Industry solution
24/7 call handling for customer support
A contact center's peak in inquiries almost never lines up with the shift schedule: the surge comes in the evening after the workday, at lunch when half the agents are on break, and on holidays when the line runs on a skeleton crew. In those windows the answer-time SLA collapses, the abandonment rate climbs, and a customer who can't get through on the first try calls two more times — inflating the load themselves. An AI receptionist takes the first line at any hour: it answers with no queue, runs the conversation in the customer's language, and by request type either resolves the question itself or captures context and escalates.
For support this changes the very economics of night and peak handling. Keeping a standby shift for rare spikes is expensive and still doesn't scale, customers abandon voicemail and IVR trees, and a supervisor's morning turns into sorting through incoherent recordings. The receptionist instead logs every inquiry as a structured card with a category, urgency and captured fields — and the first line stops depending on how many people are physically on the line at 3 a.m.
Which industry pains this solves
Queue and dropped calls
At peak and overnight customers can't get through: the call piles up in the queue, drops off and becomes a missed contact no one ever learns about.
Quality by gut feel
You only get to review 2–3% of conversations. Whether the script held, whether the agent was polite, whether it was solved on first contact — stays out of view.
How it works
A step-by-step scenario — the same steps as in the full use case, applied to your industry.
- 1
Set up the intake scenario
Define the secretary's goal, persona and greeting, plus the request fields — exactly what to collect (name, question, urgency) with required flags and validation.
- 2
The secretary answers around the clock
The agent takes inbound calls at any hour: it runs the dialogue in the customer's language, responds to the scenario and lets itself be interrupted (barge-in) — this is no "button tree."
- 3
The request is collected into fields
Instead of rambling voicemail the agent structures the conversation: it fills the configurable request fields, and the transcript is saved alongside them.
- 4
Urgent — instant escalation
By the scenario and automation rules, urgent requests are escalated immediately: a conditional transfer, plus a notify (email) or a webhook to the on-call person.
- 5
In the morning — a structured list
The team opens a list of requests with fields and topics, not an answering machine: you can see what happened overnight, what's urgent and what can wait its turn.
Industry scenario
A service outage at 11:40 pm: a wave of calls into the first line
A customer's key feature goes down around midnight, and they call support — where a single agent is covering the whole night line. Several other people call about the same issue at once, and the queue instantly fills. The AI receptionist answers each caller immediately, with no wait: it asks for the product, plan and symptom, checks against the knowledge base and the standard scenario for this issue. Some callers get a ready workaround and the incident status right in the call and hang up satisfied — they never even reach a live agent.
Inquiries the scenario can't resolve itself, the receptionist tags with the "incident/outage" category, sets urgency and packs the summary, reproduction steps and customer contact into the ticket fields. By an automation rule, critical cases don't wait until morning: the on-call engineer gets a notify email and a webhook into the on-call system with the context already collected, not a note that "someone called at night." The single night agent is offloaded in the process — they take only the calls where a human is genuinely needed.
In the morning the supervisor opens not a voicemail box but a list of overnight inquiries grouped by category: how many calls the outage generated in total, how many the receptionist resolved itself with a workaround, what was escalated and in what status. The spike on one issue is visible at once, and every overnight call recording flows into the shared analysis loop — the topics and metrics of those calls later refine both the intake scenario and the knowledge-base article.
Key facts
- What it does
- Answers inbound calls 24/7 — at night, at peak and on holidays — runs the dialogue and collects the request into fields.
- Capturing the request
- Configurable fields with required flags and validation; the transcript is saved alongside the fields — instead of rambling voicemail.
- Urgent
- Rule-based escalation: a conditional transfer plus automation actions — a notify (email) or a webhook to the on-call person.
- In the morning
- A structured list of requests with fields and topics, not answering-machine messages.
- Closes the flywheel
- Recordings of night calls flow into the shared analysis loop — metrics and topics improve the intake scenario.
Related scenarios for this industry
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