

Voice is quickly becoming the default way we interact with agents, but natural conversation brings a new set of challenges like interruptions, background noise, and accents. Voice agents need to handle all of this while still completing real tasks. Existing benchmarks only measure these skills in isolation – not whether voice agents can do both at once, under realistic conditions. τ-voice tests agents in realistic voice conversations – and it's surfacing real, fast progress on real tasks. In just 8 months, pass rates jumped from ~30% to ~67%, and voice agents now retain ~79% of text capability, up from ~45%. Learn more: sierra.ai/blog/tau-voice…



















