Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Extract candidate information from a resume PDF, then generate a formatted employee profile document for HR onboarding.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Staffing agencies and HR departments use this pipeline to accelerate onboarding — extracting key details from a candidate's resume and generating a standardized employee profile document ready for internal systems.
Document Extraction (1 credit per page), Document Generation (1 credits/request)
You need an Iteration Layer API key. Get one at platform.iterationlayer.com during the 7-day trial.
For full integration guidance (SDKs, auth, MCP, error handling), see the Iteration Layer Integration Guide.
# Step 1: Extract resume data
EXTRACTION=$(curl -s -X POST https://api.iterationlayer.com/document-extraction/v1/extract \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"files": [
{
"type": "url",
"name": "resume-elena-vasquez.pdf",
"url": "https://example.com/resumes/elena-vasquez-2026.pdf"
}
],
"schema": {
"fields": [
{
"name": "full_name",
"type": "TEXT",
"description": "Candidate full name"
},
{
"name": "email",
"type": "EMAIL",
"description": "Email address"
},
{
"name": "phone",
"type": "TEXT",
"description": "Phone number"
},
{
"name": "address",
"type": "ADDRESS",
"description": "Home address"
},
{
"name": "job_title",
"type": "TEXT",
"description": "Most recent job title"
},
{
"name": "employer",
"type": "TEXT",
"description": "Most recent employer"
},
{
"name": "years_of_experience",
"type": "INTEGER",
"description": "Total years of professional experience"
},
{
"name": "education",
"type": "TEXT",
"description": "Highest degree and institution"
},
{
"name": "skills",
"type": "TEXTAREA",
"description": "Key skills listed on the resume"
}
]
}
}')
# Step 2: Generate an employee profile document
curl -X POST https://api.iterationlayer.com/document-generation/v1/generate \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"format": "pdf",
"document": {
"metadata": {
"title": "Employee Profile — Elena Vasquez",
"author": "Apex Staffing Solutions"
},
"page": {
"size": {
"preset": "A4"
},
"margins": {
"top_in_pt": 54,
"right_in_pt": 54,
"bottom_in_pt": 54,
"left_in_pt": 54
}
},
"content": [
{
"type": "headline",
"level": "h1",
"text": "Employee Profile"
},
{
"type": "headline",
"level": "h2",
"text": "Elena Vasquez"
},
{
"type": "separator"
},
{
"type": "table",
"header": {
"cells": [
{
"text": "Field"
},
{
"text": "Details"
}
]
},
"rows": [
{
"cells": [
{
"text": "Email"
},
{
"text": "elena.vasquez@email.com"
}
]
},
{
"cells": [
{
"text": "Phone"
},
{
"text": "+1 (512) 555-0198"
}
]
},
{
"cells": [
{
"text": "Address"
},
{
"text": "814 Congress Ave, Austin, TX 78701"
}
]
},
{
"cells": [
{
"text": "Current Title"
},
{
"text": "Senior Product Manager"
}
]
},
{
"cells": [
{
"text": "Current Employer"
},
{
"text": "NovaTech Solutions"
}
]
},
{
"cells": [
{
"text": "Experience"
},
{
"text": "8 years"
}
]
},
{
"cells": [
{
"text": "Education"
},
{
"text": "MBA, University of Texas at Austin"
}
]
}
]
},
{
"type": "separator"
},
{
"type": "headline",
"level": "h3",
"text": "Key Skills"
},
{
"type": "paragraph",
"runs": [
{
"text": "Product roadmap planning, Agile/Scrum methodology, cross-functional team leadership, data-driven decision making, user research, A/B testing, SQL, stakeholder management"
}
]
},
{
"type": "separator"
},
{
"type": "paragraph",
"runs": [
{
"text": "Prepared by Apex Staffing Solutions — Confidential"
}
]
}
]
}
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
// Step 1: Extract resume data
const extraction = await client.extractDocument({
files: [
{
type: "url",
name: "resume-elena-vasquez.pdf",
url: "https://example.com/resumes/elena-vasquez-2026.pdf",
},
],
schema: {
fields: [
{ name: "full_name", type: "TEXT", description: "Candidate full name" },
{ name: "email", type: "EMAIL", description: "Email address" },
{ name: "phone", type: "TEXT", description: "Phone number" },
{ name: "address", type: "ADDRESS", description: "Home address" },
{ name: "job_title", type: "TEXT", description: "Most recent job title" },
