The outcome

Learn the interaction loop using a small task with a clear outcome.

LiveKit is a Open-source realtime framework and cloud platform for voice, video, text, telephony, and multimodal AI agents. Building low-latency voice assistants, multimodal room participants, phone agents, realtime translation, tool-using conversational workflows, and human handoffs. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.

Before you begin

Set the boundary before the tool starts.

Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.

Troiana principle

AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.

Step by step

A workflow you can repeat.

  1. 01

    Define the caller, purpose, allowed topics, identity disclosure, languages, latency, interruption behavior, tools, consent, recording, retention, accessibility, and human handoff.

  2. 02

    Prototype with minimum synthetic data and the simplest STT-LLM-TTS or realtime pipeline, keeping credentials server-side and every tool read-only or sandboxed.

  3. 03

    Test noisy audio, silence, accents, crosstalk, barge-in, hallucination, unsafe requests, tool failures, latency, disconnection, and escalation while capturing approved metrics.

  4. 04

    Add authentication, authorization, disclosure, redaction, rate and spend limits, monitoring, emergency stop, and human review before a narrow production canary.

Working standard

What good use looks like.

  • State the outcome before the background.
  • Provide the real source material.
  • Review the result before expanding the task.

Realtime agents can hear, transcribe, infer, speak, call tools, and initiate telephony actions before a reviewer can intervene. Hidden observation, recording, voice cloning, payment or identity collection, and cross-provider routing carry serious consent and privacy risk. LiveKit Inference is zero-data-retention by default, but plugins, observability, recordings, telephony, and external models have separate policies. Require clear disclosure, least-privilege tools, explicit confirmation, human handoff, and an immediate kill switch.

Official references

Check the current product documentation.

Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.