---
title: "Features"
slug: "features-1"
updated: 2026-06-02T12:03:16Z
published: 2026-06-02T12:03:16Z
canonical: "docs.knovvu.com/features-1"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.knovvu.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Features

## Overview

The Coaching & Training module provides tools to improve contact center agent performance. It consists of three main sections:

| Section | Description | 
|---|---|
| **Coaching Dashboard** | Agent performance tracking, feedback management, AI reports | 
| **Conversation Simulation** | Simulation environment for agent practice | 
| **Email Alerts** | Automated coaching notifications triggered by category matches | 
---

## 1. Coaching Dashboard

The main screen that combines AQM evaluation data with AI-driven analysis. Targeted at Supervisor and Quality Analyst roles.

### Panel 1 — Coaching Panel

General performance view based on AQM evaluations.

**Metric Cards:**

| Metric | Description |
|---|---|
| Evaluations | Number of evaluations completed in the selected period |
| Agents | Number of evaluated agents |
| Average Score | Form-based average score |

**Visualizations:**
- **Score Trend:** Time series chart showing score progression
- **Question Performance:** Success distribution at the form question level

### Panel 2 — Quality Panel

Performance panel tracking KPI metrics over time.

| Component | Description |
|---|---|
| KPI Bar Cards | Bar chart view per metric |
| KPI Group Panel | Grouped metric summary |
| KPI Trend | KPI change over time |

**Supported Metrics:**

| Metric | Direction |
|---|---|
| Estimated CSAT | Higher is better |
| First Call Resolution (FCR) | Higher is better |
| Transfer Ratio | Lower is better |
| Avg Conversation Duration | Lower is better |
| Avg Hold Duration | Lower is better |
| Avg Silence Duration | Lower is better |

### Panel 3 — Feedback Panel

Lists and queries evaluation feedback from multiple perspectives.

**Search Types:**

| Type | Description |
|---|---|
| All | All feedback combined |
| Question-based | Per form question |
| Form-based | Per evaluation form |
| User-based | Per agent |
| Conversation-based | Per conversation |

### Panel 4 — AI Coaching Report Panel

Displays periodic, LLM-generated coaching analysis reports per agent. **Premium** feature — requires an OpenAI/Azure LLM connection.

**Report Contents:**

| Field | Detail |
|---|---|
| Positive Feedbacks | Agent strengths (up to 5 items) |
| Negative Feedbacks | Behaviors requiring improvement (up to 5 items) |
| Improvement Areas | 5 focus areas selected from a predefined list |
| Training Plan | 4 training recommendations: 2 High + 2 Medium priority |
| Progress Summary | Comparison with the previous period (max 2 sentences) |
| Improvement Areas Comparison | Status of focus areas from the previous period |

**Priority Levels:**

| Level | Value |
|---|---|
| High | 3 |
| Medium | 2 |
| Low | 1 |

### Panel 5 — Performance Panel

Compares agents as "Top Performers" and "Needs Coaching."

---

## 2. AI Coaching — How It Works

### Period Types

| Type | Description |
|---|---|
| 7 Days | Weekly cycle |
| 14 Days | Bi-weekly cycle |
| Monthly | Monthly cycle |

### Configuration (Admin > Settings > Generative AI > AI Coaching)

| Setting | Description |
|---|---|---|
| Enabled | Activates AI Coaching |
| Start Date | The date from which analysis begins |
| Period | Period type |
| Target Selection | Who the reports are generated for |
| Targets | Target user/department/group IDs |
| Max Conversations Per Agent |  Maximum conversations analyzed per agent per period |

### LLM Integration

The analysis runs automatically via a background job at the end of each period:

1. Conversations from the period are collected (up to the **Max Conversations Per Agent** setting)
2. AI Insights data (summary, topic, conversation_result, etc.) is compiled
3. Improvement areas from the previous period are retrieved
4. Data is sent to the LLM; the response is parsed and stored as an `AICoachingReport`

**Supported LLM Providers:** OpenAI, Azure OpenAI, Private LLM

---

## 3. Conversation Simulation

A module where agents can practice using scenarios based on real past conversations.

| Mode | Description |
|---|---|
| Test Mode | Simulation for evaluation purposes |
| Practice Mode | Free-form practice simulation |

**Features:**
- Simulation list with filtering and sorting
- Detail view and playback (player component)
- Dedicated detail panel per simulation

---

## 4. Email Alerts

Email Alerts is a coaching feature that notifies relevant stakeholders whenever a conversation matches a defined category. When a category match occurs, the system automatically sends an email to inform the agent, supervisor, or other designated recipients — enabling timely coaching interventions based on real conversation data.

### Notification Schedule

| Type | Description |
|---|---|
| Immediately | Sent as soon as a category match is detected |
| Hourly | Hourly digest |
| Daily | Daily digest |
| Custom | Custom date/time interval |




| Document Number | Revision Number | Revision Date |
| --- | --- | --- |
| KN.GU.02.EN | Rev1 | 01.06.2026 |