{ name: "employer", type: "TEXT", description: "Most recent employer" },
{ name: "years_of_experience", type: "INTEGER", description: "Total years of professional experience" },
{ name: "education", type: "TEXT", description: "Highest degree and institution" },
{ name: "skills", type: "TEXTAREA", description: "Key skills listed on the resume" },
],
},
});
const fullName = String(extraction["full_name"].value);
const email = String(extraction["email"].value);
const phone = String(extraction["phone"].value);
const address = String(extraction["address"].value);
const jobTitle = String(extraction["job_title"].value);
const employer = String(extraction["employer"].value);
const yearsOfExperience = String(extraction["years_of_experience"].value);
const education = String(extraction["education"].value);
const skills = String(extraction["skills"].value);
// Step 2: Generate an employee profile document
const profile = await client.generateDocument({
format: "pdf",
document: {
metadata: {
title: `Employee Profile — ${fullName}`,
author: "Apex Staffing Solutions",
},
page: {
size: { preset: "A4" },
margins: { top_in_pt: 54, right_in_pt: 54, bottom_in_pt: 54, left_in_pt: 54 },
},
content: [
{ type: "headline", level: "h1", text: "Employee Profile" },
{ type: "headline", level: "h2", text: fullName },
{ type: "separator" },
{
type: "table",
header: { cells: [{ text: "Field" }, { text: "Details" }] },
rows: [
{ cells: [{ text: "Email" }, { text: email }] },
{ cells: [{ text: "Phone" }, { text: phone }] },
{ cells: [{ text: "Address" }, { text: address }] },
{ cells: [{ text: "Current Title" }, { text: jobTitle }] },
{ cells: [{ text: "Current Employer" }, { text: employer }] },
{ cells: [{ text: "Experience" }, { text: `${yearsOfExperience} years` }] },
{ cells: [{ text: "Education" }, { text: education }] },
],
},
{ type: "separator" },
{ type: "headline", level: "h3", text: "Key Skills" },
{ type: "paragraph", runs: [{ text: skills }] },
{ type: "separator" },
{ type: "paragraph", runs: [{ text: "Prepared by Apex Staffing Solutions — Confidential" }] },
],
},
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
# Step 1: Extract resume data
extraction = client.extract_document(
files=[
{
"type": "url",
"name": "resume-elena-vasquez.pdf",
"url": "https://example.com/resumes/elena-vasquez-2026.pdf",
}
],
schema={
"fields": [
{"name": "full_name", "type": "TEXT", "description": "Candidate full name"},
{"name": "email", "type": "EMAIL", "description": "Email address"},
{"name": "phone", "type": "TEXT", "description": "Phone number"},
{"name": "address", "type": "ADDRESS", "description": "Home address"},
{"name": "job_title", "type": "TEXT", "description": "Most recent job title"},
{"name": "employer", "type": "TEXT", "description": "Most recent employer"},
{"name": "years_of_experience", "type": "INTEGER", "description": "Total years of professional experience"},
{"name": "education", "type": "TEXT", "description": "Highest degree and institution"},
{"name": "skills", "type": "TEXTAREA", "description": "Key skills listed on the resume"},
]
},
)
full_name = extraction["full_name"]["value"]
email = extraction["email"]["value"]
phone = extraction["phone"]["value"]
address = extraction["address"]["value"]
job_title = extraction["job_title"]["value"]
employer = extraction["employer"]["value"]
years_of_experience = extraction["years_of_experience"]["value"]
education = extraction["education"]["value"]
skills = extraction["skills"]["value"]
# Step 2: Generate an employee profile document
profile = client.generate_document(
format="pdf",
document={
"metadata": {
"title": f"Employee Profile — {full_name}",
"author": "Apex Staffing Solutions",
},
"page": {
"size": {"preset": "A4"},
"margins": {"top_in_pt": 54, "right_in_pt": 54, "bottom_in_pt": 54, "left_in_pt": 54},
},
"content": [
{"type": "headline", "level": "h1", "text": "Employee Profile"},
{"type": "headline", "level": "h2", "text": full_name},
{"type": "separator"},
{
"type": "table",
"header": {"cells": [{"text": "Field"}, {"text": "Details"}]},
"rows": [
{"cells": [{"text": "Email"}, {"text": email}]},
