AI Receptionist & Voice Agents
A voice agent that answers every call, books meetings, qualifies leads, and hands the hard ones to a human. Built on your call flows and your knowledge, tested against real conversations, and handed over with documentation.
An AI receptionist is a voice agent that answers your business phone line, holds a real conversation, books appointments, qualifies leads, and transfers to a person when the call needs one. Oleg Sotnikov builds an AI receptionist for small business and mid-sized companies as a fixed-price package: $10,000 covering call flow design, integrations with your calendar and CRM, testing on real scenarios, launch, and handover. The agents run on production-grade LLM infrastructure — the same kind he operates at AppMaster, which processes 11B+ tokens a month.
What the Agent Does
Six things a voice agent has to get right before it belongs on your phone line.
Answers every call, 24/7
Callers never reach voicemail or hold music, and the one who rings at seven on a Friday evening gets a conversation instead of a missed call. The agent picks up on the first ring at any hour and handles as many simultaneous calls as come in.
Books into your calendar
The agent checks real availability, offers slots, confirms, and writes the appointment to your calendar and CRM. The caller hangs up with a time, not a promise that someone will get back to them.
Qualifies and routes
Callers get the questions your team would ask: what they need, budget range, timeline, location. Qualified leads reach the right person with the transcript attached, and the rest get an answer without taking anyone's time.
Speaks in your voice, from your knowledge
The agent is grounded in your documents, price lists, and FAQs, so it answers about your business instead of improvising. Greeting, tone, and the topics it refuses are yours to set. This is not a generic chatbot with your logo on it.
Multilingual conversations
One number, several languages, and the agent switches to whatever the caller speaks without being asked. I tune English and Russian myself, and for anything else a native speaker checks the scripts before launch.
Human handoff rules you define
Anything sensitive, angry, or high-stakes goes to a person by a rule you set: warm transfer, callback request, or a message with the full transcript. The agent does not talk its way through a call it should not be handling.
How It Works
Discovery
We map what actually happens on your calls: the common requests, the edge cases, the questions that need a human, and the systems the agent has to reach — calendar, CRM, telephony. You approve a call flow spec before anything gets built.
Build and test
I build against that spec, wire the integrations, and run the agent through real scenarios including the awkward ones: bad audio, interruptions, a caller who changes their mind mid-sentence. Escalation rules and guardrails get tested as hard as the happy path.
Launch and tune
The agent goes live on a real number with monitoring on every call. The first weeks are iteration: I read the transcripts, adjust the prompts and the flows, and close the gaps they expose. You end up with the documentation, the accounts, and a system your team can run without me.
Why Me
- AppMaster processes 11B+ tokens a month, so LLM systems in production are daily work here rather than a demo
- I hold my own platform to 99.99% uptime, and the same discipline goes into a system that answers your phone
- Users in 190+ countries: multilingual is how I build by default, and I work in English and Russian personally
Where This Fits
Voice is one piece of the AI work. These are the neighbouring ones.
Frequently Asked Questions
How much does an AI receptionist cost?
Here it is a $10,000 fixed implementation: discovery, build, integrations, testing, launch, and handover with documentation. Running costs are separate and stay on your own accounts — the LLM API, the telephony provider, and the voice platform, all billed by usage. We size that monthly range during discovery, so you know the number before you commit.
Will it replace my receptionist?
No, and I would not sell it that way. It removes the after-hours gap, the calls that arrive while everyone is busy, and the routine booking that eats an afternoon. Judgment calls stay with people: an upset customer, an unusual request, anything that needs someone who knows the history.
What happens when the AI can't handle a call?
It follows the handoff rules we agree during discovery: transfer the caller to a person, take a callback request with a promised window, or record a message with the full transcript attached. Every branch we build ends somewhere a human sees it, so a caller never lands in a loop or a dead end.
Which languages does it support?
The underlying models handle most widely spoken languages, and the agent switches to the caller's language on the same phone number. English and Russian I build and tune myself. Other languages run through the same process, with a native speaker reviewing the scripts and the test calls before launch.
How is this different from an answering service?
An answering service takes a message and passes it on, so someone on your side still has to call back. A voice agent has the conversation and then does the work: checks availability, books the slot, updates the CRM, answers from your own documents, and routes the call to the right person. The money works differently too — an answering service bills per minute indefinitely, while here you pay once for the build and then only for the services it runs on.
What if we need more than phone answering?
Then the receptionist package is the wrong shape. Once agents have to work across your CRM, ticketing, and internal systems, read records, run multi-step tasks and hand off to a person when they get stuck, that is custom enterprise AI agent work, scoped per engagement rather than sold as a box. I build both, and the discovery call sorts out which one you need.
Put an Agent on Your Phone Line
Thirty minutes to go through your call volume, the flows worth automating, and whether the $10,000 fixed package fits what you need.
Fixed price, agreed scope, documentation at handover.
Related reading
Voice agents, LLM systems in production, and what AI changes in day-to-day operations.
