Automate Your Customer Support Busywork with AI Agents

Ticket triage, reply drafts, SLA alerts, and CSAT reports. Describe the task in one sentence, the agent does it across your helpdesk and apps.

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CUSTOMER SUPPORT AGENT

Triage the overnight queue and route every ticket by topic and priority

Find duplicate tickets from the same customer and merge the context

Draft a reply for a ticket using your help docs and the customer's history

Turn a customer bug report into a clean ticket for engineering

Find unhappy customers from recent low CSAT scores and prep recovery

Assemble the weekly support report without opening a single tab

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Any Support Task. One Message. Done.

A messy queue, a tricky reply, a CSAT dip. Tell the agent what you need and it works across your helpdesk, Slack, Sheets, and 1,500+ apps.

Get Work Done With Simple Chat Messages

Pull every unassigned ticket from the helpdesk that came in since 6 PM yesterday. Read each one and tag it by topic (billing, bug, how-to, account access, feature request). Set priority based on language and customer plan: urgent for anything mentioning 'down,' 'broken,' or 'charged twice,' high for paying customers, normal for the rest. Route billing tickets to the billing queue, bugs to the tier-2 queue, and the rest to the general queue. Post a summary of the triage to the support channel in Slack with counts by topic and how many are urgent.||

Overnight queue triaged. 23 tickets sorted, 3 flagged urgent.

Overnight Triage — 23 Tickets

Priority	Topic	Count	Routed To
🔴 Urgent	Billing (double charge)	2	Billing queue
🔴 Urgent	Bug (login failing)	1	Tier-2 queue
🟡 High	Account access	5	General queue
🟡 High	How-to (paying)	4	General queue
🟢 Normal	Feature request	6	General queue
🟢 Normal	How-to (free)	5	General queue

Summary: 23 tickets triaged and routed. 3 urgent need eyes now: 2 double-charge complaints and 1 widespread login bug (4 separate reports, may be related). Billing queue is heaviest this morning. Suggest grabbing the login bug first, it's hitting multiple paying customers.

👇 Here's what your team could do with a single message.

1.Triage the overnight queue and route every ticket by topic and priority

2.Find duplicate tickets from the same customer and merge the context

Scan all open tickets in the helpdesk for any customers who have more than one ticket open right now. For each, pull the ticket subjects and check whether they're about the same issue. List the likely duplicates in a Google Sheet with the customer name, ticket IDs, and subjects. For clear duplicates about the exact same problem, leave a private note on the newer ticket linking it to the original so whoever picks it up has the full picture.

3.Spot a spike in tickets about the same issue and flag a possible outage

Look at all tickets from the last 2 hours in the helpdesk. Group them by topic and keyword. If more than 5 tickets mention the same product area, error, or feature in that window, treat it as a possible incident. Post an alert to the support channel in Slack with the issue, the number of affected customers, and example ticket IDs so the team can confirm whether something is broken.

1.Draft a reply for a ticket using your help docs and the customer's history

Open the ticket I'm pointing at in the helpdesk. Read the customer's question and pull their account details and past tickets. Search our help center for the relevant article. Draft a reply that answers their question in our support voice, references the right help doc, and accounts for anything in their history. Leave the draft on the ticket for me to review before sending.

2.Pull order and account details into a ticket so you stop tab-switching

For the ticket I'm working on, find the customer in your CRM and their most recent orders or subscription details. Add a private internal note to the ticket with their plan, signup date, last payment, open invoices, and any recent orders. That way I have everything I need to answer without opening five other tabs.

3.Clear out the easy how-to tickets with ready-to-send draft replies

Find all open tickets tagged 'how-to' in the helpdesk. For each one, match the question to the right help center article and draft a friendly reply in our support voice that answers it and links the doc. Leave each draft on its ticket for a quick review. Post a list to the support channel in Slack of how many drafts are ready so I can review and send them in one pass.

1.Turn a customer bug report into a clean ticket for engineering

Take the ticket I'm pointing at. Pull the customer's description, their browser and device details if available, the steps they took, and any screenshots or error messages. Write up a clear bug report with a summary, steps to reproduce, expected versus actual behavior, and affected customer count if other tickets mention the same thing. Create a task in your project tracker for the engineering team and link it back to the original ticket. Leave a note on the ticket so I remember it's now with engineering.

