IT Asset Management Agent

Agent Description:

The IT Asset Management Agent automates the process of querying and analyzing an organization’s hardware and software inventory. It uses an Asset Data Reader to connect to an SQL database and dynamically execute queries to retrieve relevant asset data. The retrieved information is then passed to the Asset Query Response Agent, which analyzes the data to identify critical issues such as expiring warranties or software licenses. The agent’s final output is a human-readable summary that provides an inventory analysis along with actionable recommendations for the IT team.

Purpose and Components
  • Purpose: To provide an automated way to query and analyze an organization's IT asset inventory (both hardware and software), enabling IT teams to generate reports, identify issues like expiring licenses or warranties, and receive actionable recommendations.
  • Components:

    • Asset Data Reader: An agent that connects to the IT inventory SQL database and fetches relevant asset data based on user queries.

    • Asset Query Response Agent: An agent that analyzes the fetched data, detects trends or issues, and generates human-readable summaries and recommendations.

    • SQL Database Toolkit: A tool used by the Data Reader to interact with the (SQLite) asset database.

Supported Capabilities

  • Connecting securely to an SQL database containing hardware and software asset inventories.

  • Executing SQL queries dynamically based on user intent (e.g., "show all laptops with expiring warranties").

  • Normalizing field names and ensuring consistent JSON output from database queries.

  • Retrieving detailed asset information from both HardwareAssets and SoftwareAssets tables.

  • Analyzing asset information to detect trends, expiring warranties, and software license issues.

  • Generating plain-language summaries suitable for IT or business reporting.

  • Providing actionable recommendations, such as renewal alerts, replacement planning, or follow-ups.

  • Outputting the final analysis as a structured summary in a natural language response.

LLM Used

  • GPT_4O_MINI

    Note: To learn more about the LLM and to modify its behavior, refer to the Configuring LLM settings section.

Sub-Agents

1. Asset Data Reader Agent

  • Role: Data Extraction

  • Scope: Fetch and filter data from SQL tables (HardwareAssets and SoftwareAssets).

  • Description: This agent is the interface to the IT asset database. Based on the user's query, it connects to the SQL database, executes the necessary queries against the HardwareAssets and SoftwareAssets tables, normalizes the results, and returns the relevant asset data in a structured JSON format.

  • LLM Used: Default (Inherits from parent agent).

  • Tools Used: SQL - Toolkit

2. Asset Query Response Agent

  • Role: Insight Generation

  • Scope: Interpret and summarize data from Subagent 1.

  • Description: This agent receives the structured JSON data from the Data Reader. It analyzes this information to identify important patterns or issues, such as assets nearing warranty expiration or software licenses that need renewal. It then generates a plain-language summary of its findings and provides actionable recommendations.

  • LLM Used: Default (Inherits from parent agent).

  • Tools Used: None

Tools Used:

  • SQL - Toolkit (SQLite): Executes queries against a SQLite database containing the HardwareAssets and SoftwareAssets tables.

Note: For details on modifying the Tools, refer Tools Library section.
Agent Workflow Behavior Summary

  1. A user asks a question about IT assets (e.g., "Which laptops need replacing?").

  2. The Asset Data Reader Agent (start node) receives the query, uses the SQL - Toolkit to query the HardwareAssets and SoftwareAssets tables in the database, and retrieves the relevant data.

  3. It passes the structured JSON data to the Asset Query Response Agent.

  4. The Asset Query Response Agent (end node) analyzes the data, identifies key insights (like expiring warranties), and generates a final, human-readable summary with actionable recommendations.

Sample Questions:

  • How many laptops are assigned to employees?

  • Show me all active hardware assets