SUMMARIZATION

On-submit Loom standup roll-up archived to Confluence

When a standup video is submitted via webhook, transcribes it, generates a per-person written summary, and appends it to a running team standup page in Confluence.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook receives submitted standupHTTP webhook
  • ActionFetch video transcriptLoomLoom
  • ActionWrite per-person summaryOpenAI
  • LogicFind or create today's section
  • OutputAppend summary to Confluence pageConfluenceConfluence

What it does

This workflow turns each submitted Loom standup into a written entry on a persistent Confluence page. When someone posts their standup through your intake webhook, it transcribes the video, writes a concise summary of their update, and appends it under that day's heading on the team's standup archive page. Over time you build a searchable, permanent record of every standup in your knowledge base.

When to use it

Use this when standups flow through a custom intake (a form, a bot, or your own app) rather than directly from Loom's feed, and you want the canonical record living in Confluence alongside your other team docs.

How it works

  1. 1An incoming webhook fires with the Loom video URL and submitter info.
  2. 2The workflow fetches the transcript for that video from Loom.
  3. 3OpenAI writes a short, structured per-person summary (done, next, blocked).
  4. 4A logic step finds or creates today's dated section on the standup page.
  5. 5The summary is appended under that section in Confluence, preserving prior entries.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect LoomVideo transcripts, libraries.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect ConfluenceSpaces, pages, blueprints.
  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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