How to Extract Invoice Data and Send It to Any Target
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| Workflow Name: |
Extract Invoice and Send It to Any Target |
|---|---|
| AI Model Type: |
LLM / Vision |
| Model Provider: |
Goldfinch AI / OpenAI |
| Task Type: |
Invoice Extraction / Classification |
| Input Type: |
PDF / Image |
| Output Format: |
JSON / CSV |
| Who Uses It: |
Finance Ops; AP Teams |
Table of Contents
Description
| Problem Before: |
Manual invoice entry |
|---|---|
| AI Solution: |
OCR + line-item extraction |
| Validation (HITL): |
Sampled QA 5% |
| Accuracy Metric: |
Line-item accuracy % |
| Time Savings: |
75% faster processing |
| Cost Impact: |
Reduced AP workload |
Extract Invoice and Send It to Any Target
This workflow enables Invoice Extraction from PDF or image-based invoices using LLM and vision models.
Automated Accounts Payable Processing
The system captures invoice details such as vendor, amounts, dates, and line items, structures the data into JSON or CSV, and delivers it to any target system. It helps finance operations and AP teams reduce manual entry, improve accuracy, and accelerate invoice processing.
Watch Demo
| Video Title: |
Automated e-Invoice Generation with IRN, QR Code, and GST Compliance Using eZintegrations™ |
|---|---|
| Duration: |
03:41 |
Outcome & Benefits
| Accuracy: |
98% |
|---|---|
| Touchless Rate: |
75% |
| Time Saved: |
From 10m to 2m/invoice |
| Cost Saved: |
$0.30 per invoice |
Functional Details
| Business Tasks: |
AP invoice processing |
|---|---|
| KPI Improved: |
Touchless rate; SLA |
| Scheduling: |
Batch / Real-time |
| Downstream Use: |
Datalake / ERP AP |
Technical Details
| Model Name/Version: |
GPT-4o-mini |
|---|---|
| Hosting Type: |
API / Cloud |
| Prompt Strategy: |
Invoice schema prompts |
| Guardrails: |
Duplicate detection; totals check |
| Throughput: |
90 invoices/min |
| Latency: |
~3s/invoice |
| Data Governance: |
No invoice data training |
FAQ
1. What is the Extract Invoice and Send It to Any Target workflow?
It is an AI-powered workflow that uses LLM and vision models to extract and classify invoice data from invoices and send the structured output to any target system.
2. How does the workflow work?
The workflow ingests invoices in PDF or image format, applies LLM and vision models to extract key invoice fields, classifies the data, and exports the results in JSON or CSV format to the configured target.
3. What invoice information can be extracted?
It can extract details such as invoice number, vendor name, invoice date, line items, amounts, taxes, payment terms, and totals.
4. What AI models are used in this workflow?
The workflow uses LLM and vision models from Goldfinch AI and OpenAI to accurately interpret invoice layouts and content.
5. What is the output of the workflow?
The extracted and classified invoice data is output in JSON or CSV format and can be sent to ERP systems, AP platforms, Datalakes, or accounting tools.
6. Who uses this workflow?
Finance Operations Teams and Accounts Payable Teams use this workflow to automate invoice processing, reduce manual entry, and improve accuracy.
7. What are the benefits of automating invoice extraction?
Automation speeds up invoice processing, reduces errors, improves data consistency, and enables faster approvals and financial reporting.
Resources
Case Study
| Industry: |
Finance / Accounting |
|---|---|
| Problem: |
Slow invoice approvals |
| Solution: |
AI invoice extraction |
| Outcome: |
Faster AP cycles |
| ROI: |
3-month payback |

