CypherMonkeyAI omni-channel lab

A lifelong-learner lab on AI omni-channel agents, including voice and the contact center. Free to read. Nothing sold.

Voice AI agent stack · L2 · 15 min

Latency budgets you label

Learn in five minutes

  • LiveKit's pipeline page says voice conversations feel natural when end-to-end response latency stays under one second. That sentence is LiveKit's, not a measurement from this lab.
  • The same page says each stage of a cascaded pipeline adds delay, and streaming overlaps the stages.
  • Pipecat's overview says that in most cases the round trip happens between 500 and 800 milliseconds. That sentence is Pipecat's.
  • The Voice overview on docs.x.ai says the Voice APIs offer sub-second latency. The page calls them SpaceXSI Voice APIs, powered by Grok. That sentence is the page's.
  • This lab states no service-level agreement. The milliseconds in lab 08 are a teaching fixture.

Write each vendor sentence next to the vendor name. Do not add the three sentences into one number of your own.

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Visual

T9-R3 diagram

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Three labeled sentences

  1. Copy LiveKit's 'under one second' sentence and write LiveKit beside it.
  2. Copy Pipecat's 500 to 800 millisecond sentence and write Pipecat beside it.
  3. Copy the Voice overview's sub-second sentence and write that page beside it.
  4. Add a fourth line: this lab measured none of these.

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Quiz

Whose sentence is 'under one second' on the pipeline page?

The pipeline page says it. This lab did not time a call.

What does this page state as a service-level agreement?

Vendor sentences stay attached to the vendor.

What are the milliseconds in lab 08?

The lab file labels them as a fixture.

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Ecosystem

Labeled latency
A timing sentence copied with the vendor's name. Not a promise from this lab.

Sisters: Speech-to-text, Language model, Text-to-speech, WebRTC, SIP.

A cascaded pipeline and a speech-to-speech model are two shapes the LiveKit docs name. The xAI Speech to Speech API is a hosted speech-to-speech session.

Pin the model id, the voice, and the date you read the docs.

Config

  • Write the goal in one sentence.
  • Name the input and the allowed output.
  • Save the trace next to the result.

Troubleshooting

  • The answer looks fluent and is wrong. Check whether a source passage actually contains the claim.
  • The loop never stops. Set a step cap and stop when the tool result repeats.

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Sources and go deeper

sources.json