Noveum launched NovaSynth, an automated voice agent testing platform that simulates realistic callers with diverse personas, accents, background noise, and adversarial edge cases across real telephony stacks.
NovaSynth is a voice agent simulation and evaluation platform developed by Noveum to stress-test conversational AI agents against unpredictable real-world scenarios. Instead of relying on static mock transcripts or manual staging, NovaSynth conducts live calls over SIP telephony providers and real-time audio protocols like LiveKit, introducing realistic variables such as interruptions, ambient noise, varied accents, and network degradation. The system assesses and scores agent performance across more than 30 audio and transcript dimensions, highlighting conversation breakdowns, latency bottlenecks, and adversarial vulnerabilities so engineering teams can remediate failures before reaching production.
Evaluating voice agents purely on text transcripts is obsolete; the real failure modes of conversational AI emerge at the audio transport layer, latency margins, and complex turn-taking dynamics.
- –Protocol-level testing: Simulating over actual SIP and WebRTC stacks surfaces network jitter, packet drops, and audio artifacts that text-based LLM evaluators miss.
- –Realistic adversarial personas: Stress-tests agents against real human behaviors such as frequent interruptions, rapid topic switching, impatient callers, and prompt injection attempts.
- –Comprehensive scoring: Benchmarking across 30+ audio and transcript dimensions replaces subjective spot-checks with systematic, repeatable QA metrics.
- –Seamless developer workflow: Bridges simulation and observability by connecting synthetic test failures directly into Noveum's agent tracing and debugging pipeline.
DISCOVERED
1h ago
2026-09-17
PUBLISHED
6h ago
2026-09-17
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