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Description

The AI Command Center is a centralized dashboard for monitoring and managing AI use cases. It provides execution log analysis, performance metrics, cost tracking, and chat session management for all AI implementations.

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What you can do:

• Create and manage AI Use Cases
• Monitor execution logs and performance metrics
• Track costs and optimize spending
• Review chat conversations for conversational agents

Getting Started

Accessing the AI Command Center

Navigate to AI Command Center from the main menu. You will see the dashboard with all your AI Use Cases displayed as cards. Each card shows key metrics like execution count, success rate, and total cost.

Understanding the Dashboard

The main dashboard displays:

• Summary statistics: Total use cases, executions, costs, and average success rate at the top
• Date range filter: Controls data visibility for specific time periods
• Search box: Find specific use cases by name
• Sort options: Order by name, executions, cost, or creation date
• Use Case cards: Individual cards showing metrics for each AI implementation

Use Case Types

There are two types of AI implementations you can manage:

• SimpleT AI Component: Single-turn AI operations that process input and provide immediate output (for example, translation, classification, content generation)
• Chat Agent: Multi-turn conversational AI that maintains context across multiple messages (for example, customer support bots, virtual assistants)

Creating Use Cases

Step‑by‑step use case creation

Step 1: Select Create Use Case in the top‑right corner of the dashboard.

Step 2: Fill out the creation form with these required details:

• Name: Enter a descriptive name that clearly identifies the purpose (for example, “Customer Support Email Classifier”, “Sales Lead Chat Assistant”)
• Description: Provide a detailed explanation of what this use case accomplishes
• Type: Select either SimpleT AI Component for single operations or Chat Agent for conversations
• Status: Choose Active to enable immediate execution or Inactive for testing

Step 3: Configure tracking connections:

• Use Case API Names: Add API endpoint identifiers that will be associated with this use case. When these APIs are called, execution logs automatically attach to this use case for tracking.
• Active Prompt Builders: Select which prompt templates from the Prompt Builder will be connected. Executions using these prompts are tracked under this use case.

Step 4: Set cost parameters (optional):

• Fixed cost: Enter any operational costs beyond token usage (for example, infrastructure, licensing)
• Cost per execution: Set a baseline cost if not using token‑based pricing

How execution logs connect

Once created, execution logs automatically attach to your use case based on:

• API name matching: When any of your specified Use Case API Names are called in the system, those execution logs are linked to this use case
• Prompt Builder connections: When any of your connected Active Prompt Builders are executed, those logs are automatically tracked
• Real‑time tracking: New executions appear immediately in your use case metrics and detailed logs

Updating Use Cases

Modifying existing use cases

• Select any use case card to open the detail view
• Select Edit Use Case in the top‑right
• Access the full editing form with all configuration options
• Save changes and return to the dashboard

What you can update

• Basic information: Name, description, and status
• API connections: Add or remove Use Case API Names for tracking
• Prompt Builder links: Connect or disconnect Active Prompt Builders
• Cost settings: Modify fixed costs and operational parameters
• Activation status: Enable or disable the use case

Impact of updates

When you update a use case:

• Historical data: Past execution logs remain unchanged
• Future tracking: New API Names and Prompt Builders take effect immediately
• Metrics recalculation: Dashboard metrics update in real time
• Log association: New executions are tracked based on the updated connections

Execution Logs Analysis

Accessing execution logs

Navigate to the Execution Logs tab to view comprehensive execution data. This is your primary tool for debugging, performance monitoring, and understanding AI behavior patterns.

Filtering and search capabilities

The execution logs interface provides powerful filtering options:

• Date range filter: Select specific time periods (last 24 hours, 7 days, 30 days, or a custom range)
• Status filter: View only successful executions, failures, or pending operations
• Use Case filter: Focus on specific use cases or view all executions
• User filter: Filter by Salesforce user ID or username to see individual user patterns
• Organization filter: View executions by Salesforce organization (useful for multi‑org setups)
• AI model filter: Filter by specific AI models (for example, GPT‑4, Claude)

Chat Sessions Management

Understanding chat sessions

For Chat Agent use cases, the system tracks complete conversation threads. Navigate to Chat Sessions to analyze multi‑turn conversations and user interactions.

Session organization

Chat sessions are organized hierarchically:

• Session groups: Conversations grouped by user and time period
• Individual sessions: Complete conversation threads with start and end times
• Message threads: Individual messages within each session
• Context preservation: How context carries forward between messages

Session details and analytics

Each chat session provides comprehensive information.

Session overview

• Duration: Total conversation length from start to finish
• Message count: Number of exchanges between user and AI
• Completion status: Whether the conversation reached a natural conclusion
• User satisfaction: Feedback provided at the end of the session