OTHER

Daily Multilingual Voice Digest of Status Updates

On a schedule, gathers the day's customer-facing status notes, generates a short spoken digest in each supported language with ElevenLabs.

CategoryOther
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerScheduled trigger before shift start
  • ActionFetch last 24h of status notes from PostgresPostgreSQLPostgres
  • ActionSummarize into spoken-style script per languageOpenAI
  • LogicSkip languages with no updates today
  • ActionGenerate audio digest per languageElevenLabsElevenLabs
  • OutputPost digest to regional Slack channelsSlack

What it does

Each morning the workflow pulls the latest customer status notes from a Postgres table, condenses them into a tight script, and produces a spoken digest in every supported language. The finished audio clips are posted into the right regional Slack channel so support and CS teams start the day with an audio briefing in their own language.

When to use it

Use this when distributed support teams need a fast daily catch-up on incidents, releases, or policy notes and prefer a 60-second listen over a wall of text. It is ideal for hands-busy ops teams and markets where audio uptake beats email open rates.

How it works

  1. 1A scheduled trigger fires each morning before shift start.
  2. 2A Postgres query fetches the past 24 hours of published status notes.
  3. 3An OpenAI step summarizes them into a short, spoken-style script per language.
  4. 4A logic step skips languages with no relevant updates so quiet days stay quiet.
  5. 5ElevenLabs renders each script into an MP3 voice digest.
  6. 6The clip is posted to the matching regional Slack channel as the morning briefing.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect PostgresAny Postgres URL — query, write, migrate.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ElevenLabsText-to-speech, voice cloning.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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