Call centre automation ยท AI voice

Automate the calls that never needed an agent. Keep the ones that do.

Most call centre automation projects fail by trying to automate everything. Callsy takes the repetitive, high-volume calls off the queue entirely and routes the rest to your agents with context attached, so handle times fall on both sides.

0 secqueue time on automated calls
Uitgevoerd doorAda ยท Front-line agent
Kanalen:TelefoonSMSEmailWhatsApp

Vertrouwd door 261+ merken in e-commerce, zorg en SaaS

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Voor wie het is

  • Contact centres where a large share of volume is a handful of repeat intents
  • Operations leads under pressure on cost per contact and average handle time
  • Teams whose IVR menu tree is deflecting callers into abandonment rather than resolution
  • Businesses with sharp seasonal peaks that are expensive to staff for

Hoe het werkt

  1. 1

    Front-line answer replaces the menu

    Instead of pressing 1 through 5, the caller says what they want. The agent understands the intent and either handles it or routes it correctly the first time, which removes the misroutes that a menu tree generates.

  2. 2

    High-volume intents resolve without a queue

    Balance checks, order status, opening hours, appointment changes, payment reminders, address updates. These typically dominate volume and rarely need judgement, so they never reach an agent at all.

  3. 3

    Everything else lands pre-triaged

    Complex or sensitive calls transfer to a human with the caller identified, the intent captured, and the routine checks already done. Agent handle time drops because the first ninety seconds of every call have already happened.

Waarom het werkt

  • Volume is concentrated, not evenly spread. A small number of intents usually make up the majority of calls, which makes partial automation far more valuable than it sounds.
  • Menu trees deflect into abandonment. Callers who cannot find their option hang up or press zero, so the IVR generates misroutes rather than resolutions.
  • Peaks stop being a staffing problem. Capacity is elastic, so a seasonal spike does not require hiring and training against a forecast that may be wrong.
  • Handle time falls on escalated calls too, because agents skip identification and basic diagnosis.
  • Automating badly is worse than not automating. Routing to a human early, with context, beats trapping someone in a loop that cannot help them.

Hoe het gesprek klinkt

Live transcript

Hoe het gesprek echt verloopt.

Opname komt binnenkort

Het transcript hieronder is echt. Het audiovoorbeeld volgt binnenkort.

Ada
Thanks for calling. You're speaking to an AI assistant. Tell me what you need and I'll either sort it or put you through to the right person.
Klant
I need to move an appointment I've got booked for Thursday.
Ada
I can do that. Can I take the phone number the booking was made under?
Klant
It's the one I'm calling from.
Ada
Found it, Thursday at 11:15 with the Fairfield branch. What day suits you better?
Klant
Some time next week, ideally the morning.
Ada
I've got Tuesday at 9:30 or Wednesday at 10:45. Either work?
Klant
Tuesday's good.
Ada
Booked for Tuesday at 9:30, and I've cancelled the Thursday slot. Confirmation is on its way by text. Anything else?

Wat het oplevert

No queue
on the intents that get automated
Elastic
capacity through seasonal peaks
Pre-triaged
handovers cut agent handle time

Veelgestelde vragen

What actually automates well in a call centre?

High-volume, low-judgement intents with a clear data source behind them: order and delivery status, balances, opening hours, appointment booking and rescheduling, address changes, payment reminders. What does not automate well is anything requiring negotiation, discretion, or emotional judgement, and trying to force those through automation is how these projects earn their bad reputation.

How is this different from our existing IVR?

An IVR makes the caller translate their problem into your menu structure. If they guess wrong they get misrouted or they press zero. Callsy lets the caller say what they want in their own words, then either resolves it or routes it correctly first time. It replaces the menu rather than adding another layer to it.

Will this replace our agents?

It replaces a category of call, not the team. The realistic outcome is that agents stop spending their day on order status and appointment changes and spend it on the calls that need a person, with shorter handle times because the identification and diagnosis are already done. Most operations use the freed capacity rather than cutting it.

How does it handle peak periods?

Capacity is elastic, so there is no queue on automated intents regardless of concurrent volume. This matters most for businesses with sharp seasonal peaks, where staffing to the peak is expensive and staffing below it means abandoned calls.

Can it integrate with our CRM and telephony?

Yes. It connects to your systems for live data and can sit in front of, or alongside, your existing telephony rather than replacing it. You choose which call flows route to it, so you can start with one intent and expand.

What is a realistic starting point?

Pick your single highest-volume intent, automate that one, and measure containment and customer satisfaction before widening scope. Teams that try to automate the whole queue on day one generally end up rolling it back. Sequencing by volume gets you most of the benefit with a fraction of the risk.

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Neurogena
$40K+
additional revenue
Geverifieerde klant
Shopify App Store review, verified merchant
โ€œHighly recommend! Easy to use, well-priced, and with great potential to grow. We now made over 40k in additional revenue using Callsy!โ€
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Shopify Merchant
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34x
ROI on Callsy spend
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Shopify App Store review, verified merchant
โ€œGreat app for recovering abandoned cart purchases. Been using it for the last 3 months, we get around 34x ROI. Team is very responsive and constantly developing new features!โ€
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Arunas Vismantas (CEO) and Laimonas Sutkus (CTO), founders of Callsy
De oprichters

Gebouwd door oprichters, niet door een commissie.

Wij zijn Arunas en Laimonas. We begonnen Callsy omdat elke D2C-oprichter met wie we spraken omzet verloor bij de checkout, en email-recovery was vastgelopen. Stem was het voor de hand liggende antwoord. AI maakte de unit economics eindelijk rond. Zit je in dezelfde situatie, laten we praten.

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