AI AGENTS

Loom walkthrough to Confluence SOP draft

When a new Loom recording is published, transcribe it and draft a clean step-by-step SOP page in Confluence marked 'Draft - needs review', then ping the author in Slack to approve.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Loom video publishedLoomLoom
  • ActionFetch transcript and timestampsLoomLoom
  • ActionSummarize transcript into ordered SOP stepsHugging FaceHugging Face
  • ActionCreate draft SOP page in ConfluenceConfluenceConfluence
  • OutputDM author in Slack to review and publishSlack

What it does

Turns a screen-recorded Loom walkthrough into a structured written SOP and parks it in Confluence as a draft awaiting human sign-off. No one has to re-watch the video and type out the steps.

When to use it

Use it when subject-matter experts explain processes by recording Loom videos but your team needs searchable written procedures. Ideal for support runbooks, onboarding guides, and tool walkthroughs where the knowledge currently lives only in someone's screen recording.

How it works

  1. 1A new Loom video published in the watched workspace fires the trigger and passes the share URL.
  2. 2The agent pulls the recording's transcript and timestamps from Loom.
  3. 3A Hugging Face summarization model converts the spoken transcript into ordered, imperative SOP steps with section headings.
  4. 4The agent creates a Confluence page in the SOP space titled with the video name, prefixed 'Draft - needs review', embedding the source Loom link.
  5. 5A Slack DM goes to the video author with the page link asking them to verify and publish.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LoomVideo transcripts, libraries.
  2. 2
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  3. 3
    Connect ConfluenceSpaces, pages, blueprints.
  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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