Fewer repetitive questions
Order status, account and plan questions are answered in the customer’s own channel, day and night, so your team stops answering the same questions all day.
Customer Desk AI Agent
Customer Desk AI Agent answers your customers’ routine questions in seconds and passes everything else to the right person with the work already prepared. Your support team handles more requests with the same people, and you stay in control of every decision that matters.
What it means for your business
-
61%
of routine requests answered without a person
- Before
- Every request waited in a shared queue until someone had time.
- With Customer Desk
- Order, account and plan questions are answered in the same channel, in seconds.
-
4 min
for a request to reach the right team
- Before
- Requests were sorted by hand each morning, often hours later.
- With Customer Desk
- Each request is read, classified and routed the moment it arrives.
-
3×
more bug reports developers can act on first time
- Before
- Developers went back to the customer for steps and screenshots.
- With Customer Desk
- Reports arrive with the steps to repeat them, the account and the likely cause.
What your support team gets back
Every request reaches the right person
Requests are sorted the moment they arrive. Billing, developers, the warehouse or sales each receive only what is theirs, with the details already gathered.
Decisions stay with your people
Refunds, replacements and exceptions follow your rules and limits. Anything above them waits for an employee to approve.
A clear view of your support
Managers see volumes, response times and what the agent handled, team by team, so they can plan staffing and spot problems early.
What it looks like in practice
A support employee asks one question. The agent looks up the order and the customer, prepares a replacement and a refund, and waits for approval. The employee checks it and approves with one click.
Support team memberA customer says order #48213 arrived damaged. What can we do?
Customer DeskOrder #48213 shipped on 3 November and is within the 30-day return window. I opened a replacement request for the warehouse in Jira and prepared an €89 refund in Stripe. It is waiting for your approval.
Looked up
- Order system
- Customer database
- Jira
- Stripe
How six companies use the Customer Desk AI Agent
Each one in short: the problem, the results, and how the agent handles the work.
Support engineers see an account’s full picture in 3 minutes, not 40
To look into one account, a support engineer checked the account's plan and users, asked the data team for a usage query or ran it themselves, searched the error logs, read the latest GitHub releases and looked for known issues in Notion.
- 1Takes the question where the team already works
A support engineer or customer success manager asks about an account in plain words, in a Slack channel or from inside the Intercom conversation.
- 2Joins internal data with outside tools
It reads the account's plan, users and recent activity from the internal database and the matching errors from the product logs, then lines them up with GitHub releases and the known-issues page in Notion.
- 3Prepares a bug report developers can reproduce
It checks Jira for an existing report first.
- 4Drafts the reply, and the engineer sends it
A reply in the company's tone waits in Intercom for the support engineer to check, edit and send.
- 3 minto see an account's full picture
- 9in 10 bug reports reproducible first time
- −60%time spent writing tickets and replies
- Same dayrenewal risks reach customer success
Peak season handled without a single temporary hire
On peak-season Monday mornings, team leads spent the first hour sorting thousands of weekend tickets by hand.
- 1Sorts the inbox before the team starts
The agent reads every new ticket as it arrives, puts it in the right queue, merges duplicates and flags urgent ones.
- 2Summarises each ticket with the facts
At the top of every ticket the team sees what the order system, warehouse stock, Shopify and Stripe say about this customer and order, so nobody has to open four systems.
- 3Drafts the reply for a one-click check
Following the retailer's rules and tone, the agent drafts the reply, reserves a replacement size or adds a return label where that fits.
- 4Sends refunds over the limit to finance
Refunds above €150 go to finance in Microsoft Teams (or Slack) with the order, payment, damage photos and customer history attached.
- 40 sto handle a routine ticket
- 7in 10 replies sent after a one-click check
- 2 hfor finance to approve a large refund
- 0extra seasonal staff
Card dispute files ready in 2 minutes instead of 12
Preparing a single card dispute took a contact-centre employee about 12 minutes: finding the payments, checking the card, locating the customer's signed form and looking up the filing deadline.
- 1Checks who is asking
Every question comes from a signed-in employee, and their role decides what the agent may show.
- 2Looks up the facts across the bank's systems
For Sara's dispute it finds the three payments in core banking, confirms the customer and card in the customer records, attaches the signed form from the document archive and takes the filing deadline from the bank's procedures.
- 3Sends sensitive steps for approval
The temporary credit goes to compliance in Microsoft Teams with the file attached, and nothing happens until someone approves it.
- 4Gives the employee a summary and a draft reply
Sara gets a short summary of what was done and a draft message for the customer.
- 2 minto prepare a dispute file
- −60%files sent back by the back office
- Every sensitive step approved first
- 0customer records leaving the bank
214 outage tickets handled as one incident
During an outage, every support employee worked through the same ticket again and again, writing replies from scratch and asking colleagues in chat whether something bigger was going on.
- 1Spots the pattern in the queue
The agent notices tickets about the same problem from the same area arriving within minutes, and links them into one incident in Zendesk instead of leaving 214 separate tickets.
