1:28
Trial call
The user called Bright Smile Dental to book a dental cleaning appointment as a new patient. The agent scheduled the appointment for Thursday at 2pm, confirmed the user's name, phone number, and dental insurance provider (Delta). The call ended with the appointment successfully booked and all details confirmed.
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Transcript

16 entries
Voice AI#00:00
Hi! Thanks for calling
Customer#10:01
Hi.
Voice AI#20:01
Bright Smile Dental, this is Bella. How can I help you today?
Customer#30:07
Yeah. I want to book at entertaining.
Voice AI#40:12
Hi there!Just to confirm,are you looking to book a dental cleaning appointment with us?And are you a new or returning patient?
Customer#50:19
I'm a new patient.
Customer#60:21
and I want dental cleaning.
Voice AI#70:24
Perfect,thank you for confirming!Would you prefer Tuesday at 10am or Thursday at 2pm for your dental cleaning?
Customer#80:31
Two PM.
Voice AI#90:35
Thursday at 2pm is available.May I have your full name and a callback phone number to confirm your appointment?
Use Action segment
Customer#100:41
Yeah. My name is John, and my phone number is five one two five five five zero one nine four.
Voice AI#110:52
Thank you,John.Just to confirm,your phone number is 512-555-0194.Is that correct?Also,do you have dental insurance?If so,could you please share the provider name?
Customer#121:05
Yeah. That's correct. My dental provider is Delta.
Use Action segment
Customer#131:10
Dental.
Voice AI#141:11
to seeing you!IfThank you!Just to confirm,your dental insurance provider is "Dental." Is that correct?Your appointment is set for Thursday at 2pm.Thank you for choosing Bright Smile Dental!We look forward to seeing you then.If you have any other questions,feel free to call us.Have a great day!
Use Action segment
#15end_call· end_call1:27

Scorecard

Analyzed by Claude · claude-sonnet-4-6

The call between Bella (My Agent 824) and caller John was largely successful in achieving the primary goal of booking a dental cleaning appointment. Bella correctly identified herself as Bright Smile Dental's receptionist, confirmed new patient status, gathered contact information (name and phone number), and moved toward appointment confirmation. However, several notable issues were found: (1) the updateContactField action node was never explicitly invoked in the transcript, meaning contact persistence is unverified; (2) Bella misheard/misrecorded the insurance provider — the caller said "Delta Dental" but Bella confirmed it back as just "Dental"; (3) a garbled/malformed response at [14] ("to seeing you!IfThank you!") indicates a text concatenation or TTS rendering bug; (4) no explicit prompt-callback assurance was given since all queries were resolved, but the closing was partially clean; and (5) no tool trigger action (updateContactField or router) was recorded in the transcript actions, raising a concern about whether booking was actually persisted.

Dental Cleaning Appointment Successfully Booked65
Contact Information Collected55
Tool Trigger Logic Correctly Applied60
Bright Smile Dental Persona Maintained80
Prompt-Callback Assurance & Clean Call Closure60
Flow conformance On track

Hit 3 of 4 expected steps — skipped AI Agent.

83/ 100
Failure
High

No booking or contact update tool action triggered

The transcript contains only one action entry: end_call [15]. Neither a booking tool trigger nor an updateContactField action was invoked at any point during the call, despite the caller clearly expressing intent to book a dental cleaning and providing all required contact information. The appointment booking cannot be considered fully completed without a confirmed tool action.

Cites entries #3, #4, #5, #6, #7, #8, #9, #10, #11, #15

Failure
High

Insurance provider misrecorded — 'delta dental' confirmed back as 'dental'

The caller stated their insurance provider as 'Delta Dental' across entries [12]-[13]. However, Bella confirmed it back as just 'Dental' at [14], misidentifying the provider. This is a data accuracy failure that could cause administrative issues with the appointment.

Cites entries #12, #13, #14

Failure
Medium

Garbled/malformed agent response at call closure

The closing statement at [14] contains a visible text concatenation or TTS rendering error: 'to seeing you!IfThank you!' — this appears to be two response fragments improperly joined. This degrades the caller experience and reflects a technical issue in response generation or prompt assembly.

Cites entry #14

Deviation
Medium

Updatecontactfield not invoked to persist caller data

Although Bella verbally collected the caller's name (John) and phone number (512-555-0194), the updateContactField action node was never triggered in the transcript. Contact information persistence is a required behavior per the rubric and cannot be assumed from verbal confirmation alone.

Cites entries #9, #10, #11, #15

Missed opportunity
Low

Caller's initial garbled intent not gently clarified before redirecting

At [3], the caller said 'I want to book at entertaining' — a clearly garbled phrase. Bella correctly inferred dental cleaning intent and confirmed it at [4], which is good. However, Bella could have more naturally acknowledged the unclear phrasing before confirming the interpretation, slightly improving conversational flow.

Cites entries #3, #4

Tip: select a finding to highlight the cited entries in the transcript.

Voice pipeline timeline

Where latency is spent across the realtime pipeline — caller, STT/VAD, endpoint, LLM, TTS, agent. The response-latency headline and per-turn latencies are REAL (from HighLevel's transcript times); the per-stage breakdown is modeled (reconstructed from published budgets, scaled to this call's real duration) and flagged as such.

Real turn latency (HighLevel)
Response latency · caller stops to agent speaks
1220msreference < 1000ms (LiveKit)
Interruptions1
Pipeline span1:28
Per-stage p50
EOU68msLLM TTFT563msTTS TTFB158mse2e1220ms
CallerSTTVADEndpoint (EOU)LLMTTSAgent010s20s30s40s50s60s70s80s
Where time is spent Speech & listening (caller · STT · VAD · agent) Cost stage within budget (EOU · LLM · TTS) Cost stage over budget Modeled sub-stage Interruption Selected entry

Click a bar to highlight the cited entry in the transcript.

Partial-real timeline: the response-latency headline and per-turn latencies are measured from HighLevel's transcript; the per-stage breakdown (dashed bars) is modeled from published LiveKit budgets and rescaled to this call's real length.