How to Extract Read-Only Documents and Send Data to Any Target
$0.00
| Workflow Name: |
Extract Read Document and Send It to Any Target |
|---|---|
| AI Model Type: |
Vision / OCR / LLM |
| Model Provider: |
Goldfinch AI / OpenAI |
| Task Type: |
Text Extraction |
| Input Type: |
PDF / Image / Scanned Docs |
| Output Format: |
JSON / TXT / CSV |
| Who Uses It: |
Content Ops; Data Teams |
Table of Contents
Description
| Problem Before: |
Unreadable scanned documents |
|---|---|
| AI Solution: |
OCR + language modeling |
| Validation (HITL): |
Spot-check review |
| Accuracy Metric: |
Character accuracy rate |
| Time Savings: |
90% faster digitization |
| Cost Impact: |
Reduced manual transcription |
Extract Read Document and Send It to Any Target
This workflow enables Read Document Extraction from PDFs, images, and scanned documents using vision, OCR, and LLM models.
Automated Text Capture for Structured Data
The system extracts textual content, converts it into structured JSON, TXT, or CSV formats, and sends it to any target system. It helps content operations and data teams reduce manual effort, improve accuracy, and accelerate document processing workflows.
Watch Demo
| Video Title: |
How to Overcome Supplier & Fulfilment Challenges? – D2C No-Inventory Model Explained |
|---|---|
| Duration: |
3:09 |
Outcome & Benefits
| Accuracy: |
99% OCR accuracy |
|---|---|
| Touchless Rate: |
90% |
| Time Saved: |
From 5m to 20s/page |
| Cost Saved: |
$0.15 per page |
Functional Details
| Business Tasks: |
Text digitization |
|---|---|
| KPI Improved: |
Text accuracy; speed |
| Scheduling: |
Batch / Real-time |
| Downstream Use: |
Datalake / Search Index |
Technical Details
| Model Name/Version: |
GPT-4o-mini Vision |
|---|---|
| Hosting Type: |
Cloud API |
| Prompt Strategy: |
Text-cleaning prompts |
| Guardrails: |
Language detection checks |
| Throughput: |
200 pages/min |
| Latency: |
~0.8s/page |
| Data Governance: |
No document retention |
FAQ
1. What is the Extract Read Document and Send It to Any Target workflow?
It is an AI-powered workflow that uses vision, OCR, and LLM models to extract text and structured information from documents and send it to any target system.
2. How does the workflow work?
The workflow ingests PDFs, images, or scanned documents, applies OCR and LLM models to extract readable text and key data points, and exports the output in JSON, TXT, or CSV format to the configured target.
3. What types of documents can be processed?
It supports a wide range of documents including reports, forms, letters, manuals, scanned documents, and other text-based files.
4. What AI models are used in this workflow?
The workflow uses vision, OCR, and LLM models provided by Goldfinch AI and OpenAI to accurately read, interpret, and structure textual content.
5. What is the output of the workflow?
The extracted text and structured data is output in JSON, TXT, or CSV format and can be sent to Datalakes, CMS, analytics platforms, or downstream applications.
6. Who uses this workflow?
Content Operations Teams and Data Teams use this workflow to automate text extraction, reduce manual effort, and standardize document processing.
7. What are the benefits of automating document text extraction?
Automation improves text extraction speed and accuracy, ensures consistent data structuring, reduces manual errors, and enables seamless integration with downstream systems.
Resources
Case Study
| Industry: |
Publishing / Enterprise Docs |
|---|---|
| Problem: |
Unreadable text data |
| Solution: |
AI-powered OCR |
| Outcome: |
Fully searchable documents |
| ROI: |
1-month payback |

