AI reception and telephony

Answers the phone when no one can. Takes notes, schedules, qualifies and passes the case along with the full context.

• 6 hours – 2 daysLaunch
• individuallyScope
• AI and automationArea

Problem

The phone rings during work, so nobody answers it. A missed call in a local company is most often a client who at that same minute calls the competition — and they answer. Nobody knows how many such calls there were yesterday, because missed calls leave no trace in any report. After hours nobody answers either, and that's exactly when people have time to call.

What we do

We build a phone layer where AI answers: knows your services, prices and schedule, and can close the deal.

• Answers incoming calls, including at night and on weekends
• Qualifies the inquiry, schedules a visit and records everything in CRM
• Transfers more complex conversations to a human along with a summary and recording

What's included

The setup is one-time and unavoidable. The depth is matched to the number of calls and to how much of the conversation has to stay in the system — not to the size of the company.

• Configuration: knowledge base, conversation scripts, FAQ, qualification, booking logic, CRM connection, tests
• Shallowest: inbound calls, FAQ, simple transfers, call summaries
• Deeper: round-the-clock answering, qualification, bookings, transfers, CRM, call-backs
• Deepest: many scenarios, many numbers, advanced integrations, analytics, priority support
• Corporate telephony: numbers, redirects, recording, queues, working hours, analytics
• Call analytics: recordings, transcription, summaries, tags, AI assessment, reports

How long it takes

Launch takes 6 hours – 2 days — both in the version answering typical questions and with booking and CRM connection. For the first two weeks we then work in supervision mode — you listen to recordings and correct answers with one sentence before AI starts working fully independently.

How much it costs

The setup — knowledge base, scenarios, the link into your CRM — is a closed job, and its cost depends on how much of your offer has to be written down before the AI starts talking about it. After that what counts is the number of calls, numbers and languages, not the size of the company.

Answering and call analytics last as long as the phone does, so they go together with the rest of the system — and that is where they make sense: a call ends as a CRM record, and from there qualification and call-backs take over.

What you get

No call is lost, also after hours and at peak times. Each conversation has a summary and tag, so for the first time you can see what people really ask about and how many of those questions end in a visit. The team stops interrupting work with every ring.

How to work out the cost of one missed call

A missed call is not a neutral event — it is an enquiry that can go to a competitor in the same minute. The cost can be worked out from your own data, without guessing:

• Cost of a week of missed calls = number of missed calls that week × the share of enquiries that turn into a visit (worked out from calls that were answered) × the average value of one visit

Take the share of enquiries that turn into a visit from your own CRM, counted on answered calls — it is the one number in the formula that cannot be guessed, and the one you genuinely need to know for the formula to mean anything.

How AI reception differs from voicemail and a plain IVR

Three phone solutions look like they solve the same problem, but in practice they handle a call very differently when nobody physically picks up:

• Voicemail — records a message and waits for someone to listen to it; the callback time depends purely on when someone finds a spare moment
• A keypad IVR menu — routes the call by the digits pressed, but does not understand speech and cannot answer anything outside the menu
• An outsourced call centre — a real person answers, but usually does not know your current prices and schedule, so it passes the enquiry on anyway
• AI reception — understands free speech, knows your services and schedule, and can close a simple enquiry itself instead of only logging it

The difference is not cosmetic: the first two solutions log the enquiry, the third passes it on, and only the fourth can close it there and then.

When AI reception does not pay off

There are situations where this layer will give you nothing, and it is more honest to say so up front than to roll it out and be disappointed a month later.

• The phone rings a few times a day rather than a dozen — the cost of this layer can exceed the value of the calls it saves
• Most calls are individual negotiations, or legal and medical matters that need a human judgement call rather than an answer from a fixed knowledge base
• You have no written-down price list or service scope — without one, the knowledge base would have to be built from scratch alongside the offer itself, which is different work from rolling out telephony
• Nobody at the business has time in the first two weeks to listen to recordings and correct wrong answers — without that supervision the AI keeps repeating the same mistakes for longer

What you need to prepare before launch

The one-off setup mentioned in the service scope comes down to these four specific things on your side:

• A phone number to forward or port over, and consent to record calls, if the law requires it
• Your current prices, service scope and answers to common questions — the raw material for the knowledge base the AI answers from
• Access to a calendar or CRM, if the AI is meant to book visits rather than just log an enquiry
• One person ready to spend the first two weeks listening to a sample of recordings and fixing answers in a single sentence

How to check after a month whether telephony paid off

It is worth fixing the measures before launch, so that after a month you judge numbers from your own systems, not an impression:

• The share of calls answered at peak hours and after closing time — from the phone records, before and after
• The number of calls that ended in a booked visit with no human involved
• The time from a difficult enquiry coming in to it being handed to a person, together with a summary
• The spread of call tags — shows what people ask about most, including things not yet in your offer

Where AI reception uses a language model, and where it uses plain logic

The distinction matters in practice, not just in naming.

• A language model understands the caller's free speech, recognises the intent and drafts the reply — the only part that can honestly be called artificial intelligence
• Scoring an enquiry and deciding when to hand the call to a person are rules and thresholds agreed with you beforehand — plain conditional logic, not artificial intelligence
• Logging the call in the CRM, tagging it and summarising it are automation and a template, not reasoning

Calling the second and third points «artificial intelligence» sounds more impressive, but it is not true — and it is precisely those two points that weigh most in what telephony really costs in work.

What AI reception does not do

It answers and qualifies calls, but it does not replace decisions nobody should hand to an automated system. It does not negotiate price outside ranges agreed beforehand, does not judge legal or medical matters, and does not own a complaint — such calls always go to a person, together with the recording and a summary. Nor does it call people with a sales pitch on its own — that is a different module's job, not reception's.

The most common mistake when rolling out AI reception

The costliest mistake is not bad voice or script configuration — it is an outdated knowledge base: prices change and nobody tells the phone system, so the AI quotes the old price for weeks until someone catches it in a live call. A second, less often mentioned mistake is switching off the handover to a human 'to save money' — then a difficult call that should have reached a real person ends with no answer at all, which is exactly the problem the service was meant to relieve the phone of.

When the problem lies elsewhere

If your problem sounds different, neighbouring areas of the same system stand right next to it — AURA connects them to each other rather than selling them separately:

• AI Chatbot — Site assistant that answers questions after hours, collects data and schedules contact. From the first sentence it says it's AI.
• Request automation — Form goes to CRM, notification to the right person, and task to the calendar. No manual retyping.
• AI lead qualification — AI evaluates and tags inquiries by potential before anyone starts calling back. The team starts with the best inquiries, not the newest.
• AI follow-up — Message sequences for those who didn't respond. Second and third reminder go out on their own, at set time and with stop condition.