Component Lifecycle Predictor Agent

Agent Description:

The Component Lifecycle Predictor Agent helps businesses manage the lifecycle of hardware components by identifying parts nearing or past their end-of-life (EOL) and recommending suitable replacements. It processes invoice and product documents to determine warranty status and lifecycle stage, then cross-references availability and market trends to suggest up-to-date alternatives that are better performing or more efficient.

Purpose and Components
  • Purpose: To monitor component lifecycle status and recommend replacements for expired or end-of-life products based on market trends and supplier data.
  • Components:
    • Invoice and product document parsing for lifecycle metadata.
    • Lifecycle classification and EOL tagging.
    • Integration with manufacturer and sales data for alternative recommendations.
Supported Capabilities
  • Parsing product and invoice PDFs for component metadata.
  • Classifying components as "Active" or "Expired" based on EOL.
  • Structuring lifecycle insights in a machine-readable format.
  • Recommending alternative parts with better performance or extended warranties.
  • Filtering replacement suggestions using supplier data and sales popularity.
LLM Used
  • Google Vertex
    Note: To learn more about the LLM and to modify its behavior, refer to the Configuring LLM settings section.

Sub-Agents

1. Component Lifecycle Extractor

  • Role:Data Extractor.
  • Scope:Processes component documents (e.g., component.pdf) to extract lifecycle-relevant information and classify status.
  • Description: This sub-agent uses RAG and OCR capabilities to:

    • Extract fields like: Component Name, Manufacturer, Invoice Date, End-of-Life (EOL), and Warranty Expiry.

    • Compare the EOL against the current date to classify each component as Active or Expired.

    • Outputs a clean, structured dataset containing all parsed fields with lifecycle status for downstream analysis.

  • LLM Used: Google Vertex (inherits from parent).
  • Tool Used: MCP Client Tool

2. Replacement Suggestion Agent

  • Role:Solution Recommender.
  • Scope:Uses the expired component list and filters from market or manufacturer data to suggest appropriate replacements.
  • Description: This sub-agent:

    • Receives the expired components list from the Lifecycle Extractor.

    • Searches for better alternatives based on performance, efficiency, warranty, or launch recency.

    • Integrates available data from Sales and Manufacturer Agents to prioritize available and popular models.

    • Outputs structured recommendations including:

      • Suggested Replacement

      • Manufacturer

      • Launch Date

        Upgrade Rationale

  • LLM Used: Google Vertex (inherits from parent).
Tools Used:
  • MCP Client Tool : Used by the Lifecycle Extractor to parse invoice/product PDFs and extract metadata.
Note: For details on modifying the Tools, refer Tools Library section.
Agent Workflow Behavior Summary
  • The Component Lifecycle Extractor opens the component.pdf file and uses OCR and RAG methods to extract relevant data, including:
    • Component Name, Manufacturer, Invoice Date, Warranty Expiry, and End-of-Life (EOL).
  • It compares each component’s EOL to the current date to classify it as Active or Expired, and outputs a structured dataset for further use.
  • The Replacement Suggestion Agent receives the list of expired components.
  • It searches available component data (via Sales or Manufacturer Agents) for modern, efficient, and supported replacements.
  • Each suggestion includes:
    • A suitable replacement component
    • Manufacturer details
    • Launch date of the new product
    • A brief rationale explaining the upgrade or replacement
  • The output is structured, concise, and ready for integration into asset management or procurement workflows.
Sample Questions:
  • Analyze our component database and identify parts that have a high risk of becoming obsolete in the next 24 months