Resize, sharpen, and compress an image to fit email platform size limits in a single pipeline.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate a branded PDF report with custom client logo placeholder, colors, and content sections for white-label agency delivery.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Agencies delivering reports under their clients' branding use this recipe to generate white-label PDF reports — with custom headers, color schemes, and content sections that match the client's visual identity.
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.
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": "Monthly Performance Report — March 2026",
"author": "Prepared by Northbridge Analytics"
},
"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": "Cedarwood Financial Group"
},
{
"type": "headline",
"level": "h2",
"text": "Monthly Performance Report — March 2026"
},
{
"type": "separator"
},
{
"type": "headline",
"level": "h3",
"text": "Portfolio Summary"
},
{
"type": "table",
"header": {
"cells": [
{
"text": "Metric"
},
{
"text": "Value"
}
]
},
"rows": [
{
"cells": [
{
"text": "Total AUM"
},
{
"text": "EUR 14,250,000"
}
]
},
{
"cells": [
{
"text": "Monthly Return"
},
{
"text": "+1.8%"
}
]
},
{
"cells": [
{
"text": "YTD Return"
},
{
"text": "+5.4%"
}
]
},
{
"cells": [
{
"text": "Benchmark (S&P 500 YTD)"
},
{
"text": "+4.9%"
}
]
},
{
"cells": [
{
"text": "Alpha"
},
{
"text": "+0.5%"
}
]
}
]
},
{
"type": "separator"
},
{
"type": "headline",
"level": "h3",
"text": "Asset Allocation"
},
{
"type": "table",
"header": {
"cells": [
{
"text": "Asset Class"
},
{
"text": "Allocation"
},
{
"text": "Value"
}
]
},
"rows": [
{
"cells": [
{
"text": "US Equities"
},
{
"text": "45%"
},
{
"text": "EUR 6,412,500"
}
]
},
{
"cells": [
{
"text": "International Equities"
},
{
"text": "20%"
},
{
"text": "EUR 2,850,000"
}
]
},
{
"cells": [
{
"text": "Fixed Income"
},
{
"text": "25%"
},
{
"text": "EUR 3,562,500"
}
]
},
{
"cells": [
{
"text": "Alternatives"
},
{
"text": "10%"
},
{
"text": "EUR 1,425,000"
}
]
}
]
},
{
"type": "separator"
},
{
"type": "headline",
"level": "h3",
"text": "Commentary"
},
{
"type": "paragraph",
"runs": [
{
"text": "The portfolio outperformed its benchmark by 50 basis points in March, driven by strong performance in the technology and healthcare sectors. Fixed income allocations provided stability amid rising rate expectations. We recommend maintaining the current allocation through Q2."
}
]
},
{
"type": "separator"
},
{
"type": "paragraph",
"runs": [
{
"text": "Confidential — Prepared for Cedarwood Financial Group by Northbridge Analytics. Not for redistribution."
}
]
}
]
}
}'
import { IterationLayer } from "iterationlayer";
const client = new IterationLayer({ apiKey: "YOUR_API_KEY" });
const report = await client.generateDocument({
format: "pdf",
document: {
metadata: { title: "Monthly Performance Report — March 2026", author: "Prepared by Northbridge Analytics" },
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: "Cedarwood Financial Group" },
{ type: "headline", level: "h2", text: "Monthly Performance Report — March 2026" },
{ type: "separator" },
{ type: "headline", level: "h3", text: "Portfolio Summary" },
{
type: "table",
header: { cells: [{ text: "Metric" }, { text: "Value" }] },
rows: [
{ cells: [{ text: "Total AUM" }, { text: "EUR 14,250,000" }] },
{ cells: [{ text: "Monthly Return" }, { text: "+1.8%" }] },
{ cells: [{ text: "YTD Return" }, { text: "+5.4%" }] },
{ cells: [{ text: "Benchmark (S&P 500 YTD)" }, { text: "+4.9%" }] },
{ cells: [{ text: "Alpha" }, { text: "+0.5%" }] },
],
},
{ type: "separator" },
{ type: "headline", level: "h3", text: "Asset Allocation" },
{
type: "table",
header: { cells: [{ text: "Asset Class" }, { text: "Allocation" }, { text: "Value" }] },
rows: [
{ cells: [{ text: "US Equities" }, { text: "45%" }, { text: "EUR 6,412,500" }] },
{ cells: [{ text: "International Equities" }, { text: "20%" }, { text: "EUR 2,850,000" }] },
{ cells: [{ text: "Fixed Income" }, { text: "25%" }, { text: "EUR 3,562,500" }] },
{ cells: [{ text: "Alternatives" }, { text: "10%" }, { text: "EUR 1,425,000" }] },
],
},
{ type: "separator" },
{ type: "headline", level: "h3", text: "Commentary" },
{ type: "paragraph", runs: [{ text: "The portfolio outperformed its benchmark by 50 basis points in March, driven by strong performance in the technology and healthcare sectors. Fixed income allocations provided stability amid rising rate expectations. We recommend maintaining the current allocation through Q2." }] },
{ type: "separator" },
{ type: "paragraph", runs: [{ text: "Confidential — Prepared for Cedarwood Financial Group by Northbridge Analytics." }] },
],
},
});
