CUSTOMER SUPPORT
Draft KB articles from Intercom chats only when none already covers them
When an Intercom conversation closes, checks whether an existing help-center article already answers it before drafting; if there's a gap, it writes a new article and routes it…
How it runs
The automated pipeline, trigger to output.
- TriggerIntercom conversation closedIntercom
- ActionExtract core question from transcriptIntercom
- ActionSearch existing help-center for matchOpenAI
- LogicBranch on coverage gap vs. already documented
- ActionDraft new article for the gapOpenAI
- OutputPost proposal to Slack for sign-offSlack
What it does
Guards against documenting the same thing twice. Each closed Intercom conversation is matched against your existing knowledge base; the workflow only drafts a new article when no good match exists, then posts the proposal to a Slack review channel with an approve/skip prompt.
When to use it
Use it when your help center already has decent coverage and you want to fill genuine gaps rather than create redundant pages. The Slack sign-off step suits teams that prefer lightweight approval in chat over a separate editorial queue.
How it works
- 1An Intercom conversation is closed, triggering the run.
- 2The flow grabs the conversation transcript and extracts the core question.
- 3It searches existing Intercom help-center articles for a semantic match using OpenAI embeddings.
- 4A branch checks the match score: if an article already covers the topic, the run stops and logs a skip.
- 5If the topic is uncovered, OpenAI drafts a new article with title, summary, and steps.
- 6The draft is posted to a Slack editor channel with the source thread and approve/skip actions for a human decision.
Set it up
What you configure once, before turning it on.
- 1Connect IntercomConversations, contacts, articles.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect SlackChannels, DMs, threads, mentions.
- 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.
More Customer Support workflows
Close the loop with requesters when a Linear bug moves to Done
When a Linear issue created from a support escalation moves to Done after deploy, look up the originating Zendesk tickets and notify each requester that their reported bug is…
Reopen and notify Front conversations when their bug fix deploys
When a deploy resolves a Sentry issue, find the snoozed or closed Front conversations linked to it, reopen them, and send the customer a reply that the fix is now live.
Suggest the right Loom video by classifying Intercom message intent
Reads each new inbound Intercom conversation, classifies what the customer is trying to do, and surfaces the best-matching Loom walkthrough to the agent as an internal note.
Draft personalized fix-live replies for support to review
When a Sentry issue resolves, an agent reads each linked ticket's full thread and drafts a tailored 'your fix is live' reply per requester.
Send a tailored Loom onboarding sequence on Front first-reply
When a new customer's first email lands in Front, this picks the Loom onboarding walkthroughs matching their plan and use case, builds a friendly sequenced reply.
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.
Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.