Voice AI Testing · Conversation QA

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Q: What does voice AI testing measure?

Voice AI testing evaluates the full conversational pipeline, not just whether the agent responds. Key measurement areas: (1) Transcription accuracy (Word Error Rate) — does the STT model correctly transcribe the caller's speech, especially with accents, background noise, and domain-specific vocabulary? (2) Intent recognition — does the agent correctly understand what the caller wants? (3) Response correctness — is the information in the agent's response factually accurate (correct property price, correct account balance, correct appointment availability)? (4) Language handling — for multilingual agents (Arabic/English, Hindi/English): does the agent detect and respond in the right language? Does it switch cleanly mid-conversation? (5) Conversation completion rate — what percentage of calls reach a defined success outcome (viewing booked, payment made, query resolved) without human fallback? (6) CRM/system update accuracy — after the call, did the agent correctly log the outcome (PTP date, lead score, booking confirmation) to the downstream system?

Q: How do you test a voice AI agent before production launch?

Pre-production voice AI testing involves: (1) Scripted scenario testing — run the agent through 200+ scripted call scenarios covering all the happy paths and key failure modes for your domain; (2) Audio simulation — inject real audio clips (recorded customer calls with identifying information removed) to test STT accuracy under real acoustic conditions; (3) Adversarial testing — callers who speak quickly, use slang, switch languages mid-sentence, interrupt the agent, or attempt to push the agent outside its scope; (4) End-to-end system testing — verify that what the agent says during the call matches what gets written to the CRM, payment gateway, or calendar system; (5) Load testing — confirm the agent handles concurrent calls at peak volume without latency degradation. We combine automated testing with human evaluators who listen to call recordings and score agent performance on domain-specific criteria.

Your voice agent works in a quiet office with a clear microphone. The question is whether it works with real callers — accented speech, background noise, language switching, interruptions, and adversarial inputs. We test it all before it goes live.

Transcription Accuracy (WER) Intent Recognition Response Correctness Arabic ↔ Hindi ↔ English Interruption Handling CRM Update Accuracy

Test My Voice Agent All Test Dimensions

Voice AI Testing — Free Scoping

Tell us your voice agent use case and languages. We'll scope the test plan in 30 minutes.

Test Dimensions

What Voice AI Testing Covers

🎙️

Transcription Accuracy (STT)

Word Error Rate measured per language, accent, and noise condition. Identifies systematic STT failures on domain-specific vocabulary (property names, loan product names, medication names) that generic benchmarks miss.

WER per language + accent variant
Domain vocabulary accuracy (property names, product codes)
Background noise performance degradation
Phone audio quality simulation

🧠

Intent Recognition

Does the agent classify what the caller wants correctly? Tests edge cases where the same intent is expressed multiple ways, and adversarial cases where the caller's phrasing could be misclassified.

Intent accuracy across 50+ paraphrase variants
Multi-intent turn handling
Out-of-scope rejection accuracy
Ambiguous intent escalation correctness

✅

Response Correctness

Is the information the agent states factually correct? For real estate: correct price + availability. For collections: correct balance + DPD. For healthcare: correct appointment availability. Measured against live system data.

Factual accuracy vs live CRM/ERP data
Hallucinated information detection
Wrong-promise detection (price guarantees, etc.)
Date and number accuracy

🌐

Multilingual Handling

For agents serving Arabic, Hindi, Tamil, and English callers: does the agent detect the language correctly, respond in the same language, and handle mid-conversation switches cleanly?

Language detection accuracy (per language)
Code-switching (Hinglish, Arabic-English) handling
Response language consistency
Dialect accuracy (Khaleeji vs MSA Arabic)

⚡

Interruption + Edge Cases

Real callers interrupt, talk over the agent, go silent, or ask questions mid-flow. We test all these — including callers who try to extract information the agent shouldn't give or take actions outside the agent's scope.

Barge-in handling (caller interrupts agent)
Silence and timeout handling
Scope boundary enforcement
Repetition and clarification requests

🔗

System Update Accuracy

The agent's conversation is only half the job. We verify that what it said during the call matches what it wrote to downstream systems — CRM lead fields, promise-to-pay date in LMS, booking in calendar.

CRM field update accuracy
PTP date and amount logged correctly
Appointment booked at stated time
Payment link sent to correct number

Domain-Specific Evaluation

Test Checklist by Agent Type

🏠 Dubai Real Estate Voice Agent

Correct property price + availability quoted?
Correct lead qualification (buy/invest/rent)?
Arabic (Khaleeji) ↔ English switch clean?
Viewing booked at correct time + broker?
WhatsApp sent with right property brochure?
CRM lead score + community assigned correctly?
Wrong promise made? (guaranteed returns, etc.)
Competitor mention handled correctly?

💰 Collections Voice Agent (NBFC India)

Correct account balance stated?
Correct loan product + EMI amount?
Promise-to-pay date recorded accurately in LMS?
Payment link sent to correct WhatsApp number?
RBI prohibited language — any violations?
Correct human escalation on dispute / legal threat?
DND number called? (should never happen)
Hindi ↔ English switch for Tier 2/3 callers?

🎧 Customer Support Agent

Correct product information stated?
Correct policy / T&C information?
Issue resolution rate without human escalation?
Hallucinated product features / pricing?
Escalation precision (right issues escalated)?
Tone and empathy on complaint calls?
Refund/replacement process followed correctly?
Ticket created with correct fields in CRM?

Evaluation Cluster

Full AI Evaluation Stack

AI Agent EvaluationFull agent QA → LLM EvaluationHallucination + accuracy → RAG EvaluationRetrieval + faithfulness → Custom Voice AIBuild it first → Dubai RE Voice AgentBuild + evaluate → Collections AgentRBI compliant →

Pricing

Voice AI Testing Pricing

Pre-launch test + continuous production monitoring. Fixed scope, clear go/no-go decision.

Pre-Launch Test

₹2L – ₹6L

One-time evaluation before go-live

200 scripted call scenarios (all key flows)
STT accuracy (WER) per language
Intent recognition accuracy
Response correctness vs live system data
Interruption + edge case testing
Go/No-Go report with specific fixes
2–3 week delivery

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Common Questions

What does voice AI testing measure?

Voice AI testing evaluates the full pipeline: Transcription accuracy (Word Error Rate per language and noise condition), Intent recognition (correct classification across paraphrase variants), Response correctness (factually accurate answers against live CRM/ERP data), Language handling (detection, switching, dialect accuracy), Conversation completion rate (% reaching a success outcome without human fallback), and System update accuracy (CRM fields, PTP dates, bookings match what was said during the call).

How do you test a voice AI agent before production launch?

Pre-production testing: 200+ scripted scenario runs covering happy paths and failure modes; real audio injection (de-identified production recordings) to test STT under real acoustic conditions; adversarial testing (fast speech, language switches, interruptions, out-of-scope requests); end-to-end system testing verifying CRM/calendar/payment outputs; domain-expert human evaluation of call recordings. We give a go/no-go recommendation with specific failing scenarios and fixes before any real callers are affected.

Can you test a voice agent that XPndAI didn't build?

Yes. We test any voice AI agent accessible via API or as a staged phone number — regardless of who built it (Vapi, Retell AI, Bland AI, custom build, or platform like Twilio Autopilot). We need the agent's test endpoint, the task specification, and any relevant live system access (CRM API for response correctness verification). We build the test suite, run it, and deliver findings.

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