{
 "schema": "aiblocks-page/1",
 "id": "agency-engineering-voice-ai-integration-engineer",
 "type": "agent",
 "name": "Voice AI integration planner",
 "summary": "Plan a speech-to-text system for your recordings, with the audio prep, tool choice, speaker labels, subtitles, privacy steps and quality checks.",
 "headline": "Voice AI integration planner",
 "subhead": "Describe your recordings, how many you have and where the text must go. The agent plans each stage of a speech-to-text pipeline, from audio clean-up to the transcript, speaker labels and subtitles. You get a stage-by-stage plan with checks for each stage.",
 "job": {
  "id": "work-with-audio",
  "name": "Turn speech into text and back"
 },
 "level": "intermediate",
 "thinking": "high",
 "tested": true,
 "updated": "2026-10-28",
 "first_published": "2026-10-26",
 "inputs": [
  {
   "type": "question",
   "required": true,
   "label": "Question",
   "what": "the problem, decision or piece of work you want help with, and what a good outcome looks like"
  }
 ],
 "outputs": [
  {
   "type": "plan",
   "required": true,
   "label": "Plan",
   "what": "a dated plan: what to do, in what order, with a decision rule for each step"
  }
 ],
 "you_give": [
  "What your recordings are, such as support calls, podcasts or interviews, and how long they run",
  "How many you have, and whether they arrive in batches or one by one",
  "Languages and accents, and how noisy the audio is",
  "What you need out, such as plain text, subtitles, speaker labels or action items",
  "Where the text must go, such as your website, a spreadsheet or a summary tool",
  "Privacy limits, budget and speed needs (optional)"
 ],
 "you_get": [
  "A stage-by-stage plan from audio file to finished transcript, with what each stage does",
  "A choice between local and cloud transcription, with the trade-offs for your case",
  "Audio clean-up steps, a splitting plan for long files, and speaker-label and subtitle steps",
  "A privacy and storage checklist for the audio and the text",
  "Quality checks to run at each stage, and a small test to try before you scale up"
 ],
 "use_when": [
  "You have hundreds of interviews, calls or podcast episodes to turn into text and need a plan that scales.",
  "Your transcripts come out garbled on noisy, long or multi-speaker recordings and you do not know which stage is at fault.",
  "You need subtitles (SRT or VTT) or speaker-labelled text to feed a summary tool or your website.",
  "You must decide whether private recordings can go to a cloud service or must stay on your own machine."
 ],
 "skip_when": [
  "You just want one audio file turned into text today: use the Whisper speech transcriber.",
  "You want a summary and action items from one meeting recording: use the Audio meeting notes writer.",
  "You want to turn text into speech: use the Voiceover maker.",
  "You want a video in another language: use the Video dubbing editor.",
  "You need a legal or medical compliance sign-off for call recordings. A plan is not one: ask a qualified professional."
 ],
 "output_sample": {
  "input": [
   "What your recordings are, how many and how long",
   "Languages, noise level and the outputs you need",
   "Where the text must go, and any privacy limits"
  ],
  "prerequisites": [
   "An AI that reads pasted text, such as Claude, ChatGPT or Gemini",
   "Python, ffmpeg and a transcription tool, only if you want to run the code it writes"
  ],
  "output": [
   {
    "name": "Goal",
    "contains": "Your audio, languages, needed outputs and destination in one short block."
   },
   {
    "name": "Pipeline plan",
    "contains": "Each stage in order, with what it does, what can go wrong and how to check it."
   },
   {
    "name": "Local or cloud",
    "contains": "A pick with reasons based on privacy, cost, speed and language coverage."
   },
   {
    "name": "Outputs",
    "contains": "Each file you get, such as plain text, subtitles or speaker-labelled text, and who uses it."
   },
   {
    "name": "Privacy and storage",
    "contains": "How audio and text are handled, kept and deleted, and what private data is removed."
   },
   {
    "name": "Test plan",
    "contains": "Three kinds of recordings to try first and what a pass looks like for each."
