On June 24, 2026, ElevenLabs published a technical guide detailing actionable techniques for reducing end-to-end voice agent latency, breaking down the delay across six pipeline stages: capture, speech-to-text (STT), network, language model (LLM), text-to-speech (TTS), and playback. The company provided real-world latency ranges, including a median (P50) time-to-first-audio (TTFA) of ~680ms and a worst-case (P95) of ~1560ms, highlighting that LLM inference and endpointing are the largest contributors. The article emphasizes that overlapping pipeline stages, tuning silence thresholds, and streaming partial transcripts can recover significant time. According to Futurum Group's 1H 2026 AI Platforms Decision Maker Survey (n=820), 56% of organizations cite support and customer experience as their leading GenAI use case, with reliability and hallucination management now the top adoption challenge at 55%. The guide notes that optimizing voice agent latency requires a holistic system approach, as each pipeline stage adds measurable delay, and the largest controllable cost is often endpointing, not inference.