- 2Checks the network and the accounts
It compares the tickets with network health in Datadog to confirm a real outage, and finds which customer accounts sit in the area, including the business customers.
- 3Alerts network operations once
The network team gets a single Slack alert with the area, start time, the mast that went offline and how many accounts are affected.
- 4Equips frontline staff and account managers
Every linked ticket gets the current status and a draft reply that the employee checks and sends.
- 214 → 1tickets handled as one incident
- 5 minto alert network operations
- −60%frontline time per outage ticket
- Same daybusiness customers contacted
Referral letters ready in 7 minutes instead of 25
A single referral meant copying patient details from the admin records, finding the follow-up slot in the appointment system, retyping the reason from the doctor's note and checking the insurance policy.
- 1Reads the request
A receptionist asks in Teams, or an insurer writes to the shared inbox.
- 2Looks up the facts
It joins the patient admin records, the appointment system and the doctor's note, and checks what the patient's insurer needs before a scan or a specialist visit.
- 3Prepares the paperwork for staff to check
Referral letters, pre-approval requests and replies to insurers arrive as drafts, with every line showing where it came from.
- 4Passes anything clinical to nurses and doctors
A question about symptoms, medication or treatment goes straight to the nurse on duty in Teams, with the record attached.
- 7 minto prepare a referral letter
- Same daypre-approval requests
- −50%emails chasing paperwork
- 100%of clinical questions answered by nurses and doctors
Delivery exceptions ready for dispatchers in 4 minutes, not 20
Dispatchers started each morning by searching for the previous day's exceptions.
- 1Picks up every exception
When a driver scans a failed delivery or reports damage, or a dispatcher asks in Slack, the agent opens a case straight away.
- 2Puts the facts together
It joins the scan history and photos from the tracking system, the driver's notes in Slack, the sender's account and the next free slot in the depot schedule.
- 3Sends the case to the team that owns it
Damaged parcels go to the depot's Slack channel, failed deliveries to dispatch and wrong addresses to the address desk in Zendesk, with a suggested next step for staff to confirm.
- 4Drafts the update and spots patterns
A draft customer update waits in Zendesk for a support agent to check and send.
- 4 minto prepare an exception case
- −35%parcels sent back to the depot
- 1hour from exception to customer update
- −30%repeat failures
Illustrative scenarios with unnamed companies. The figures show the kind of improvement each setup is designed to deliver; actual results depend on volume, the systems connected and how the agent is configured.
From first conversation to live in four to six weeks
We set up the Customer Desk AI Agent around how your support team works today.
-
1
Week 1
Learn your process
We sit with the people who do the work, map the process step by step and find the systems that hold the information. You get a written plan before anything is built.
-
2
Weeks 2 to 3
Customize your agent
We build and configure the agent around your process: your rules, your approvals, your wording, and connections to your databases and the tools your teams use.
-
3
Weeks 3 to 4
Deploy and test with your team
We install it inside your infrastructure, or in our cloud if you prefer, and test it with your team on real requests until the results meet the standard you set.
-
4
From week 5
Onboard your team
We train your employees and administrators, hand over the controls and stay with you: monthly reviews, updates you approve, and the next process when you are ready.
What your team and managers see
Customer Desk AI Agent: questions from business leaders
How quickly will we see results?
Your team tests the agent on real requests within the first weeks. Most companies see the share of routine requests it answers, and the time saved, during the first month after going live.
What does it cost?
It depends on your request volume, the systems it connects to and where it runs. After a first conversation you get a written proposal with the price, so you can compare it with what the work costs you today.
Will it replace our support staff?
It takes over the repetitive part of the work, so the same team can handle more requests and spend its time on the customers who need a person. Decisions, exceptions and sensitive conversations stay with your people.
What if it gives a wrong answer?
It answers only from your own systems and documents, follows the limits you set, and passes anything it is unsure about to a person. Every answer and action is recorded, so you can review and correct it.
Can we control what it says and does?
Yes. You decide which questions it answers alone, which actions it may take and up to what amount, and how it should sound. You can pause it at any time.
Is our customer data safe?
It can run on your own servers, where every conversation and customer record stays inside your company and we have no access to it. Your data is never used to train AI models.
Do we have to change our help desk or tools?
No. It works with Zendesk, Intercom, Salesforce, Microsoft Teams, Slack and the other tools your team already uses.
Which channels can customers use?
Chat, email, messaging apps such as WhatsApp, Messenger and Telegram, and text messages. The agent works in writing only.
What do you need from our team?
One person who knows how support works today, access to test versions of the systems involved, and a few hours a week from the team while we test.
Can we start small?
Yes. Most companies start with one channel or one team, see the results, and then extend the agent to the rest of support.
See what the Customer Desk AI Agent can do for your support team.
Tell us how many requests your team handles, where they come from and what slows it down. You get a written proposal with the expected results, the setup, a timeline and a price.