2.Find every customer waiting on a bug fix and prep their follow-ups

Look up the engineering bug ticket I name in your project tracker. Find all customer support tickets linked to that bug or mentioning the same issue. For each affected customer, draft a follow-up reply letting them know the fix is in progress or shipped, in our support voice. List the customers and their ticket IDs in Slack so I can send the updates once the fix is confirmed.

3.Escalate stalled tickets to a manager before the customer gets angrier

Scan all open tickets in the helpdesk that have been waiting on us for more than 24 hours or have had more than 4 back-and-forth replies without resolution. For each, summarize the issue, what's been tried, and why it's stuck. Post the list to the support leads channel in Slack and add an internal note to each ticket flagging it for manager review.

1.Find unhappy customers from recent low CSAT scores and prep recovery

Pull all CSAT survey responses from the last 7 days in the helpdesk. Find every rating of 3 or below. For each, pull the original ticket, the customer's account details from your CRM, and what went wrong. Draft a personal recovery reply for each one in our support voice. List the unhappy customers in a Google Sheet with the score, the reason, and a link to the ticket, and post the count to the support channel in Slack.

2.Review a teammate's recent replies against your quality checklist

Pull the last 20 tickets resolved by the agent I name from the helpdesk. Check each reply against our quality checklist: correct greeting, clear answer, right help doc linked, friendly tone, proper closing. Score each ticket and flag any that missed the mark. Put the results in a Google Sheet with the ticket ID, score, and what was missing so I can use it in their next coaching session.

3.Spot at-risk customers from angry or repeat tickets before they churn

Scan all tickets from the last 30 days in the helpdesk. Find customers who filed 3 or more tickets, used frustrated language, or gave a low CSAT score. Cross-reference with their plan and account value in your CRM. Build an at-risk list in a Google Sheet with the customer name, account value, ticket count, and the main complaint, and post the highest-value ones to the support channel in Slack.

1.Assemble the weekly support report without opening a single tab

Pull this week's ticket volume, average first response time, average resolution time, and CSAT score from the helpdesk. Compare each number against last week. Pull the top 5 ticket topics by volume. Summarize the wins, the slips, and the biggest recurring issues. Post the weekly report to the support channel in Slack and email a copy to the support lead via Gmail.

2.Surface the recurring issues product needs to hear about

Pull all tickets from the last 30 days in the helpdesk and group them by topic and root cause. Find the issues that come up most often and the ones tied to bugs or feature requests. Build a summary in Google Docs with the top recurring problems, how many customers each one affected, and example ticket IDs. Post the highlights to the product feedback channel in Slack so the patterns don't get lost in the queue.

3.Build the monthly support scorecard for your lead

Pull last month's total tickets, first response time, resolution time, CSAT, and reopened ticket rate from the helpdesk. Compare against the previous month and flag any metric that got worse by more than 10%. Break ticket volume down by topic. Update the monthly metrics tab in Google Sheets and draft a one-page summary in Google Docs with the trends for your lead's review.

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Set It Once. Support Runs Itself.

Morning triage, SLA alerts, CSAT recovery, weekly reports. Running on schedule and on every new ticket, whether you're at your desk or not.

Automate recurring processes in 30 seconds.

Triage every new ticket the moment it lands

When this happens...

App

Your Helpdesk

When

When a new ticket is created

Then do this...

👇 No workflow builder. Set it up in plain English.

Triage every new ticket the moment it lands

When a new ticket is created in your helpdesk

When a new ticket comes into the helpdesk, read it and tag it by topic (billing, bug, how-to, account, feature request). Set priority based on the customer's plan and urgent keywords like 'down,' 'broken,' or 'charged twice.' Route it to the right queue. If it looks urgent and is from a paying customer, post an alert to the support channel in Slack with the ticket ID and summary.

