Modern voice assistants don’t just need testing: they need constant, automated coverage that adapts as models and prompts evolve. That’s why tools that auto-generate test cases are needed. These systems use AI to create conversation flows, utterances, and validation scripts automatically - covering thousands of real-world variations without manual scripting.
What Auto-Generated Testing Means
Instead of hand-writing every “user says → bot replies” script, automated test-case generation tools use natural language and voice analysis to build those tests for you. They synthesize accents, re-phrasings, context shifts, and full dialogues to ensure your voice assistant interprets, responds, and recovers correctly.
These tools typically handle:
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Utterance expansion — generating intent-aligned variants automatically.
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Dialogue flow simulation — testing slot filling, error handling, and multi-turn memory.
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Regression assurance — automatically re-using and updating cases after model changes.
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Speech recognition checks — validating ASR consistency between spoken and expected inputs.
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Analytics and scoring — quantifying success rates, precision, recall, and latency.
How Cekura Fits the Definition
Cekura is an end-to-end testing and observability platform built exactly for the purpose of automating the generation, execution, and analysis of test cases for voice and chat agents.
From the agent description, Cekura’s fine-tuned model automatically creates diverse scenarios and evaluators, each with expected outcomes and success criteria. Every test includes metrics like instruction following, latency, interruption handling, and voice quality - giving teams instant insight into where the assistant performs well and where it fails.
Core Automation Features in Cekura
| Function | How Cekura Implements It |
|---|---|
| Scenario Generation | Converts agent descriptions and knowledge bases into hundreds of auto-generated test cases for complete coverage. |
| Intent Variation Testing | Uses custom personalities (accents, tone, background noise, speaking style) to emulate realistic users and linguistic diversity. |
| Dialogue Flow Validation | Runs end-to-end simulations—both inbound and outbound—verifying slot filling, tool calls, and conversation recovery. |
| Regression & A/B Testing | Auto-compares model or prompt changes across identical scenarios to ensure no degradation in performance. |
| Voice-to-Text Consistency | Audits ASR accuracy and routing correctness within the same test run. |
| Automated Metrics & Reporting | Tracks custom and AI-generated metrics—CSAT, latency, interruptions, relevancy—and visualizes them in dashboards. |
Why It Matters
Cekura eliminates repetitive manual test creation, speeds up QA for every update, and improves coverage across languages, accents, and edge-case phrasings. It enables:
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Continuous regression protection during CI/CD.
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Rapid deployment of new prompts or voice models with confidence.
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Early detection of ASR and NLU misinterpretations before they reach production.
Whether you’re testing Alexa-style assistants or custom voice IVRs, Cekura automates what QA teams used to spend weeks doing: turning test generation, execution, and analysis into a single continuous loop.
Learn more at Cekura.ai