What inputs does the Invoice Data Extractor & Matcher workflow use?

The workflow uses Invoice, Purchase Orders. Required fields and their expected formats are listed on this page.

What resources are included in the Invoice Data Extractor & Matcher blueprint?

The blueprint contains 2 AI agents, 0 functions, 0 MCP servers. Its workflow pattern is Dag.

All blueprints Finance AI workflow blueprint

AI Invoice Data Extractor & Matcher workflow blueprint

Extract line items from invoices and match them against purchase orders

See where this blueprint fits in the production workflow lifecycle

Finance

Invoice

Extraction

Matching

Request access

Pattern

Dag

Agents

2

Functions

0

MCP servers

0

Inputs for the Invoice Data Extractor & Matcher workflow

Provide the following information when starting this workflow. Required inputs are validated before the first workflow stage runs.

Invoice
Required
Invoice document content
Type: String
Purchase Orders
Required
Related purchase order data
Type: String

Input template

This request shape is generated from the blueprint's input schema. Angle-bracket values are placeholders; defaults and examples appear only when the source blueprint defines them.

{
  "invoice": "<required string>",
  "purchase_orders": "<required string>"
}

How the Invoice Data Extractor & Matcher AI workflow works

This finance blueprint uses a dag workflow with 2 agents, 0 functions, and 0 MCP servers. This catalog blueprint is available by request; contact GraphN to discuss access and customization for your use case.

Invoice Parser
Agent using Invoice Parser
PO Matcher
Agent using PO Matcher

Blueprint resources and prerequisites

These are the actual agents, functions, and MCP servers declared by the blueprint. If an MCP server connects to an external system, configure the required connection and credentials in your GraphN workspace before running the workflow.

AI agent

Invoice Parser

Extract structured data from the invoice: vendor, line items, quantities, amounts, dates, payment terms.

AI agent

PO Matcher

Match extracted invoice data against purchase orders and flag discrepancies in pricing, quantities, or terms.

Workflow output contract

The completed workflow makes the following output available to downstream steps, applications, or API clients:

Matcher

Frequently asked questions

What does the Invoice Data Extractor & Matcher blueprint do?: Extract line items from invoices and match them against purchase orders
What inputs does the Invoice Data Extractor & Matcher workflow use?: The workflow uses Invoice, Purchase Orders. Required fields and their expected formats are listed on this page.
What resources are included in the Invoice Data Extractor & Matcher blueprint?: The blueprint contains 2 AI agents, 0 functions, 0 MCP servers. Its workflow pattern is Dag.
Can I customize the Invoice Data Extractor & Matcher blueprint in GraphN?: This blueprint is currently available by request. Contact GraphN to discuss access and customization for your use case.

Related Finance blueprints

View all finance automation workflows

Expense Report Auditor

Review expense submissions against company policy and flag violations automatically

Financial Narrative Writer

Turn raw financial data into an executive-ready narrative with variance analysis

Investment Due Diligence

Analyze financials and market data to produce a Go/No-Go investment memo

Regulatory Change Monitor

Track regulatory updates relevant to your industry and assess impact on your operations