How to Extract Receipt Data and Send It to Any Target

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Workflow Name:

Extract Receipt and Send It to Any Target
AI Model Type:

Vision / LLM
Model Provider:

Goldfinch AI / OpenAI
Task Type:

Receipt Data Extraction
Input Type:

Image / PDF
Output Format:

JSON / CSV
Who Uses It:

Finance Teams; Expense Ops
Category:

Description

Problem Before:

Manual receipt entry
AI Solution:

OCR + line-item parsing
Validation (HITL):

Exception-based review
Accuracy Metric:

Field-level accuracy
Time Savings:

85% faster expense processing
Cost Impact:

Lower accounting effort

Extract Receipt and Send It to Any Target

This workflow enables Receipt Data Extraction from images and PDFs using vision and LLM models.

Automated Expense Data Processing

The system captures key receipt details such as vendor, date, amount, and line items, structures the data into JSON or CSV, and sends it to any target system. It helps finance teams and expense operations reduce manual entry, improve accuracy, and streamline expense management workflows.

Watch Demo

Video Title:

Automate E-Way Bill Generation from ERP or Accounting Software
Duration:

3:03

Outcome & Benefits

Accuracy:

98%
Touchless Rate:

75%
Time Saved:

From 4m to 45s/receipt
Cost Saved:

$0.40 per receipt

Functional Details

Business Tasks:

Expense capture
KPI Improved:

Expense cycle time
Scheduling:

Batch / Real-time
Downstream Use:

Datalake / ERP Expenses

Technical Details

Model Name/Version:

GPT-4o-mini Vision
Hosting Type:

Secure Cloud API
Prompt Strategy:

Receipt schema prompts
Guardrails:

Fraud detection rules
Throughput:

100 receipts/min
Latency:

~1.5s/receipt
Data Governance:

Financial data isolation

FAQ

1. What is the Extract Receipt and Send It to Any Target workflow?

It is an AI-powered workflow that uses vision and LLM models to extract structured data from receipts and send it to any target system.

2. How does the workflow work?

The workflow ingests receipt images or PDFs, applies vision and LLM models to extract relevant fields such as vendor, date, amount, and line items, and exports the data in JSON or CSV format to the configured target.

3. What information can be extracted from receipts?

It can extract details such as merchant name, transaction date, total amount, tax, line items, payment method, and other receipt metadata.

4. What AI models are used in this workflow?

The workflow uses vision and LLM models provided by Goldfinch AI and OpenAI to accurately recognize and structure receipt data.

5. What is the output of the workflow?

The extracted receipt data is output in JSON or CSV format and can be sent to expense management systems, ERP, Datalakes, or accounting platforms.

6. Who uses this workflow?

Finance Teams and Expense Operations Teams use this workflow to automate receipt processing, reduce manual entry, and improve accuracy.

7. What are the benefits of automating receipt extraction?

Automation improves processing speed, reduces errors, ensures consistent data capture, and enables seamless integration with downstream finance and accounting systems.

Case Study

Industry:

Finance / Accounting
Problem:

Slow expense reporting
Solution:

AI receipt extraction
Outcome:

Faster reimbursements
ROI:

2-month payback

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