# AI agents for support and success, nothing sent without you. AI for customer support and success teams works best behind the scenes. In Arclyx, five agents sort the support queue and draft routine replies, group the week's requests by root cause, rate renewals at risk, brief you before customer calls and write the handoff when you name a closed deal. None of them talks to a customer. What lands in Slack, one example from each agent (placeholder companies): - **Support triage · 4 urgent, 0 need a person, 6 routine** (#support): Customer A, Urgent · no draft. Everything failing since last night. An outage. Page the on-call engineer. - **Support digest · Monday to Friday · 22 requests in 9 groups** (#support-digest): Customer A, Reports stop after a schedule is edited · 5. Five requests, from Customers A, G, H, I and J. Tracked by #214: editing a schedule's time clears where its report is sent. - **Renewal risk radar · 9 renewals in the next 90 days** (#renewals): Customer A, Red · renews 20 Nov. $3,200 MRR. 37 to 14 active seats, 2 open high tickets, 73 days since contact. All four signals. Next: Priya to run an exec call this week on both open tickets. - **Customer call brief · Customer B** (your Slack DMs): Customer B, Account. Team plan, 25 seats, $1,250 MRR. Renews 5 December, in 42 days. Owned by Marcus. The renewal is close enough to come up on the call. - **Handoff · Customer N · Business plan** (your Slack DMs): Customer N, Deal. $33,600 a year for 35 seats, closed won 22 October, 12 months from 1 November. A 10% first-year discount, tied to a case study by month six. ## How can support and success teams use AI agents? On the reading and sorting between conversations, never the conversations themselves. Two agents work the support queue, three work the accounts. Each starts from one sentence, reads only the tools it is given and sends one short message to you or your team. - [Support triage](https://arclyx.ai/agents/ticket-triage) (Weekdays, 9:00; reads Tables, Document search; drafts in Gmail; posts to #support): Every weekday, today's requests sorted into urgent, needs a person or routine, with a Gmail draft waiting for each routine request. - [Support digest](https://arclyx.ai/agents/support-ticket-analysis) (Fridays, 16:00; reads Tables, GitHub; posts to #support-digest): Every Friday, the week's requests grouped by root cause, with the customers named and the open GitHub issue for each problem. - [Renewal risk radar](https://arclyx.ai/agents/churn-prediction) (Mondays, 8:00; reads Tables; posts to #renewals): Every Monday, each renewal in the next 90 days rated red, amber or green on four signals, with one next step for its CSM. - [Customer call brief](https://arclyx.ai/agents/customer-meeting-prep) (When you ask; reads Tables, Document search, Google Calendar; posts to your Slack DMs): Before a customer call: the account, open tickets, the usage trend and every promise from the last call, kept or not. - [Success handoff](https://arclyx.ai/agents/customer-success-handoff) (When you ask; reads HubSpot, Document search; posts to your Slack DMs): When you name a closed deal: what they bought and why, every promise checked against the contract, and who's who. ## Where does each agent fit in a customer's year? Each one takes a moment that usually slips: the day the deal closes, the requests that pile up, the problems that repeat, the call you prepare for in a minute, and the renewal you notice too late. They don't hand work to each other; each reads your data at its own moment. 1. **The deal closes**: Ask Success handoff for the deal: it reads the HubSpot deal and the discovery notes, then writes what success needs on day one. 2. **Requests come in**: Support triage sorts every new request each morning and drafts the routine replies for a person to send. 3. **The same problem repeats**: Support digest groups the week's requests by root cause and checks whether engineering tracks each one. 4. **A call is booked**: Customer call brief pulls the account, tickets, usage and last call's promises into one brief. 5. **Renewal comes into view**: Renewal risk radar rates every renewal in the next 90 days and names who acts next. ## Can an AI agent reply to customers for us? Not these five. In Gmail their only writing tool saves drafts, so a person reviews and sends every reply, and nothing urgent or sensitive is drafted at all. Your tables, HubSpot and GitHub are only read. Each agent's one message goes to you or your team, and every run is recorded. They can: - Read the tables and documents you upload - Read HubSpot deals, GitHub issues and your calendar - Save Gmail drafts addressed to a request's sender - Post one message to Slack, or email you They can't: - Send an email or message a customer - Draft for urgent or sensitive requests - Change HubSpot, GitHub issues or your tables - Fill in missing data - Email anyone but you [How Arclyx keeps agents inside their access](https://arclyx.ai/security) ## How do you use AI in customer success? Give each job that slips its own agent, and let it run on a schedule or when you ask. Here is a week of a support and success team on Arclyx: each step is the sentence that built an agent, then what it posted in Slack. Try it runs a new agent once as a dry run first. 1. **Monday, 8:00, Renewal risk radar** ([Renewal risk radar](https://arclyx.ai/agents/churn-prediction)). The sentence that built it: "Every Monday at 8, find every customer renewing in the next 90 days in our customer, usage and ticket tables, rate each red, amber or green on usage drop, open urgent tickets, days since contact and seats in use, and post the list to #renewals with one next step for each account's CSM." It posted to #renewals: Renewal risk radar · 9 renewals in the next 90 days. - Customer A, Red · renews 20 Nov: $3,200 MRR. 37 to 14 active seats, 2 open high tickets, 73 days since contact. All four signals. Next: Priya to run an exec call this week on both open tickets. - Customer B, Red · renews 5 Dec: $1,250 MRR. 22 to 9 active seats, an urgent ticket open, 86 days since contact. All four signals. Next: Marcus to close the urgent ticket this week and right-size 25 seats to about 9. 