Break it in staging. Not in production.
Run real calls against your agent with simulated callers built from the conversations your customers actually have. Test different personas, accents, edge cases, and adversarial behavior, then score every call with the same evals you use in production.
Stop calling your own agent to test every release.
Automate realistic conversations at scale and find out whether your agent still works before you ship it.
AI-generated scenarios
Build scenarios from your real call types. Test cooperative callers, angry callers, ramblers, interrupters, and everything in between — from the happy path to the cases most likely to break your agent.
Real SIP calls
These aren't text-based mocks. Tuner calls your agent over SIP, so you test the full voice stack — telephony, ASR, LLM, TTS, and the conversation between them.
Inbound & Outbound
Test both sides of the call. Simulate customers calling your agent, or have your agent make calls to simulated customers.
Rapid iteration
Run a simulation, inspect the results, make a change, and run it again. Validate a fix in minutes instead of waiting for production traffic.
Test the callers your happy path ignores.
Real callers interrupt, change their minds, misunderstand questions, go off topic, and ask for things your happy path never planned for. Build tests around those conversations.
Stress-test specific flows
Target a specific flow — booking, refunds, identity verification, escalation — and test what happens when the caller takes it somewhere unexpected.
Routine and pressure scenarios
Run routine scenarios to verify the baseline, then add callers designed to challenge the agent. Find the cases where it starts to lose the conversation.
Reusable caller profiles
Define a caller once — accent, verbosity, patience, interruption style — and reuse the profile across scenarios and test suites. Change the profile once and every test using it picks up the change.
Multilingual and multi-accent
Test the languages and accents your agent actually encounters, including code-switching and non-native speakers. Reuse the same caller profiles across any scenario.
Make the environment as messy as reality.
A voice agent that works in a quiet room can behave very differently when the caller is in traffic, a café, or a noisy office. Test those conditions before your customers do.
Add realistic background noise
Simulate cafés, traffic, offices, and other environments where real calls happen.
Test speech recognition under stress
See how background noise and difficult audio affect what the agent hears.
Measure the downstream impact
Connect audio conditions to transcription, latency, turn-taking, and conversation quality.
Make edge cases reproducible
Save the conditions that caused a failure and run the same scenario again after every change.
Coming SOON
Turn production failures into regression tests.
When a call breaks in production, don't just fix it — turn it into a test that prevents it from ever breaking again. Then gate every deploy on the full suite, so conversation quality is validated the same way your unit tests validate logic.