Direct Answer (TL;DR)
Brilo AI Widget Unresolved Query Tracking lets you identify and export questions the Brilo AI voice widget could not answer, using low-confidence triggers, transcript markers, and unresolved-query analytics. When enabled, Brilo AI marks calls and widget sessions where intent detection failed or confidence scores fell below your configured threshold, and surfaces those records in the conversation log and analytics exports so you can refine prompts, knowledge content, or routing. This tracking includes a flag on the transcript, a reason code (for example: low confidence, out-of-scope, or noisy audio), and optional automatic routing to a fallback workflow or human handoff. Use these unresolved-query signals to prioritize content updates, add answer paths, or tune confidence thresholds.
Does Brilo AI flag widget questions that failed to resolve? — Yes. Brilo AI flags unresolved queries and records reason codes and transcripts so you can review and improve flows.
How are unresolved widget questions identified? — Brilo AI uses intent detection confidence scores and answer-quality checks to flag unresolved queries for review.
Can I export unresolved query data for analytics? — Yes. Brilo AI logs flagged widget sessions and includes them in transcript and analytics exports for downstream reporting.
Why This Question Comes Up (problem context)
Buyers ask about unresolved query tracking because unresolved questions create poor customer experiences and hidden operational costs. In regulated sectors such as healthcare and banking, unresolved or incorrect answers can delay service, trigger compliance reviews, or require manual follow-up. Teams need a reliable way to find where the voice widget failed—whether due to poor intent detection, low audio quality, or missing knowledge—so they can prioritize improvements without combing through raw call recordings.
How It Works (High-Level)
Brilo AI marks a widget interaction as an unresolved query when internal checks (intent confidence, answer-quality heuristics, or similarity to known out-of-scope patterns) fall below configured thresholds.
In practice, Brilo AI:
Evaluates intent detection confidence and semantic match for each user turn.
Attaches an unresolved flag and a reason code to the session transcript when thresholds are breached.
Records the transcript and metadata (confidence score, timestamp, audio quality indicators) in the conversation log for review.
In Brilo AI, an unresolved query is a session-level flag set when the system cannot produce a reliable answer. Confidence score is the numeric indicator the platform uses to decide whether to mark a turn as unresolved. For more on measurement and accuracy, see: Brilo AI how accurate are AI voice agents.
Guardrails & Boundaries
Brilo AI applies safety boundaries to unresolved-query handling to avoid unsafe fallbacks or “confidently wrong” answers. Typical guardrails include:
Do not treat low-confidence answers as resolved; instead mark unresolved and follow the fallback workflow.
Block sensitive response generation when intent is ambiguous or flagged as out-of-scope.
Limit automated escalation for high-risk topics unless a human-review route is configured.
Fallback route is the configured path (for example: voicemail, human handoff, or knowledge-base prompt) the system takes when a query is flagged unresolved. These guardrails prevent the Brilo AI voice agent from presenting unreliable information and ensure unresolved queries are routed for human review or safe handling.
Applied Examples
Healthcare example: A patient asks the Brilo AI voice widget about medication interactions. The agent’s intent confidence is low and the answer would require a clinician. Brilo AI flags the query as unresolved, attaches the transcript and confidence score, and routes the session to a nurse triage workflow for human review.
Banking example: A caller asks a complex loan qualification question that the Brilo AI voice widget cannot resolve. Brilo AI marks the session unresolved, logs the reason code as “out-of-scope,” and triggers a warm transfer to a loan officer or schedules a callback.
Insurance example: During a claims inquiry, the Brilo AI voice agent detects insufficient policy context. The widget flags the turn as unresolved and adds the transcript to a review queue for an adjuster to follow up.
Human Handoff & Escalation
Brilo AI can be configured to escalate unresolved widget queries to humans or alternate workflows. Typical handoff patterns include:
Immediate warm transfer: when the unresolved reason code indicates urgency, Brilo AI can route the call to a live agent.
Callback scheduling: Brilo AI logs the unresolved session and schedules a callback with required context.
Ticket creation: unresolved queries can auto-create a CRM ticket or support item that includes the transcript, reason code, and metadata.
Handoffs use the unresolved flag and attached metadata so the human agent receives the transcript, confidence scores, and recommended context, reducing handle time and avoiding repeated questioning.
Setup Requirements
Configure: Define unresolved thresholds (confidence score cutoffs and out-of-scope intent patterns) in your Brilo AI widget settings.
Provision: Provide Brilo AI with a webhook endpoint or your CRM integration to receive flagged session exports and tickets.
Upload: Supply initial knowledge-base content or FAQ mappings so unresolved reasons can be differentiated between “missing knowledge” and “poor audio.”
Enable: Turn on transcript logging and unresolved-query tagging in the widget configuration.
Route: Map fallback workflows—human handoff, callback scheduling, or ticket creation—in Brilo AI’s routing settings.
Test: Run controlled test sessions to verify flags, reason codes, and routing behave as expected.
For guidance on tuning audio, voice, and transcript behavior see: Brilo AI does the AI sound natural or robotic? and for accuracy and measurement see: Brilo AI how accurate are AI voice agents.
Business Outcomes
Tracking and acting on unresolved widget queries reduces manual review time, lowers repeat contacts, and helps teams prioritize high-impact knowledge updates. For regulated customers in healthcare and banking, resolving unresolved queries sooner reduces escalation risk and improves compliance traceability by ensuring that every unresolved interaction includes a clear audit trail (transcript + reason code).
FAQs
How does Brilo AI decide a question is unresolved?
Brilo AI uses configured confidence thresholds and answer-quality heuristics; when intent confidence or match score falls below that threshold, the widget marks the turn as unresolved and records a reason code.
Can I export unresolved queries for my analytics team?
Yes. Brilo AI includes unresolved flags and transcripts in conversation exports and can POST records to your webhook endpoint or CRM for downstream analytics.
Will unresolved-query flags include the transcript?
Yes. When a session is flagged unresolved, Brilo AI attaches the transcript snippet, timestamp, and metadata (confidence score, reason code) to the record for review.
Can unresolved queries trigger a human callback automatically?
Yes. You can configure fallback routing so Brilo AI schedules callbacks, creates CRM tickets, or performs a warm transfer based on the unresolved reason code and priority.
How do I reduce unresolved rates?
Review unresolved transcripts, update or expand your knowledge content, tune confidence thresholds, and add explicit fallback scripts for common out-of-scope questions.
Next Step
If you want hands-on help, collect a few unresolved examples (transcripts, timestamps, and associated reason codes) and book a configuration review with Brilo AI support so we can recommend threshold and routing adjustments.