   },
   {
    "name": "Open checks",
    "contains": "Assumptions to confirm, such as vendor terms or your own privacy rules."
   }
  ]
 },
 "output_shape": "GOAL\n  Audio <type, length, count> | Languages <list> | Need <outputs> | Destination <where>\n\nPIPELINE PLAN\n  <stage> | <what it does> | <what can go wrong> | <check>\n\nLOCAL OR CLOUD\n  Pick <local, cloud or mix> | Why <privacy, cost, speed, languages>\n  Open question <what to verify with the vendor or your own test>\n\nOUTPUTS\n  <transcript, subtitles, speaker labels, data file> | <format> | <who uses it>\n\nPRIVACY AND STORAGE\n  <rule> | <how the plan meets it>\n\nTEST PLAN\n  <recording type> | <what to compare> | <pass looks like>\n\nOPEN CHECKS\n  <assumption> | <who confirms it>",
 "how_to_use": [
  "Add the pack to your AI as a skill. Or open a new chat and paste SKILL.md, then references/source-agent.md.",
  "Describe your recordings, volume, languages and the output you need. Add any privacy rules, such as \"audio may not leave our network\".",
  "Ask for the plan first. Say \"Plan only. Do not write code yet.\" Your AI asks once for anything missing.",
  "Read the local versus cloud choice and the privacy section before the rest. Fix anything that does not match your rules.",
  "Ask for code for one stage at a time. You need a person or tool that can run it, such as Python and ffmpeg. A chat AI cannot run it for you.",
  "Test the plan on three of your own recordings, one clean and two hard. Compare the text to what you hear before you scale up."
 ],
 "checks": [
  "The result addresses your actual task and cites the evidence used.",
  "Examples, role-play experience and targets are kept separate from verified results.",
  "Claims of tests, memory, tool access or completed actions match what actually happened."
 ],
 "next": [
  {
   "name": "Subtitle and transcript maker",
   "url": "https://useaiblocks.com/skills/subtitle-and-transcript-maker",
   "why": "Subtitle and transcript maker"
  }
 ],
 "source": {
  "by": "Michael Sitarzewski and Agency Agents contributors",
  "repo": "msitarzewski/agency-agents",
  "url": "https://github.com/msitarzewski/agency-agents/blob/b37b5bb33b78f2c1d6567d98e25ca818e3259219/engineering/engineering-voice-ai-integration-engineer.md",
  "licence": "MIT",
  "original_name": "Voice AI Integration Engineer",
  "commit": "b37b5bb33b78f2c1d6567d98e25ca818e3259219"
 },
 "credits": [
  {
   "title": "Voice AI Integration Engineer",
   "by": "Michael Sitarzewski and Agency Agents contributors",
   "url": "https://github.com/msitarzewski/agency-agents/blob/b37b5bb33b78f2c1d6567d98e25ca818e3259219/engineering/engineering-voice-ai-integration-engineer.md",
   "used": "Original agent profile, preserved in references/source-agent.md; AI Blocks adds setup and review instructions."
  }
 ],
 "files": [
  "LICENSE",
  "references/source-agent.md",
  "SETUP.md",
  "source.json"
 ],
 "links": {
  "page": "https://useaiblocks.com/agents/agency-engineering-voice-ai-integration-engineer",
  "markdown": "https://useaiblocks.com/agents/agency-engineering-voice-ai-integration-engineer.md",
  "json": "https://useaiblocks.com/agents/agency-engineering-voice-ai-integration-engineer.json",
  "instructions": "https://useaiblocks.com/skills/agency-engineering-voice-ai-integration-engineer/SKILL.md",
  "download": "https://useaiblocks.com/skills/agency-engineering-voice-ai-integration-engineer.zip",
  "api_item": "https://useaiblocks.com/api/v1/items/agency-engineering-voice-ai-integration-engineer",
  "api_document": "https://useaiblocks.com/api/v1/documents/agent/agency-engineering-voice-ai-integration-engineer",
  "mcp": "https://useaiblocks.com/mcp"
 }
}
