Customer Support Chatbot Ticket Automation

AI agents that resolve support tickets faster — 24/7

Deploy an AI support agent that handles FAQs, routes complex tickets, and assists your team with instant answers. Reduce response times, cut ticket volume, and keep customers happy — 24/7.

Browse the full agent library

Ready-to-use AI Customer Support Agent agents

Clone and run these agents in one click. Built by the Twin community.

AI employee

DTC Support Triage Operator

Read all unread support inbox messages received since the last successful run, skipping any whose message ID is already in the handled ledger.

For each new message, fetch the matching Shopify customer and most recent order(s) by email lookup so the classifier has order context.

Classify intent into one of the enabled categories with a confidence score; if confidence is below 0.7 or the intent is not in the enabled list, route the thread to human approval.

Apply the auto-action policy: execute the Shopify mutation directly when the intent is auto-approved and within the refund cap; otherwise present the proposed action for approval before executing.

Send a reply from the support inbox using the configured brand voice and signature, BCC the owner, and append the message ID and ticket outcome to the handled ledger.

+1 more step

0 Uses

AI employee

Helpdesk Pulse Analyst

Read connected helpdesk filters and pull yesterday's created, resolved, and currently-open tickets along with tags, priorities, and CSAT scores

Compute week-over-week deltas against the same weekday last week and check backlog against the alert threshold

Cluster ticket subjects and CSAT comments into 3-6 themes with a short narrative for the AI feedback summary

On the configured weekly day, also compute median first response time, median resolution time, and build a tag distribution chart

Render the digest in the chosen format with metrics, backlog flag, themes, priority-tag callouts, and chart if weekly

+2 more steps

1 Use

AI employee

Clinic Front Desk Concierge

Trigger fires when a new patient message webhook arrives or on the scheduled follow-up tick

Agent parses the payload, extracts sender + body, and checks the processed-messages database for duplicates

Twin AI classifies the message into one of seven intents using the clinic's services and tone

If a booking or reschedule intent is detected, Twin checks the calendar for the next available slot inside operating hours

Twin drafts a reply in the configured language, sends it through the inbound channel, and updates the appointments table

+2 more steps

1 Use

AI employee

Multi-Page Messenger Concierge

On each tick, list all connected Facebook Pages and pull recent Messenger threads per Page

Filter to threads where the last message is from the customer and no human or agent reply has been sent since

Cross-check the agent database to skip threads already in human-handoff or human-takeover state

For each remaining thread, classify intent (FAQ, pricing, booking, complaint, off-topic) using the knowledge base

Draft a reply in the configured brand voice, ask one qualifying question if contact info is missing

+3 more steps

3 Uses

AI employee

Storefront Support Operator

Load already-processed message IDs from the agent's local database.

Fetch new messages from the configured inbound channel and filter out anything already in the dedup table.

Classify each remaining message — order status, cancellation request, shipping issue, subscription change, automated/marketing, or escalation.

Look up the referenced order on your commerce platform and capture fulfillment, transaction, and shipping details.

Execute the policy-permitted action: cancel + refund, update address, refund for delivery failure, pause subscription, or no-op.

+2 more steps

2 Uses

AI employee

Local Lead Reply Pilot

On each tick, read last_processed_id from agent_state and fetch only newer messages from the inbound channel

Insert message IDs into processed_messages with INSERT OR IGNORE; skip any rows already present and early-exit if all are duplicates

Classify each new message into a typed intent label and pull the existing conversation_state row if a contact_id already exists

Branch into Flow A (new lead intake), Flow B (continue existing conversation), Flow C (booking confirmation), or Flow D (escalate)

Generate the reply with Twin AI using the brand voice setting, the contact history, and a short intake script for first-touch leads

+3 more steps

111 Uses

How customer support automation works

Go from zero to a working customer support agent in minutes.

Step 1

Clone a support automation agent

Choose an agent for ticket triage, auto-replies, or FAQ handling and clone it to your workspace.

Step 2

Share your knowledge base and tone

The agent learns your product docs, FAQs, and brand voice to answer customers accurately.

Step 3

Connect your help desk, email, and chat

Link Zendesk, Gmail, Slack, Telegram, or your help desk — the agent works where your customers are.

Step 4

Tickets get resolved around the clock

The agent answers common questions instantly and escalates complex issues to the right team member.

Run AI Customer Support Agent on Twin

Create, run, and monitor your agents from a single interface.

B2B Intent Intelligence

Workspaces

Send Twin live feedback to adjust the run...

Scrapers

Extract data from any website

Slide deck

Generate presentations instantly

Image & video

Create visual content with AI

Web search

Find information in real-time

Deep research

In-depth analysis on any topic

Any app

Connect to your favorite tools

Browser

Automate web interactions

Sharing

Share with colleagues or friends

Webhooks

Automate execution triggers

Workflow guide

Build a customer support automation workflow around real outputs.

The strongest ai customer support agent setup starts with a clear input, a repeatable decision rule, and a destination for the finished work. Twin agents can collect the data, use connected tools, and deliver a reviewable result instead of leaving the workflow as a loose prompt.

Help Desk

Monitor incoming support tickets from email, chat, and your help desk

Knowledge Base

Search your docs and past tickets to find the best answer

AI Response

Draft and send accurate, on-brand replies for common questions

Routing

Escalate complex or VIP tickets to the right team member automatically

customer support teams automate with Twin.

"Twin handles 60% of our support volume automatically. Our team focuses on the hard problems now and customers get instant answers for everything else."

Laura C.

Head of Support, SaaS Company

"Our response time went from 4 hours to under 30 seconds for common questions. CSAT scores are at an all-time high."

Kevin B.

Customer Success Manager

"We were drowning in tickets before Twin. Now the AI handles Tier 1 perfectly and our agents can finally breathe."

Sophie G.

Support Team Lead

FAQ

Common questions about ai customer support agent.

What is AI Customer Support Agent?

Deploy an AI support agent that handles FAQs, routes complex tickets, and assists your team with instant answers. Reduce response times, cut ticket volume, and keep customers happy — 24/7.

How does Twin automate customer support workflows?

Clone a support automation agent: Choose an agent for ticket triage, auto-replies, or FAQ handling and clone it to your workspace. Share your knowledge base and tone: The agent learns your product docs, FAQs, and brand voice to answer customers accurately. Connect your help desk, email, and chat: Link Zendesk, Gmail, Slack, Telegram, or your help desk — the agent works where your customers are. Tickets get resolved around the clock: The agent answers common questions instantly and escalates complex issues to the right team member.

Do I need to write code to use these agents?

No. Twin lets you clone, configure, and run AI agents using natural language and connected apps.

Ready to automate customer support?

Set up this agent in minutes. No code required. Start automating your customer support workflows today.

Browse the full agent library