Voice Agent Testing With TestMu AI

The Agent Testing Platform tests a voice agent the same way it tests a chat agent, except the conversation happens as audio instead of text. It holds a spoken conversation with your agent, transcribes the responses, and scores the interaction across the same 9 quality metrics. It covers voice assistants and voice-enabled support agents.

A voice agent uses the same setup as a chat agent: upload the documents that describe it, generate scenarios, and run an evaluation. The difference is the medium, audio rather than text.

How Voice Agent Testing Works

The platform conducts a voice-based conversation with your agent, following a generated scenario. The agent's voice responses are captured and transcribed, and the evaluation runs on the full audio conversation transcript.

A voice agent is functionally identical to a chat agent, so every chat feature applies: workflow-based scenario generation, test suites, endpoint profiles, the playground, thresholds, go-live assessment, and scheduled runs. See how to test a chat agent for the shared setup.

What Makes Voice Testing Different From Chat

Voice testing differs from chat in the medium, not the metrics.

Conversations with the agent are conducted as audio (WAV) instead of text messages.
The agent's voice responses are captured and transcribed for evaluation.
Evaluation runs on the full audio conversation transcript.

Features

A voice agent has all the features of a chat agent.

Workflow-based test generation with document upload and source integrations (Confluence, JIRA, GitHub).
Scenario management with AI generation, validation criteria, personas, and special instructions.
Test suites with test profile selection and run history.
Endpoint profiles with Postman collection import.
Test profiles for data-driven testing.
Playground for interactive testing.
Evaluation execution with metric selection and HyperExecute integration.
Metric threshold configuration.
Go-live assessment with a production readiness verdict.
Scheduled runs.

Metrics

Voice agents are evaluated on the same 9 quality metrics as chat agents, each scored on a 0 to 100% scale.

#	Metric	What it measures
1	Bias Detection	Detects biased, discriminatory, or unfair responses
2	Hallucination Detection	Identifies false, fabricated, or unsupported information
3	Completeness	Whether the agent fully addresses the user's question
4	Context Awareness	How well the agent understands and maintains conversation context
5	Response Quality	Overall quality, clarity, and helpfulness of responses
6	Conversation Flow	Natural flow and coherence across multi-turn conversations
7	User Satisfaction	Estimated end-user satisfaction based on conversation quality
8	File Handling Quality	Quality of file upload and download interactions, if applicable
9	File Generation Accuracy	Accuracy of generated files against requirements, if applicable

Every evaluation result includes the overall score, per-metric scores with pass or fail badges, detailed analysis, the full conversation transcript, identified strengths, areas for improvement, actionable recommendations, and validation criteria results.