{"cells": [{"text": "Phone"}, {"text": phone}]},
{"cells": [{"text": "Address"}, {"text": str(address)}]},
{"cells": [{"text": "Current Title"}, {"text": job_title}]},
{"cells": [{"text": "Current Employer"}, {"text": employer}]},
{"cells": [{"text": "Experience"}, {"text": f"{years_of_experience} years"}]},
{"cells": [{"text": "Education"}, {"text": education}]},
],
},
{"type": "separator"},
{"type": "headline", "level": "h3", "text": "Key Skills"},
{"type": "paragraph", "runs": [{"text": skills}]},
{"type": "separator"},
{"type": "paragraph", "runs": [{"text": "Prepared by Apex Staffing Solutions — Confidential"}]},
],
},
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
result, err := client.ExtractDocument(il.ExtractDocumentRequest{
Files: []il.FileInput{
il.FileInput{
Type: "url",
Name: "resume-elena-vasquez.pdf",
Url: "https://example.com/resumes/elena-vasquez-2026.pdf",
},
},
Schema: il.ExtractionSchema{
Fields: []any{
il.TextFieldConfig{
Name: "full_name",
Type: "TEXT",
Description: "Candidate full name",
},
il.EmailFieldConfig{
Name: "email",
Type: "EMAIL",
Description: "Email address",
},
il.TextFieldConfig{
Name: "phone",
Type: "TEXT",
Description: "Phone number",
},
il.AddressFieldConfig{
Name: "address",
Type: "ADDRESS",
Description: "Home address",
},
il.TextFieldConfig{
Name: "job_title",
Type: "TEXT",
Description: "Most recent job title",
},
il.TextFieldConfig{
Name: "employer",
Type: "TEXT",
Description: "Most recent employer",
},
il.IntegerFieldConfig{
Name: "years_of_experience",
Type: "INTEGER",
Description: "Total years of professional experience",
},
il.TextFieldConfig{
Name: "education",
Type: "TEXT",
Description: "Highest degree and institution",
},
il.TextareaFieldConfig{
Name: "skills",
Type: "TEXTAREA",
Description: "Key skills listed on the resume",
},
},
},
})
if err != nil {
panic(err)
}
_ = result
}
{
"name": "Extract resume data and generate employee profile in Iteration Layer",
"nodes": [
{
"parameters": {
"content": "## Extract Resume Data and Generate an Employee Profile\n\nStaffing agencies and HR departments use this pipeline to accelerate onboarding — extracting key details from a candidate's resume and generating a standardized employee profile document ready for internal systems.\n\n**Note:** This workflow uses the Iteration Layer community node (`n8n-nodes-iterationlayer`). Install it via Settings > Community Nodes on self-hosted n8n, or add it directly on n8n Cloud with Verified Community Nodes enabled.",
"height": 280,
"width": 500,
"color": 2
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [200, 40],
"id": "e5f6a7b8-c9d0-1234-efab-234567890101",
"name": "Overview"
},
{
"parameters": {
"content": "### Step 1: Extract Resume Data\nResource: **Document Extraction**\n\nConfigure the Document Extraction parameters below, then connect your credentials.",
"height": 160,
"width": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [475, 100],
"id": "e5f6a7b8-c9d0-1234-efab-234567890102",
"name": "Step 1 Note"
},
{
"parameters": {
"content": "### Step 2: Generate Employee Profile\nResource: **Document Generation**\n\nConfigure the Document Generation parameters below, then connect your credentials.",
"height": 160,
"width": 300,
"color": 6
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [725, 100],
"id": "e5f6a7b8-c9d0-1234-efab-234567890103",
"name": "Step 2 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [250, 300],
"id": "e5f6a7b8-c9d0-1234-efab-234567890104",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "documentExtraction",
"schemaInputMode": "rawJson",
"schemaJson": "{\"fields\":[{\"name\":\"full_name\",\"type\":\"TEXT\",\"description\":\"Candidate full name\"},{\"name\":\"email\",\"type\":\"EMAIL\",\"description\":\"Email address\"},{\"name\":\"phone\",\"type\":\"TEXT\",\"description\":\"Phone number\"},{\"name\":\"address\",\"type\":\"ADDRESS\",\"description\":\"Home address\"},{\"name\":\"job_title\",\"type\":\"TEXT\",\"description\":\"Most recent job title\"},{\"name\":\"employer\",\"type\":\"TEXT\",\"description\":\"Most recent employer\"},{\"name\":\"years_of_experience\",\"type\":\"INTEGER\",\"description\":\"Total years of professional experience\"},{\"name\":\"education\",\"type\":\"TEXT\",\"description\":\"Highest degree and institution\"},{\"name\":\"skills\",\"type\":\"TEXTAREA\",\"description\":\"Key skills listed on the resume\"}]}",
