For customer support
AI for customer support: first-pass replies grounded in your own docs.
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Meet this teammate The short answer
What can AI do for customer support without going off-script in front of customers?
AI for customer support drafts first-pass replies to the routine, repetitive tickets — grounded in your own help docs and policies — so your team answers same-day and spends its time on the cases that genuinely need a person. The safe way to do it is a teammate that answers only from your documentation and drafts rather than sends, so a human stays the final check on what reaches a customer.
That's the model Kuvai uses. Forward inbound questions to your support teammate, which reads them against the product docs, help articles, and policies it's grounded in — drafting a reply that's accurate to your actual terms rather than a generic chatbot guess. The teammate cites the source it answered from, routes the novel cases to a human, and drafts for your approval. Because it's grounded in your knowledge, the answers reflect how your business actually works.
Draft the routine reply from your docs, cite the source, route the hard cases to a human — and you decide what gets sent. That's the whole job.
Why support never feels caught up
The same questions, every day
Most inboxes are 80% variations on a handful of recurring requests. Answering them from scratch is a tax on your team's time.
Inconsistent answers across the team
Different agents answer the same question differently, because the right answer is buried in docs nobody has time to check.
Response times that slip under volume
When tickets spike, same-day replies become next-week replies, and the routine work crowds out the cases that actually need expertise.
Help docs that drift out of date
The macros and articles fall behind the product, so even a careful agent can send an answer that's no longer true.
How the work gets done. Step by step.
The morning queue, pre-drafted
- 1Add a teammate with the job title“Customer Support Representative”and give it your help articles, policies and macros.
- 2Connect Zendesk, Intercom or Freshdesk and approve it for this teammate.
- 3In chat, ask:“Every weekday at 7, draft replies for new tickets you can answer from our docs, and list the ones that need a person.”
- 4Drafts arrive with the steps behind them, including which article it used. You review each one and send it.
Hard cases routed to a person, with context
- 1Tell the teammate what counts as a hard case: refunds above a limit, legal threats, angry repeat contacts.
- 2Write those rules into its Guardrails so they apply on every run.
- 3When a ticket matches, it doesn't draft a reply. It writes a short summary of the history for whoever picks it up.
- 4Your Escalation Manager teammate can keep a living document of open escalations, one row per case.
Help content that stays honest
- 1Give your Knowledge Base Manager teammate Confluence, Notion or Google Docs, wherever your articles live.
- 2Ask it to compare each week's tickets with your articles and list questions with no good answer.
- 3It drafts the new or corrected article in your format.
- 4It's set up as a draft, so you review it and publish.
Teammates to start with. Add them one at a time.
Customer Support Representative
Resolves customer issues quickly and accurately while improving satisfaction across every support channel.
Customer Support →
Knowledge Base Manager
Keeps support documentation accurate, discoverable, and self-serve so customers find answers without filing tickets.
Customer Support →
Escalation Manager
Coordinates critical customer escalations end to end, keeping stakeholders aligned until resolution is confirmed.
Customer Support →
Customer Experience Analyst
Analyzes customer feedback across channels and turns it into prioritized experience improvements.
Customer Support →
How a teammate runs a job. Set up once, runs on schedule.
How it worksWhat your support teammate does
You ground it in your help docs the way you'd train a new support hire. From then on it owns the first pass — and queues everything for your review.
It drafts; you decide. Set it up as drafts and replies to customers wait for you to review.
Drafts first-pass replies
Reads each forwarded ticket against your documented policies and articles and drafts an accurate reply in your voice — ready for you to send.
Answers from your sources
Responds only from the documentation you ground it in, so answers reflect your actual terms — not a generic guess from the open internet.
Cites where the answer came from
Shows the source passage behind each reply, so you can trust it at a glance before it goes out.
Routes the hard cases to a human
Recognises the genuinely novel tickets and routes them to an expert rather than guessing — so the hard 20% gets real attention.
Flags stale help content
Surfaces the docs and macros that no longer match reality, so the knowledge your replies draw on stays current.
Shows its work
Every reply shows the steps it took and the source it answered from, so you can see why.
Your AI team for support
Each teammate is grounded in your business and drafts for your review. Build any from a ready-made role, or describe your own.
