CUSTOMER SUPPORT
Draft a KB article from repeated Intercom gaps and file it
When the same unanswerable question shows up in Intercom enough times, drafts a first-pass knowledge base article with an LLM and opens a Linear issue containing the draft…
How it runs
The automated pipeline, trigger to output.
- TriggerNew Intercom conversation (webhook)Intercom
- ActionDetect gap and extract core question (OpenAI)OpenAI
- LogicProceed only when recurrence crosses threshold
- ActionDraft a full article skeleton (OpenAI)OpenAI
- OutputOpen a Linear issue with the draft and sourcesLinear
What it does
This workflow doesn't just flag gaps — it starts filling them. It watches Intercom conversations for questions your saved replies and help center can't answer. When a question recurs past a set threshold, an LLM writes a structured first draft of a help article (title, summary, steps), and a Linear issue is opened with that draft pre-filled so a human writer edits rather than starts from a blank page.
When to use it
Use it when detection alone isn't enough and your docs backlog stalls at the writing step. Best for teams on Intercom who want to cut the time from gap to published article, while keeping a human in the loop for review.
How it works
- 1A new Intercom conversation fires the trigger.
- 2An OpenAI step decides whether the help center could have answered it and extracts the core question.
- 3A logic step tallies recurrence; it proceeds only once a question crosses the threshold.
- 4OpenAI drafts a complete article skeleton from the matched conversations.
- 5A Linear issue is created in the Docs project containing the draft and links to the source conversations.
Set it up
What you configure once, before turning it on.
- 1Connect IntercomConversations, contacts, articles.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect LinearIssues, projects, cycles, triage.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Send a tailored Loom onboarding sequence on Front first-reply
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Article Volume-Rebound Early Warning (Datadog)
Streams support ticket-tag events into Datadog, watches for topics whose volume is reaccelerating against a decaying article.
Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

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