VoiceAI
Conversational AI agents for inbound and outbound communications
The agent holds a phone conversation in real time, pulls data from the customer's systems and records the outcome there. Critical operations follow a script, while free dialog is handled by a language model.
- Agent
Hello! Clinic front desk. Please tell me your last name and date of birth.
- Patient
Smirnova, the twelfth of March, eighty-seven.
MIS · patient found - Agent
Anna, the nearest slots with the GP are tomorrow at 10:30, at 11:15…
barge-in · agent listens - Patient
Ten thirty works.
- Agent
You are booked with the GP tomorrow at 10:30, room 214. Goodbye!
MIS · booking created
"status": "booked""doctor": "therapist""slot": "10:30"→ booking in the MISOne dialog step in a fraction of a second
Every caller utterance passes through a processing chain: from the audio stream to an action in the information system and a spoken reply.
- 01Audio
Caller speech
Voice is streamed from the PBX in real time, with no intermediate files.
- 02STT
Recognition
Streaming recognition with interim hypotheses: the agent understands a phrase before it ends.
- 03Parsing
Normalization
Dates, times, numbers, phone numbers and addresses are converted to machine format.
- 04Decision
Script and LLM
The reply and the action are chosen: a system query, a booking, a transfer to an operator.
- 05TTS
Speech synthesis
The reply is voiced with controlled pronunciation of terms, names and addresses.
A script where precision matters. An LLM where flexibility matters
A conversation is assembled from blocks. Identification, confirmations and data entry are deterministic, and the free part of the dialog is handed to a language model within defined limits.
- Critical operations follow a script: the outcome is predictable and verifiable
- The LLM works within limits: the task, context from customer systems, the response format, a step limit
- Every model step returns a structured response rather than free text
- Non-standard requests are handed to an operator together with the conversation context
- Script
Greeting and identification
Last name and date of birth by a strict script
- Integration
Patient lookup in the MIS
A query to the clinic information system
- LLM
Choosing a time slot
Free dialog: doctor, day, convenient time
- Script
Confirmation
Explicit consent before booking
- Result
Booking in the MIS
Structured data, no manual entry
The agent understands how people actually speak
Callers say dates, numbers and addresses in many ways. A dedicated handler works for each answer type, so exact values reach the system.
Voice agents across industries
Live projects and ready-made standard scenarios. Every solution is integrated with the customer's information system: the agent pulls data from it and records the outcome of the call there.
- Task
- Offload the front desk at peak hours and handle calls around the clock.
- Agent
- Identifies the patient in the MIS, offers free slots, books an appointment, a home visit or a prescription request.
- Result
- The booking or request is created in the MIS. Non-standard requests go to the front desk.
I need a doctor to come over, I have a high fever.
What is your temperature right now?
Thirty-eight point five.
temperature · 38.5 °CI have booked a home visit for today. The doctor will come between 2 and 6 pm.
- Task
- Reduce no-shows and keep doctors' time fully used.
- Agent
- A day before the visit, calls the patient by name, states the doctor, date and time, and asks whether plans have changed.
- Result
- A confirmed appointment is marked in the MIS, a cancelled one immediately frees the slot for other patients.
Hello, Olga! A reminder: tomorrow at 9:40 you have an appointment with the cardiologist, Dr. Belova, room 312. Are your plans still the same?
MIS · tomorrow's appointmentI cannot make it tomorrow, I am going away.
I see, Olga, I am cancelling your appointment. Goodbye!
MIS · slot released- Task
- Check with every resident whether the issue was fixed, without loading the dispatchers.
- Agent
- Calls the resident, recalls the complaint and the address, finds out the outcome. If the issue persists, asks for details.
- Result
- The status and the resident's comment go to the complaint tracking system for re-inspection.
You reported no hot water at 14 Mira Street. Has the issue been fixed?
There is water, but it is barely warm.
I see. Since what day has the water been running?
Since Tuesday.
partially fixed- Task
- Quickly find available drivers for every trip.
- Agent
- Calls the driver base, describes the load, route and date, answers questions about the trip, detects secretaries and voicemail.
- Result
- Agreement or refusal with a reason. Dispatchers work only with interested drivers.
There is a load: rolled steel, twenty tons, from Moscow to Chelyabinsk, on the twenty-eighth of April. Can you take it?
What is the rate?
The dispatcher will tell you the rate when they call. Would you consider the trip?
Fine, let them call.
decision · agree- Task
- Reduce utility payment arrears without loading the customer service team.
- Agent
- Informs about the amount owed on the account, answers billing questions, records a promise to pay with a date and suggests payment options.
- Result
- The promise to pay with a date goes to billing. Disputed charges go to a specialist, and a follow-up call is scheduled automatically.
Hello, Sergey! This is the billing center. Your account at 8 Gagarina Street has an outstanding balance of 4,820 rubles for August and September. When are you planning to pay?
billing · customer and balanceOn Friday, after payday.
promise to pay · FridayThank you, Sergey, I have noted the payment for Friday. You can pay the bill in your banking app using the QR code. Goodbye!
- Task
- Cut failed deliveries and offload the call center during sales seasons.
- Agent
- Confirms the order and address, agrees on a delivery window, reschedules or cancels the order at the customer's request.
- Result
- A new window or a cancellation reaches the delivery system immediately, and the courier gets an up-to-date route.
Hello, Elena! Your coffee machine order is ready for delivery. Is tomorrow between 10 am and 2 pm convenient?
CRM · customer and orderNo, better after six in the evening.
window · 18:00–22:00Sure, Elena, I have moved the delivery to tomorrow, 6 to 10 pm. The courier will call an hour before arrival.
Mass calling under control
Tasks come from the customer's systems, calls follow a schedule and every result goes back. Operators are left with targeted conversations only.
- 01
Tasks
A list of contacts from a CRM, the customer's API or a spreadsheet
- 02
Schedule
Calls only within allowed windows by weekday and time zone
- 03
Retries
Redialing with a set interval and attempt limit
- 04
Filtering
Secretaries, voicemail and voice assistants are detected and the call ends properly
- 05
Result
The outcome and transcript go back to the customer's system
- Attempt 1 · no answer
- Attempt 2 · voice assistant, call ended
- Attempt 3 · conversation, agreed
agree → dispatcher tasksSpeech technologies and language models for the task
The provider is chosen for the project: recognition quality, voice, cost, where data is processed. Switching providers does not require reworking scenarios.
Speech recognition
Speech synthesis
Language models
Personal data compliance
Russian providers or local models inside the customer's perimeter: callers' personal data never leaves it, in line with Russian Federal Law 152-FZ.
Let's discuss your project
We will contact you, clarify the requirements and propose a pilot project format. Pricing is determined individually based on the assessment.