"files": {
"fileValues": [
{
"fileInputMode": "url",
"fileName": "resume-elena-vasquez.pdf",
"fileUrl": "https://example.com/resumes/elena-vasquez-2026.pdf"
}
]
}
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [500, 300],
"id": "e5f6a7b8-c9d0-1234-efab-234567890105",
"name": "Extract Resume Data",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
},
{
"parameters": {
"resource": "documentGeneration",
"format": "pdf",
"documentJson": "{\n \"metadata\": {\n \"title\": \"Employee Profile — {{ $json.full_name }}\",\n \"author\": \"Apex Staffing Solutions\"\n },\n \"page\": {\n \"size\": { \"preset\": \"A4\" },\n \"margins\": { \"top_in_pt\": 54, \"right_in_pt\": 54, \"bottom_in_pt\": 54, \"left_in_pt\": 54 }\n },\n \"content\": [\n { \"type\": \"headline\", \"level\": \"h1\", \"text\": \"Employee Profile\" },\n { \"type\": \"headline\", \"level\": \"h2\", \"text\": \"{{ $json.full_name }}\" },\n { \"type\": \"separator\" },\n { \"type\": \"table\", \"header\": { \"cells\": [{ \"text\": \"Field\" }, { \"text\": \"Details\" }] }, \"rows\": [{ \"cells\": [{ \"text\": \"Email\" }, { \"text\": \"{{ $json.email }}\" }] }, { \"cells\": [{ \"text\": \"Phone\" }, { \"text\": \"{{ $json.phone }}\" }] }, { \"cells\": [{ \"text\": \"Current Title\" }, { \"text\": \"{{ $json.job_title }}\" }] }, { \"cells\": [{ \"text\": \"Current Employer\" }, { \"text\": \"{{ $json.employer }}\" }] }, { \"cells\": [{ \"text\": \"Experience\" }, { \"text\": \"{{ $json.years_of_experience }} years\" }] }, { \"cells\": [{ \"text\": \"Education\" }, { \"text\": \"{{ $json.education }}\" }] }] },\n { \"type\": \"separator\" },\n { \"type\": \"headline\", \"level\": \"h3\", \"text\": \"Key Skills\" },\n { \"type\": \"paragraph\", \"runs\": [{ \"text\": \"{{ $json.skills }}\" }] },\n { \"type\": \"separator\" },\n { \"type\": \"paragraph\", \"runs\": [{ \"text\": \"Prepared by Apex Staffing Solutions — Confidential\" }] }\n ]\n}"
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [750, 300],
"id": "e5f6a7b8-c9d0-1234-efab-234567890106",
"name": "Generate Employee Profile",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Extract Resume Data",
"type": "main",
"index": 0
}
]
]
},
"Extract Resume Data": {
"main": [
[
{
"node": "Generate Employee Profile",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
Extract resume data from the file at [file URL], then generate an employee profile document. Use the extract_document tool with these fields:
- full_name (TEXT): Candidate full name
- email (EMAIL): Email address
- phone (TEXT): Phone number
- address (ADDRESS): Home address
- job_title (TEXT): Most recent job title
- employer (TEXT): Most recent employer
- years_of_experience (INTEGER): Total years of professional experience
- education (TEXT): Highest degree and institution
- skills (TEXTAREA): Key skills listed on the resume
Then use the generate_document tool to create a PDF employee profile with a summary table and skills section, branded for the staffing agency.
{
"success": true,
"data": {
"buffer": "JVBERi0xLjQ...",
"mime_type": "application/pdf"
}
}
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Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Compress an image to fit within a specific file size in bytes using quality-first compression.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Convert a contract PDF to clean markdown for clause extraction or LLM analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Convert external documents — specs, contracts, reports — to markdown for knowledge base ingestion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Convert a document to clean markdown suitable for chunking and embedding in a RAG pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Convert an image between PNG, JPEG, and WebP formats with quality control for web optimization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.