Catch SLA breaches before they happen, not after

Every 2 hours during business hours

Check all open tickets in the helpdesk against their SLA targets. Flag any ticket that is within 1 hour of breaching its first response or resolution deadline. Post the at-risk tickets to the support channel in Slack with the customer name, ticket ID, time left, and who it's assigned to so someone can grab it before it breaches.

Alert the team when tickets about one issue start piling up

Every 30 minutes during business hours

Look at all tickets created in the helpdesk in the last 30 minutes. Group them by topic and keyword. If 5 or more mention the same product area or error, post a possible-incident alert to the support channel in Slack with the issue, affected customer count, and example ticket IDs.

Draft replies for the overnight queue so they're ready at 9 AM

Every weekday at 08:00 AM

Pull every unassigned ticket that came in overnight in the helpdesk. For the straightforward how-to and account questions, match each to the right help center article and draft a reply in our support voice. Leave each draft on its ticket. Post a list to the support channel in Slack of how many drafts are ready to review and send.

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Support Playbooks Anyone on Your Team Can Run

Refund handling, bug escalation, CSAT recovery, agent onboarding. Same process, same care, every single time.

Complete repetitive processes in clicks

Run a full triage and reply-draft pass on the open queue

1. Queue & Scope

Queue & Scope

Fill fields below 👇

Queue or View to Process *

Number of Tickets to Handle *

Support Voice Guidelines Doc Link

2. Triage and Draft Replies

Agent

Pull up to Number of Tickets to Handle open tickets from the Queue or View to Process in the helpdesk. Read each ticket and tag it by topic (billing, bug, how-to, account, feature request) and set priority based on the customer's plan and urgent keywords. For straightforward how-to and account questions, match the question to the right help center article and draft a reply in the support voice described at Support Voice Guidelines Doc Link. Leave each draft on its ticket. Score each ticket by priority and note whether a draft is ready.

3. Log Triaged Tickets in Google Sheets

Add Rows to SheetinGoogle Sheets

4. Post Triage Summary to Slack

Send MessageinSlack

👇 See use cases.

1.Run a full triage and reply-draft pass on the open queue

How this Playbook works?

Enter the queue or view to process and how many tickets to handle. The AI agent pulls the open tickets, reads each one, and tags it by topic and priority based on the customer's plan and urgent keywords. For straightforward questions it matches the right help center article and drafts a reply in your support voice, leaving the draft on each ticket. It logs the triaged tickets in a 'Queue Triage' tab in Google Sheets with the topic, priority, and whether a draft is ready. A summary of how many tickets were sorted and how many drafts are waiting for review gets posted to the support channel in Slack.

2.Handle a refund request from check to resolution

How this Playbook works?

Enter the ticket ID and the refund reason. The AI agent pulls the customer's account and payment history from your CRM and billing tool, checks the request against your refund policy, and confirms the original charge. If the request fits the policy, it drafts an approval reply in your support voice explaining the refund timeline and logs the decision in a 'Refunds' tab in Google Sheets. If it falls outside the policy or exceeds the auto-approve amount, it drafts the reasoning and routes the ticket to a manager in Slack for a decision instead of replying to the customer.

3.Escalate a customer bug to engineering with full context

How this Playbook works?

Enter the ticket ID for the bug report. The AI agent pulls the customer's description, their device and browser details, the steps they took, and any error messages or screenshots. It searches the helpdesk for other tickets describing the same issue to count how many customers are affected. It writes a clean bug report with a summary, reproduction steps, and expected versus actual behavior, creates a linked task in your project tracker for engineering, and leaves an internal note on the original ticket. A heads-up with the affected customer count goes to the engineering channel in Slack.

4.Run a CSAT recovery sweep on this week's unhappy customers

How this Playbook works?

Enter the date range to review. The AI agent pulls all CSAT responses in that window from the helpdesk, finds every rating of 3 or below, and for each one pulls the original ticket and the customer's account value from your CRM. It drafts a personal recovery reply in your support voice for each unhappy customer and logs them in a 'CSAT Recovery' tab in Google Sheets with the score, the reason, and the account value. The highest-value at-risk customers get posted to the support leads channel in Slack so a senior agent can handle them personally.

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Less Queue. More Helping People.

Describe your support task in one sentence. The agent does it across your apps.

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