, transcript generation, and webhook deliveries) and are accessible to customers through Brilo AI’s administrative interfaces and export endpoints when enabled. These logs support operational review, troubleshooting, and internal audits, while being subject to retention and access controls set by your Brilo AI account team.

Are performance logs available for auditing?

Enterprises ask about Audit Logs because regulated teams and platform owners need a verifiable event trail for investigations, SLA verification, and operational tuning. Buyers want to know whether Brilo AI’s platform records decision points (routing, transcript generation, answer selection), what performance metrics are captured, and how long those records are available. This question also helps security and privacy teams assess whether logs meet their internal audit, retention, and role-based access controls before production deployment.

Brilo AI collects event-level telemetry from the Brilo AI voice agent during call handling and background processing. Events include call lifecycle markers (ring, answer, hangup), transcript creation, intent detection outcomes, routing decisions, and webhook attempts. Customers can retrieve these Audit Logs via the Brilo AI admin console or export endpoints to integrate with downstream SIEM or log stores.

An Audit Log is the chronological record of events and decisions emitted by the Brilo AI voice agent for a given call or workflow. A Performance Metric is a captured measurement such as processing latency, transcription time, or webhook response time associated with an event.

For a practical overview of the types of call analysis and telemetry Brilo AI captures, see the Brilo AI resource on call analysis: Brilo AI call analysis overview — What Is AI Call Analysis.

Related technical terms: audit trail, telemetry, event stream, call metadata, transcription, observability.

Brilo AI’s Audit Logs are designed for operational transparency, not as the primary long-term archive for sensitive transcripts or regulated records. Logs include metadata and pointers (for example, transcript IDs) but may not include full audio or verbatim transcripts unless your account is configured to store them. Access to Audit Logs is controlled by role-based permissions and account-level retention policies configured by your Brilo AI administrator.

Sensitive Content Redaction is the configuration that strips or masks personally identifiable or sensitive fields from logs and transcripts before they are written to storage.

Brilo AI enforces these boundaries:

For information about how Brilo AI uses speech analytics and the scope of captured signals, see: Brilo AI speech analytics capabilities.

Healthcare example

A hospital call center deploys Brilo AI voice agents for appointment booking. Audit Logs show call start/end, confirmation prompts read by the Brilo AI voice agent, and webhook delivery to the scheduling system. The operations team uses these logs to verify that outbound webhooks were accepted by the scheduling API and to troubleshoot failed deliveries.

Banking / Financial services example

A bank uses Brilo AI for balance inquiries. Audit Logs record each routing decision the Brilo AI voice agent made (for example, transfer to live agent after failed authentication attempts) along with processing latency. Compliance and operations use the event trail to reconstruct incidents and confirm that escalation rules fired as expected.

Insurance example

An insurer reviews Brilo AI Audit Logs to validate that claims intake calls recorded required metadata and that transcript generation completed before claims were created in the CRM. Performance logs help identify slow webhook endpoints that increased overall call handling time.

When configured, Brilo AI voice agent workflows emit Audit Log events at handoff points. Typical entries include the trigger (for example, user requested an agent or confidence threshold breached), the selected routing target (queue or agent ID), and the result of the handoff attempt (successful transfer, timed out, or fallback). The event record includes timestamps and any reason codes the Brilo AI voice agent used.

Brilo AI can be configured to:

These entries make it straightforward to trace whether a human handoff occurred and why.

Brilo AI Audit Logs support faster incident resolution, clearer root-cause analysis, and verifiable event trails for operational reviews. Customers typically use these logs to reduce mean time to resolution (MTTR) for call failures, validate SLA adherence, and provide auditors with a chronological record of system behavior. Logs also feed performance monitoring and capacity planning for the Brilo AI voice agent.

Do Brilo AI Audit Logs include full call audio and verbatim transcripts?

Audit Logs primarily capture event metadata and pointers to transcripts or audio. Full audio or verbatim transcripts are stored only when your account is configured to retain them; consult your account settings or Brilo AI support to enable audio or transcript retention.

How long are Audit Logs retained?

Retention is configurable per account and subject to your contract and account-level settings. Work with your Brilo AI account manager to set retention that matches your audit and operational needs.

Can I export Audit Logs to my SIEM or cloud log store?

Yes. Brilo AI supports exporting event streams and batch exports to external endpoints. You will need to provide a secure webhook or ingestion endpoint and test the export workflow as part of setup.

Are Audit Logs searchable through the Brilo AI console?

Brilo AI provides administrative search and filtering for recent Audit Logs; for long-term or large-scale search, exporting logs to your log store or SIEM is the recommended approach.

Will Audit Logs show decisions made by the AI (for example, intent classification)?

Audit Logs include decision metadata such as detected intent, confidence scores, and routing outcomes when configured to do so. You can choose which decision-level fields are recorded based on your privacy and operational requirements.