Automated testing

Hamming automatically generates test cases from your agent's prompt and configuration. When you import your agent from LiveKit, Pipecat, ElevenLabs, Retell, Vapi, or any custom platform, we analyze your system prompt and create diverse test scenarios covering happy paths, edge cases, and failure modes.

You can also convert production calls into replayable test cases with one click, building a regression suite from real-world interactions.

Yes. Hamming supports multilingual testing with multiple English accents (American, British, Indian, Australian, and more) plus simulated callers in other languages. You can also simulate background noise environments to test real-world conditions.

Hamming covers 65+ languages and accents. Test how your agent handles accents, code-switching, and bad audio before they cause issues in production.

Default workspaces support 50 parallel calls, configurable up to 100+. For enterprise customers, we've run 50K+ concurrent test calls. The concurrency limit is typically determined by your voice platform's concurrency allocation.

This means you can test thousands of scenarios in minutes rather than weeks of manual testing.

Hamming provides a full REST API for programmatic access to all platform features. You can trigger test runs, retrieve results, and fail builds based on pass rates, all from your existing CI/CD workflow.

Teams typically run Hamming tests on every PR that touches agent prompts or tool configurations, catching regressions before they reach production.

It depends on your constraints and timeline. Building can make sense if you have unique requirements, strict data residency needs, or testing is core to your product. For most teams, buying accelerates time-to-coverage without tying up engineering bandwidth.

We break down the decision framework, tradeoffs, and hybrid paths in our Build vs Buy guide.

Hamming reaches 95%+ agreement with human evaluators by using higher-quality models and audio-based evaluation.

Our two-step evaluation pipeline first determines relevancy (should this guardrail apply?), then evaluates, which eliminates false failures from irrelevant checks.

Yes. Hamming's test plans feature supports sequences where the same persona calls multiple times: book an appointment, then reschedule, then cancel. The system maintains memory across calls.

This is essential for testing appointment workflows where you need existing data (you can't cancel an appointment that doesn't exist).