2. **Tuesday, 9:00, as every weekday, Support triage** ([Support triage](https://arclyx.ai/agents/ticket-triage)). The sentence that built it: "Every weekday at 9, sort today's new support requests into urgent, needs a person or routine using our help notes, save a Gmail draft reply for each routine one a help note answers, never send anything, and post the list to #support." It posted to #support: Support triage · 4 urgent, 0 need a person, 6 routine. - Customer A, Urgent · no draft: Everything failing since last night. An outage. Page the on-call engineer. - Customer B, Urgent · no draft: Possible personal data in an automated message. Possible data exposure. Needs a person today. 3. **Wednesday, 11:30, asked before a call, Customer call brief** ([Customer call brief](https://arclyx.ai/agents/customer-meeting-prep)). The sentence that built it: "When I name a customer, brief me for the call from our customer, usage and ticket tables, the call notes and my calendar: plan, seats, MRR and renewal, open tickets, usage trend, what they asked for and what we promised, the next meeting, and two or three things to raise." It posted to your Slack DMs: Customer call brief · Customer B. - Customer B, Account: Team plan, 25 seats, $1,250 MRR. Renews 5 December, in 42 days. Owned by Marcus. The renewal is close enough to come up on the call. - Customer B, Open tickets: Two open: an urgent integration failure, 16 days old, and a question about paying for 25 seats. The urgent one blocks the reason they bought. Know its fix status first. 4. **Thursday, 15:40, asked as a deal closed, Success handoff** ([Success handoff](https://arclyx.ai/agents/customer-success-handoff)). The sentence that built it: "When I name a closed deal, read it in HubSpot and our discovery notes, and send me the handoff for customer success: what they bought, why they bought, what we promised, who's who on both sides, risks and the first onboarding steps." It posted to your Slack DMs: Handoff · Customer N · Business plan. - Customer N, Deal: $33,600 a year for 35 seats, closed won 22 October, 12 months from 1 November. A 10% first-year discount, tied to a case study by month six. - Customer N, Why they bought: Drafts-only email, so a person approves every message to their customers, and agents their ops staff can build without an engineer. A weekly report in Slack was the third reason. 5. **Friday, 16:00, Support digest** ([Support digest](https://arclyx.ai/agents/support-ticket-analysis)). The sentence that built it: "Every Friday at 4, read this week's support requests, group them by root cause, count each group and name the customers, find the open GitHub issue that tracks each one or say there isn't one, and post the digest to #support-digest, biggest group first." It posted to #support-digest: Support digest · Monday to Friday · 22 requests in 9 groups. - Customer A, Reports stop after a schedule is edited · 5: Five requests, from Customers A, G, H, I and J. Tracked by #214: editing a schedule's time clears where its report is sent. - Customer B, Integration shows connected, but syncs fail · 4: Four requests, from Customers B, A, D and E. Tracked by #187: mark an integration unhealthy when its sign-in fails. **A week of support and success. Nothing sent to a customer.** - Renewals rated, in #renewals - Routine answers drafted in Gmail, waiting for a person - A brief before Wednesday's call, in your Slack DMs - Thursday's deal handed to success - The week's recurring issues, in #support-digest [Create an agent from one sentence](https://arclyx.ai/product) ## AI for customer support and success, answered. ### What are AI agents for customer support and success? Software that takes a recurring support or success job, such as sorting the queue or checking which renewals are at risk, works from your own data and reports to your team. In Arclyx each one reads only the tools it's given and sends one short message. ### Are these a support chatbot? No. A chatbot answers customers. These agents work for your team behind the scenes, and none of them talks to a customer. The closest is Support triage, which drafts answers to routine requests in Gmail for a person to review and send. ### Do they work with Zendesk or Intercom? Through exports, not a connection. Export your requests, tickets and usage as CSV from your help desk, product analytics or billing tool, upload them to Arclyx, and the agents read them as tables. ### Can an AI agent predict churn? Renewal risk radar rates every renewal in the next 90 days on four signals: usage drop, open urgent tickets, days since contact and seats in use. It isn't a trained model, so every rating shows the numbers behind it. ### Do they work with HubSpot and GitHub? Yes, read-only. Success handoff searches and reads HubSpot deals, companies and contacts; Support digest lists, searches and reads open GitHub issues. Neither can change a record or an issue. ## Where to go next - [AI for sales teams](https://arclyx.ai/solutions/sales): Prospects, meeting briefs and tenders worth a bid - [AI agents for business](https://arclyx.ai/agents): Every agent, grouped by team, with the tools each one reads - [Connectors](https://arclyx.ai/product/connectors): HubSpot, GitHub, Gmail and how an agent reaches them - [Security](https://arclyx.ai/security): How an agent stays inside the access you give it Last updated 25 October 2026. ## Build your first support agent. One sentence in, a working agent out. Join the beta and we'll set you up. Join at https://arclyx.ai/#join or write to hello@arclyx.ai.