CUSTOMER SUPPORT
Suggest the best macro on each new inbound ticket
When a ticket arrives in Zendesk, matches it against your existing macro library and posts the top suggested reply as a private internal note for the assigned agent.
How it runs
The automated pipeline, trigger to output.
- TriggerNew Zendesk ticket createdZendesk
- ActionLoad published macro setSupabase
- ActionRank macros against ticketOpenAI
- LogicDrop low-confidence matches
- OutputPost suggestion as internal noteZendesk
What it does
Gives agents a head start on every ticket. The moment a new request comes in, it ranks your published macros against the customer's message and drops the best match as an internal note, so the agent can accept it or tweak it instead of starting from a blank box.
When to use it
Use it on high-volume queues where speed-to-first-reply matters and most questions are variations of known issues. It augments agents rather than auto-replying, so it's safe for nuanced support.
How it works
- 1A newly created Zendesk ticket triggers the run.
- 2Load the current published macro set from Supabase (synced from your library).
- 3Send the ticket body plus the macro titles to OpenAI to pick the best match and a confidence score.
- 4Filter out low-confidence matches so agents aren't shown noise.
- 5For a confident match, format the macro text as a suggestion.
- 6Post it as a private internal note on the Zendesk ticket for the assigned agent.
Set it up
What you configure once, before turning it on.
- 1Connect ZendeskTickets, queues, knowledge base.
- 2Connect SupabaseTables, auth, storage, edge functions.
- 3Connect OpenAIModels, embeddings, files.
- 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.