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AI support desk for e-commerce brands and online sellers

Half of an online store’s tickets boil down to three questions: where is my order, how do I return it, when do I get refunded. The agent answers them alone by reading your OMS and carrier tracking, and leaves your team the disputes that deserve a human.

In your day-to-day

A typical scenario

A store shipping 300 orders a day with two people on customer service, and ticket volume tripling between Black Friday and Christmas. The evening queue waits until morning; the weekend queue waits until Monday.

  1. 01

    At 9 AM the overnight queue is already handled: WISMO requests got the carrier’s current status, return requests got their label, and seven genuine cases sit in the human queue.

  2. 02

    A parcel marked delivered but never received: the agent checks the delivery scan, applies your policy — immediate gesture or investigation — and writes to the customer in their language, English or Spanish included.

  3. 03

    Through the December peak, capacity does not move: the 900 tickets of a holiday week get the same first response in minutes as the 300 of a quiet one.

What changes

The support team stops being crushed by volume: it handles the disputes that need judgement, while the repetitive resolves itself — nights included.

Order of magnitude

Working assumptions

  • around 900 tickets per month outside peak season
  • 60% concern three recurring reasons: order tracking, returns, refunds
  • 6 minutes average handling time per ticket

Roughly 540 tickets absorbed per month, in the order of 54 hours of support work handed back to the team — more still over the holidays.

Indicative estimate built on average sector assumptions — it gets recalibrated on your actual volumes during scoping.

What eats your days

How it works

  1. 1

    The agent learns your business

    It is fed your real sources: FAQ, documentation, ticket history, business rules. It only answers what it can source — no improvising.

  2. 2

    Autonomous resolution, fenced

    Recurring requests — tracking, invoices, procedures — are resolved end to end. Anything outside the fence goes to the human queue with a sourced draft reply already written.

  3. 3

    Supervision and continuous improvement

    Every conversation is reviewed by our engineers in the first weeks. The autonomous-resolution rate rises as the agent earns reliability — never the other way round.

Typical results

60%

of tickets resolved with no human involved, observed in production

3 min

first response, 24/7

×3

handling capacity for the same team

Orders of magnitude observed in production; your diagnostic sets your own baseline and targets.

Frequently asked questions

Can the agent trigger a refund on its own?+

Only within the fence you approve — for example a refund under a threshold amount once the return is received and conforming. Beyond that, it prepares the file and a human clicks.

Does it hold up during the Black Friday peak?+

That is when it pays off most: its capacity does not depend on a staffing plan. Ticket volume can triple over the holidays; first-response time stays in minutes.

Is this the problem eating your team’s time?

Tell us how you work today — 30-minute call, then a free written diagnostic of what this agent would change for you, with numbers.

Get my free diagnostic

Free resource

Get the self-assessment grid for your sector

Sales, admin, support, operations: the 20 tasks AI agents already handle in SMEs — with, for each one, the tell-tale sign that your team is concerned.