Every teammate drafts; you decide what's sent, posted, or filed.
Mia — Personal Assistant
- Reads forwarded emails and document packages against your checklists
- Drafts the reply for your review
Dakota — Knowledge Manager
- Keeps your SOPs and documents current
- Answers questions from your own sources, with citations
Sam — Customer Success
- Watches account health and flags renewals and churn risk
- Drafts the outreach for you to send
How you set it up
Ground it in your help docs
Upload or connect your product docs, help articles, and policies. The teammate answers from your sources — not generic knowledge — so replies are accurate to your terms.
Forward inbound tickets
Forward support emails and questions to your teammate. There's no mailbox login — it only sees what you forward, and only from senders you allow.
Set its scope
Decide which question types it drafts for and when to route to a human. The novel cases go to your experts, not to a guess.
Review and approve
You get drafts to check and send. Once you trust it on a routine question type, it can send those automatically — but never beyond the scope you set.
What it looks like in your week
Every workflow ends the same way: a draft for you to review before a customer sees it.
The morning ticket queue, pre-drafted
The routine tickets that came in overnight are already drafted from your documentation, each with its source cited, and the genuinely novel ones are flagged for a human.
Consistent answers across the team
Every reply is drafted from the same current documentation, so customers get the same accurate answer no matter who's on shift — and you approve before it sends.
Help content that stays honest
As it answers, the teammate flags the docs and macros that no longer match the product, so the knowledge behind your replies doesn't quietly go stale.
What it works from
Your support teammate works mostly from the documents you ground it in — help articles, product docs, and policies — and the tickets you forward it. It needs no mailbox access: it reads what you forward, from senders you allow.
We're honest about what's live: it answers from your documentation and the document tools in Kuvai's catalog, and every connection is made through your explicit approval.
Forwarded tickets & email
Forward inbound questions, attachments and all — no inbox login, no OAuth into your whole mailbox.
Your help docs & policies
Upload your articles, product docs and policies, vectorised so replies are grounded in your actual terms.
Notion & Google Docs
Draw answers from the knowledge bases your team already maintains, with your approval.
Slack & Microsoft Teams
Route the cases that need a human to where your team already works.
You decide what is sent
Built so AI stays on-script with a customer
Letting AI near your customers only works if it can't embarrass you. These are the guardrails the teammate runs inside — by design, not by policy.
The teammate drafts the reply and queues it for you. Sending on its own is something you opt into, for the question types you choose.
It answers only from your sources
Replies come from the documentation you ground it in, with the source cited. If the answer isn't documented, it routes to a human rather than inventing one.
Every reply shows the steps it took
Every reply shows its source, so you can see what was answered, from which doc, and why.
First-pass support replies are the job. The genuinely novel cases are routed to an expert, not guessed at.
Questions, answered
What can AI do for a customer support team?
It can draft first-pass replies from your own help docs, sort the queue into what it can answer and what needs a person, summarize long ticket histories, and spot gaps in your help center. On Kuvai this work runs on a schedule you set, and when the job is set up as drafts, replies come to you to review and send.
Can AI answer customer questions accurately, or will it make things up?
A Kuvai teammate is grounded in the help docs and policies you give it, and it's instructed to cite its sources and say it isn't sure rather than guess. Every reply shows its steps, so an agent can see what it read. Treat each answer as a draft for review.
Will AI replace customer support agents?
No. It takes the repetitive first draft and the lookup work, so agents spend their time on the conversations that need judgment and care.
Is it safe to let AI reply to customers?
You decide how far it goes. Set the job up as drafts and a person reviews and sends every reply, and work it starts on its own never makes destructive or out-of-lane changes without checking with you first. You can also set Guardrails per teammate and pause its work at any time.
Can AI handle support tickets automatically?
It can handle the preparation automatically: reading new tickets, drafting replies, summarizing history and flagging what needs a person. Set it up as drafts and the reply itself stays with you.
How is this different from a support chatbot?
A chatbot talks to your customers. A Kuvai teammate works behind your team: it drafts for your agents and keeps your help content current. Set up as drafts, every message to a customer goes out through a person.
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Name the job. Kuvai builds the teammate around your business, and you decide how far it goes.