# Agent Chat

## Overview

Agent Chat is designed to make AI performance understandable, conversational, and actionable.

Instead of digging through dashboards or interpreting complex metrics, Agent Chat lets you ask natural language questions and get clear, contextual answers about how your AI agents are performing, and what to do next.

It bridges the gap between data and decision-making.

<figure><img src="/files/cONgCGXIFy0zg3KK8pSz" alt=""><figcaption></figcaption></figure>

{% hint style="success" %}

#### **Why Agent Chat Matters**

As AI agents take on more responsibility, understanding *why* they perform the way they do becomes just as important as seeing the metrics themselves.

Agent Chat transforms performance data into insights by:

* Explaining results in plain language
* Highlighting trends and risks early
* Surfacing opportunities for improvement
* Connecting agent behavior to real business outcomes
  {% endhint %}

### What You Can Ask Agent Chat

Agent Chat supports a wide range of performance-focused questions, including:

* Summaries of agent performance and trends
* Objective and Key Result (OKR) status explanations
* Revenue and conversion insights
* Topic-level performance trends
* Recommendations for improving outcomes

#### Sample Questions

* *How’s progress on my OKRs?*
* *What topics are trending?*
* *Where are we underperforming?*
* *How do you make me money?*
* *Why is this KR low?*
* *How can we improve this objective?*
* *What conversations generate the most revenue?*
* *How do you calculate this KR?*

### Built-In Escalation to Your Account Manager

One of Agent Chat’s most powerful features is its ability to recognize **intent**.

If you ask questions that signal a need for improvement, such as:

* *How can I improve performance?*
* *What should we do differently?*

Agent Chat can automatically alert your **Account Manager**.

<figure><img src="/files/V3ardCaxWOUB3ByBbC75" alt=""><figcaption></figcaption></figure>

#### Daily Performance Highlights

Agent Chat also includes **daily, dynamic highlights** in the welcome message that highlight how the agent is performing against its Objectives and Key Results (OKRs).

These nudges may include:

* Whether the agent is on track, ahead, or falling behind on key objectives
* Notable changes in performance

By surfacing these highlights proactively, Agent Chat helps you stay aware of performance trends at a glance without needing to ask or run reports.

<figure><img src="/files/nMc3nkXGuxZ8FYr5B15r" alt=""><figcaption></figcaption></figure>


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.satisfilabs.com/resource-center/ai-agent-engine/agent-performance-console/agent-chat.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.