Online AI Analysis

Real-Time AI Analysis of Agent Calls

The system allows analyzing a manager's current call in real time. If communication issues are detected, the system alerts a more experienced manager or team lead about the problem. As a result, they can promptly take over and complete the conversation with the client.

Real-Time Call Quality Control

The agent conducts the conversation with the client, while the system simultaneously transcribes the dialogue and analyzes its content, speech, and context.

AI identifies signs that may affect the outcome of the call: insufficient agent competence, unclear speech, improper communication, deviation from the script, issues with handling objections, and other parameters set for a specific campaign.

Upon detecting a problem, the system sends a signal to the responsible employee via API. A team lead or more experienced agent can join the ongoing call and continue it with the client.

This approach enables quality control not only after calls are completed but also directly during the conversation.

The Challenge of Agent Monitoring

In call centers and sales departments, a large number of conversations take place simultaneously. It is impossible to manually listen to all of them.

Post-hoc analytics allow identifying agent errors only after the call has ended. At that point, the outcome of the conversation can no longer be changed.

Manual monitoring is also limited by the volume of calls. A team lead can regularly listen to only a portion of the dialogues, so certain issues in agent performance may go unnoticed.

Online analysis shifts quality control directly to the moment of communication with the client.

How Online Call Analysis Works

The service connects to the company's telephony infrastructure via API and receives the audio stream of the current call.

A typical scenario may work as follows:

Asterisk + SIP trunk → Service API → Transcription → Dialogue analysis → Problem detection → AI hint → Team Lead API → Joining the call

The system processes the agent's conversation with the client in real time and compares it with the pre-defined campaign parameters.

The following may be used for analysis:

• conversation content;

• campaign context;

• compliance with the established script;

• emotional tone of speech;

• signs of conflicting communication;

• speech quality and clarity;

• agent competence within the defined script;

• handling of questions and objections;

• presence of critical errors;

• other parameters defined by the company.

AI Analysis of Every Conversation

Before launching a campaign, the rules and context necessary for call analysis are defined.

Our database stores information relevant to a specific campaign. This allows the system to take the conversation context into account, rather than analyzing individual phrases in isolation.

The transcribed dialogue is sent for processing to AI models. The system determines the current situation in the conversation and generates a corresponding signal or hint.

Depending on the campaign settings, information may be sent to the Team Lead via API.

Call Takeover When a Problem Arises

One of the system's functions is sending a signal to the responsible employee when a conversation requires additional oversight.

For example, AI may determine that the agent:

• cannot answer the client's question;

• incorrectly explains the offer terms;

• deviates from the defined script;

• fails to handle an objection;

• uses incorrect wording;

• enters into a conflict with the client;

• speaks with insufficient clarity;

• exhibits other signs of problematic communication.

After receiving the signal, various operational scenarios are possible.

Signal to SuperOperator

When a defined condition is met, the system alerts the client with a notification about the need to connect a more experienced agent to the current call.

This allows communication to continue without waiting for the conversation to end and for a subsequent review of the situation.

Online Analytics Instead of Post-Call Control Only

Traditional call analytics works with already completed conversations: the call is recorded, then transcribed, analyzed, and included in a report.

Online analysis adds another level of control — a response directly during the conversation.

After the call: identify the problem and use it for agent training.

During the call: identify the problem and pass the information to the Team Lead to change the further course of the conversation.

Both approaches can be used simultaneously: online signals help react to current situations, while accumulated analytics helps evaluate agent performance and identify systemic issues.

Agent Performance Analysis

The system can be used not only for taking over individual calls but also for comprehensive analysis of team performance quality.

Based on processed dialogues, the company receives data for evaluating:

• communication quality;

• script compliance;

• typical agent errors;

• handling of objections;

• speech quality;

• problematic stages of the conversation;

• reasons why the dialogue does not lead to the target action.

This data can be used for employee training, script adjustments, and configuring service or sales processes.

AI for Call Centers and Sales Departments

Online call analysis is suitable for companies where the outcome depends on the quality of telephone communication.

Application scenarios include:

• sales departments;

• call centers;

• support services;

• client service;

• client reactivation departments;

• outbound sales;

• processing the existing client base;

• mass calling.

The system can work with different scenarios and analysis parameters depending on the specific company's tasks.

What the Company Gets

Online AI call analysis allows combining the following in a single process:

Telephony → Transcription → AI analysis → Problem detection → Team Lead notification → Connecting a more experienced agent.

As a result, quality control becomes part of the telephone conversation itself, not just the subsequent analysis of recordings.

The service can be used as an additional AI tool for sales, support, and call centers where it is important to promptly detect communication problems and transfer complex conversations to more experienced employees.