How to load test a voice agent before you launch

Voice-agent load testing should simulate production conditions by running many concurrent end-to-end conversations across speech recognition, language models, speech synthesis, tools, and telephony while measuring accuracy, latency, turn-taking, connection reliability, and cost. It distinguishes concurrency, session-start throughput, and long-duration stability, recommending steady-state, gradual ramp, sudden spike, and multi-hour soak tests because each exposes different bottlenecks such as queueing, rate limits, backpressure, memory leaks, and unclosed sessions. Testing should rely on difficult real-world telephony audio, including compression, noise, accents, interruptions, and entity-heavy information such as account numbers, while auditing transcription ground truth and prioritizing entity accuracy over aggregate word error rate. Results should use latency percentiles, particularly P95 and P99, separated between ramp and sustained periods, and should verify the actual peak concurrency reached rather than the configured target. The text also emphasizes correct audio pacing and encoding, explicit session termination to avoid misleading results and unnecessary billing, provider-limit planning, load generation through simulations, replayed calls, or SIP testing, and a pre-established rollback plan with pinned models, tested fallbacks, retry rules, and measurable thresholds for intervention.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.