supplygraph-ai

Procurement & Inventory Risk – Key component Focus

Overview

The Procurement & Inventory Risk – Key component Focus continuously monitors and analyzes upstream product or service risk events to determine whether, how, and to what extent the impact may propagate to a target company.

It transforms fragmented global supply chain signals into structured, auditable, and continuously updated product-driven risk warnings, enabling organizations to monitor upstream product exposure in near real-time.

Pain

Enterprises need continuous visibility into critical upstream products and services — not only to know when key inputs at any tier are impacted by global supply chain events, but to determine whether, how, and to what extent that impact may propagate to their own business.

Without structured product-level risk propagation analysis, organizations often lack:

Traditional monitoring tools may detect upstream events, but they usually cannot explain how disruptions affecting specific products or services propagate through dependency paths to the target company.

Breakthrough

The Supply Chain Risk Prediction – Cross-Product Agent extends supply chain monitoring into product-driven risk propagation.

Behind the scenes, it:

For the user, the workflow remains simple:

  1. Provide a target company and an upstream product or service
  2. Confirm the matched entities
  3. Activate monitoring for the product under the target company
  4. Retrieve the latest product-driven risk warnings at any time

Typical insights include:

Why SupplyGraph AI

Powered by:

SupplyGraph AI provides a continuously updated, auditable product-driven supply chain risk intelligence layer that connects upstream product disruptions to downstream enterprise exposure.

This makes the agent suitable for:

Agent Behavior Model

Sandbox Key Support (for Development)

This agent supports Sandbox API Keys, enabling developers to test integrations without consuming credits.

When using a Sandbox Key:

Sandbox Keys are ideal for:

⚠️ Sandbox data must not be used for production analytics.

The full A2A workflow (run → status → result) behaves the same as production, enabling accurate integration testing.

Initial Monitoring Setup

When a user initiates a new monitoring request through /run without specifying mode, or with mode=run, the agent starts the product-level monitoring customization process for a specific target company.

The request should provide both:

The agent then identifies and returns the matched entities for user confirmation.

First-time workflow:

  1. User calls /run with target company and upstream product or service information
  2. System creates a task_id
  3. Agent returns matched entities for confirmation
  4. User confirms the matched entities by replying Yes
  5. The product monitoring customization is activated
  6. The one-time customization fee is charged
  7. User retrieves the latest warning data via mode=result

After activation:

Pricing & Billing Model

Pricing is based on product-level customization under a target company.

The fee is charged only after the user confirms the matched target company and upstream product or service.

The fee covers:

Understanding task_id and Monitoring Lifecycle

A task_id represents a product monitoring instance under a specific target company.

How task_id is created and maintained

Implications:

Status Endpoint Behavior

The status mode is used to check whether the task setup has completed.

For this agent:

Result Endpoint Behavior

The result mode always returns the latest available warning data for the activated target-product monitoring instance.

Input Requirements

agent_id: supply_chain_risk_prediction_cross_product · MCP tool: supply_chain_risk_prediction_cross_product

Field Required Description
text Yes Target company and supplier/component information

text Format

The text field should include both target company and upstream product or service information.

Recommended format:

target company: company name, country/region, address(optional), website(optional); upstream product: product name (or MPN-XXXXX), company name, country/region, address(optional), website(optional)

Example:

target company: Tesla, Inc. United States; upstream product: Lithium Carbonate Albemarle Corporation United States

Example Response (WAITING_USER)

{
  "success": false,
  "code": "WAITING_USER",
  "data": {
    "task_id": "<task-id>",
    "agent": "supply_chain_risk_prediction_cross_product",
    "stage": "interpreting",
    "content": "Here are the entities we’ve identified.\nTarget Company Name: Tesla, Inc.\nCountry: United States\nUpstream Product: Lithium Carbonate\nCompany Name: Albemarle Corporation\nCountry: United States\nPlease reply [Yes] or [No] to confirm."
  }
}

After the user replies Yes, the product monitoring customization is activated and the one-time fee is charged.

Confirm matched entities when prompted (WAITING_USER). Uses mode=result for latest data.

Integration

Method ID / Tool Documentation
A2A supply_chain_risk_prediction_cross_product a2a.md
MCP supply_chain_risk_prediction_cross_product mcp.md
Agent API supply_chain_risk_prediction_cross_product agent-api.md

Quick examples: A2A / MCP · Agent API

Errors

Common codes → Agent API §10. Returns WAITING_USER for company confirmation. Uses mode=result.

Maintainer: info@supplygraph.ai License: Proprietary / Internal © 2025–2026 SupplyGraph AI. All rights reserved.