How to Extract General Documents and Send Data to Any Target
$0.00
| Workflow Name: |
Extract General Document and Send It to Any Target |
|---|---|
| AI Model Type: |
LLM / Vision |
| Model Provider: |
Goldfinch AI / OpenAI |
| Task Type: |
Generic Document Extraction |
| Input Type: |
PDF / Image / Text |
| Output Format: |
JSON / CSV |
| Who Uses It: |
Operations; IT Teams |
Table of Contents
Description
| Problem Before: |
Unstructured document chaos |
|---|---|
| AI Solution: |
Universal OCR + AI structuring |
| Validation (HITL): |
Optional QA sampling |
| Accuracy Metric: |
Extraction accuracy % |
| Time Savings: |
70% faster processing |
| Cost Impact: |
Reduced manual effort |
Extract General Document and Send It to Any Target
This workflow enables Document Extraction from PDFs, images, or text using LLM and vision models.
Flexible Document Processing
The system reads unstructured content, converts it into structured JSON or CSV, and sends it to any target system. It helps operations and IT teams automate document handling, reduce manual effort, and improve data accuracy across workflows.
Watch Demo
| Video Title: |
How eZintegrations™ AI Document Understanding do data validation & transformation? |
|---|---|
| Duration: |
3:05 |
Outcome & Benefits
| Accuracy: |
96% |
|---|---|
| Touchless Rate: |
78% |
| Time Saved: |
From 7m to 2m/doc |
| Cost Saved: |
$0.35 per doc |
Functional Details
| Business Tasks: |
Document normalization |
|---|---|
| KPI Improved: |
TAT; data usability |
| Scheduling: |
Batch / Real-time |
| Downstream Use: |
Datalake / Any System |
Technical Details
| Model Name/Version: |
GPT-4o-mini |
|---|---|
| Hosting Type: |
API / Cloud |
| Prompt Strategy: |
Flexible schema prompts |
| Guardrails: |
Content validation rules |
| Throughput: |
120 docs/min |
| Latency: |
~2s/doc |
| Data Governance: |
Customer data isolation |
FAQ
1. What is the Extract General Document and Send It to Any Target workflow?
It is an AI-powered workflow that extracts and structures information from general-purpose documents using LLM and vision models and sends the output to any target system.
2. How does the workflow work?
The workflow ingests documents in PDF, image, or text format, applies LLM and vision models to understand and extract relevant content, and exports structured data in JSON or CSV format to the configured target.
3. What types of documents are supported?
It supports a wide range of documents such as reports, forms, letters, policies, manuals, and other unstructured or semi-structured documents.
4. What AI models are used in this workflow?
The workflow uses LLM and vision models from Goldfinch AI and OpenAI to accurately interpret and structure diverse document types.
5. What is the output of the workflow?
The extracted document data is output in JSON or CSV format and can be sent to any downstream system such as Datalake, ERP, CMS, or analytics platforms.
6. Who uses this workflow?
Operations Teams and IT Teams use this workflow to automate document processing, reduce manual effort, and standardize data extraction across various document types.
7. What are the benefits of using a general document extraction workflow?
It provides flexibility for multiple document types, improves processing speed, ensures consistent data structuring, and enables seamless integration with downstream systems.
Resources
Case Study
| Industry: |
Cross-industry |
|---|---|
| Problem: |
Mixed document formats |
| Solution: |
Generic AI extraction |
| Outcome: |
Standardized data output |
| ROI: |
3-month payback |
