Direct Answer (TL;DR)
Brilo AI Error Tracking captures, classifies, and surfaces conversation errors by recording error events, storing transcripts and telemetry, and attaching contextual metadata to each incident. It collects error logs, conversation transcripts, intent detection failures, and fallback handler occurrences so teams can triage root causes and route incidents for review or human handoff. Alerts and dashboards summarize metrics and trends so operations teams can set thresholds and monitor error rates over time. Error Tracking is configurable so you control what counts as an error and how it is routed or escalated.
How does Brilo AI log conversation failures? — Brilo AI records an error event with a transcript snippet, telemetry, and intent scores so engineers and ops can review the failure and the decision path.
What does Brilo AI consider an "error"? — In Brilo AI an error can be a failed intent match, an interrupted or incomplete response, a webhook failure, or an unexpected fallback to a human; each is recorded with context for triage.
How quickly does Brilo AI notify teams about errors? — Brilo AI can be configured to generate real-time alerts or batched reports depending on your operational preferences and alerting rules.
Why This Question Comes Up (problem context)
Enterprise buyers ask how conversation errors are tracked because production voice agents must be auditable, diagnosable, and safe. Banks, insurers, and healthcare providers need clear records when the voice agent fails intent detection, misroutes a caller, or triggers a fallback handler. Teams want to know what data Brilo AI keeps, how long it’s retained, who can see it, and what workflows exist to escalate or remediate recurring failures. Clear error tracking reduces operational risk and speeds remediation.
How It Works (High-Level)
Brilo AI Error Tracking instruments voice agent flows to emit structured error events whenever a configured failure condition occurs. Typical signals include failed intent recognition, low-confidence transcripts, TTS/ASR errors, webhook timeouts, and explicit fallback flows. Each event stores a transcript snippet, timestamps, intent scores, session metadata (caller ID, flow ID), and the routing decision that followed. Operators can filter by error type, intent, or agent version to triage.
In Brilo AI, telemetry is the stream of time-stamped diagnostic data (structured logs and metrics tied to a call). An error event is a recorded incident that includes the transcript, error code, and decision context. These artifacts support post-call analysis, root-cause investigation, and iterative model or script updates.
Guardrails & Boundaries
Brilo AI Error Tracking is designed for operational visibility, not for replacing security or legal audits. Brilo AI will not automatically expose raw PII unless your deployment and retention policies permit it; configure data redaction and retention to meet your requirements. Brilo AI will not change routing or retry logic unless you explicitly enable automated remediation workflows. A fallback handler is the configured flow that runs when the voice agent cannot confidently handle an input; it must be explicitly defined and cannot autonomously call external systems without configuration. Error Tracking will not suppress human handoff nor auto-approve transactions that require explicit human verification.
Applied Examples
Healthcare example: A Brilo AI voice agent triggers Error Tracking when it fails to extract a medication refill intent or when speech-to-text confidence falls below a threshold. The recorded transcript, intent score, and routing decision appear in the error log so clinical operations can review and route the call to a nurse triage queue or create a follow-up ticket.
Banking example: In a retail banking flow, Brilo AI logs an error event when an identity verification webhook times out or the intent recognizer returns low confidence for a funds-transfer request. The error record includes the webhook error code and the decision that routed the caller to a verification specialist.
Insurance example: Brilo AI captures errors when claims intake fields are missing after voice capture or when policy lookup returns inconsistent data. These error records support audits and help product teams refine prompts or adjust integration routing.
Human Handoff & Escalation
When an error event meets your escalation rules, Brilo AI can trigger the configured human handoff workflows. Common behaviors include creating a ticket in your CRM, opening a live transfer to a queued agent, or invoking a supervisor callback flow. Handoff behavior is controlled by routing rules and error severity: you decide which error codes route to immediate live transfer, which create an asynchronous follow-up, and which only generate an internal alert. Brilo AI preserves the session context and recent transcript on handoff so the human agent sees what the voice agent heard and why it escalated.
Setup Requirements
Provide call flow definitions and the list of intents and expected utterances you want monitored.
Configure your retention and redaction policy so Brilo AI knows whether transcripts can include sensitive fields.
Provide your webhook endpoint or CRM integration details for ticket creation and routing.
Define error types and thresholds (for example, ASR confidence, intent confidence, or webhook timeouts).
Map escalation targets (queues, email addresses, or callback workflows) and the conditions that trigger them.
Enable telemetry and logging in the Brilo AI admin console and assign access roles for reviewers.
Verify event delivery by running test calls and confirming error events appear in your monitoring view.
Business Outcomes
Brilo AI Error Tracking helps operations reduce time-to-diagnose, improve agent handoff quality, and prioritize engineering fixes by surfacing high-impact error trends. Teams can identify problem intents, faulty integration points, or script segments that cause confusion, leading to fewer repeat escalations and improved caller satisfaction. Error visibility supports safer deployments in regulated environments by keeping a clear trail of decisions and handoffs.
FAQs
What counts as an error in Brilo AI Error Tracking?
An error can be a failed intent match, low ASR/TTS confidence, webhook or integration failure, or an explicit fallback to a human. Each error event records context so you can filter and triage.
Can I redact sensitive data from error transcripts?
Yes. Brilo AI supports configurable redaction and retention policies. Work with your Brilo AI admin to define which fields to mask before they appear in logs or exports.
How do I get real-time alerts about errors?
Configure alert rules in your Brilo AI admin settings to trigger real-time notifications for specific error types or thresholds; alerts can create tickets, send emails, or invoke escalation flows as you define.
Can Brilo AI automatically retry failed webhooks?
Retry logic must be configured in your integration settings. Brilo AI can mark the original event, attempt retries, and record each retry outcome in the error event history for auditability.
Who can access error logs?
Access is controlled by Brilo AI role-based permissions. Assign reviewer roles to operations and limited access to engineers so logs are visible only to authorized reviewers.
Next Step
Contact your Brilo AI account team to enable Error Tracking and discuss retention and redaction policies.
Configure error types and escalation targets in the Brilo AI admin console and run validation test calls.
Open a support ticket with Brilo AI Support if you need assistance mapping error events to your CRM or webhook routing.