from iterationlayer import IterationLayer
client = IterationLayer(api_key="YOUR_API_KEY")
report = client.generate_document(
format="pdf",
document={
"metadata": {"title": "Monthly Performance Report — March 2026", "author": "Prepared by Northbridge Analytics"},
"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": "Cedarwood Financial Group"},
{"type": "headline", "level": "h2", "text": "Monthly Performance Report — March 2026"},
{"type": "separator"},
{"type": "headline", "level": "h3", "text": "Portfolio Summary"},
{
"type": "table",
"header": {"cells": [{"text": "Metric"}, {"text": "Value"}]},
"rows": [
{"cells": [{"text": "Total AUM"}, {"text": "EUR 14,250,000"}]},
{"cells": [{"text": "Monthly Return"}, {"text": "+1.8%"}]},
{"cells": [{"text": "YTD Return"}, {"text": "+5.4%"}]},
{"cells": [{"text": "Benchmark (S&P 500 YTD)"}, {"text": "+4.9%"}]},
{"cells": [{"text": "Alpha"}, {"text": "+0.5%"}]},
],
},
{"type": "separator"},
{"type": "headline", "level": "h3", "text": "Asset Allocation"},
{
"type": "table",
"header": {"cells": [{"text": "Asset Class"}, {"text": "Allocation"}, {"text": "Value"}]},
"rows": [
{"cells": [{"text": "US Equities"}, {"text": "45%"}, {"text": "EUR 6,412,500"}]},
{"cells": [{"text": "International Equities"}, {"text": "20%"}, {"text": "EUR 2,850,000"}]},
{"cells": [{"text": "Fixed Income"}, {"text": "25%"}, {"text": "EUR 3,562,500"}]},
{"cells": [{"text": "Alternatives"}, {"text": "10%"}, {"text": "EUR 1,425,000"}]},
],
},
{"type": "separator"},
{"type": "headline", "level": "h3", "text": "Commentary"},
{"type": "paragraph", "runs": [{"text": "The portfolio outperformed its benchmark by 50 basis points in March. We recommend maintaining the current allocation through Q2."}]},
{"type": "separator"},
{"type": "paragraph", "runs": [{"text": "Confidential — Prepared for Cedarwood Financial Group by Northbridge Analytics."}]},
],
},
)
package main
import il "github.com/iterationlayer/sdk-go"
func main() {
client := il.NewClient("YOUR_API_KEY")
_, err := client.GenerateDocument(il.GenerateDocumentRequest{
Format: "pdf",
Document: il.DocumentDefinition{
Metadata: il.DocumentMetadata{Title: "Monthly Performance Report — March 2026", Author: "Northbridge Analytics"},
Page: &il.DocumentPage{Size: il.DocPageSize{Preset: "A4"}, Margins: il.DocMargins{TopInPt: 54, RightInPt: 54, BottomInPt: 54, LeftInPt: 54}},
Content: []il.ContentBlock{
il.ContentBlock{"type": "headline", "level": "h1", "text": "Cedarwood Financial Group"},
il.ContentBlock{"type": "headline", "level": "h2", "text": "Monthly Performance Report — March 2026"},
il.ContentBlock{"type": "separator"},
il.ContentBlock{"type": "headline", "level": "h3", "text": "Portfolio Summary"},
il.ContentBlock{"type": "table", "header": map[string]any{"cells": []map[string]string{{"text": "Metric"}, {"text": "Value"}}}, "rows": []map[string]any{{"cells": []map[string]string{{"text": "Total AUM"}, {"text": "EUR 14,250,000"}}}, {"cells": []map[string]string{{"text": "Monthly Return"}, {"text": "+1.8%"}}}, {"cells": []map[string]string{{"text": "YTD Return"}, {"text": "+5.4%"}}}}},
il.ContentBlock{"type": "separator"},
il.ContentBlock{"type": "paragraph", "runs": []map[string]string{{"text": "Confidential — Prepared by Northbridge Analytics."}}},
},
},
})
if err != nil {
panic(err)
}
}
{
"name": "Generate white-label PDF report in Iteration Layer",
"nodes": [
{
"parameters": {
"content": "## Generate a White-Label PDF Report\n\nAgencies delivering reports under their clients' branding use this recipe to generate white-label PDF reports — with custom headers, color schemes, and content sections.\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": "d6e7f8a9-b0c1-2345-defa-345678901201",
"name": "Overview"
},
{
"parameters": {
"content": "### Step 1: Generate Report\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": [475, 100],
"id": "d6e7f8a9-b0c1-2345-defa-345678901202",
"name": "Step 1 Note"
},
{
"parameters": {},
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [250, 300],
"id": "d6e7f8a9-b0c1-2345-defa-345678901203",
"name": "Manual Trigger"
},
{
"parameters": {
"resource": "documentGeneration",
"format": "pdf",
"documentJson": "{\n \"metadata\": { \"title\": \"Monthly Performance Report — March 2026\", \"author\": \"Northbridge Analytics\" },\n \"page\": { \"size\": { \"preset\": \"A4\" }, \"margins\": { \"top_in_pt\": 54, \"right_in_pt\": 54, \"bottom_in_pt\": 54, \"left_in_pt\": 54 } },\n \"content\": [\n { \"type\": \"headline\", \"level\": \"h1\", \"text\": \"Cedarwood Financial Group\" },\n { \"type\": \"headline\", \"level\": \"h2\", \"text\": \"Monthly Performance Report — March 2026\" },\n { \"type\": \"separator\" },\n { \"type\": \"headline\", \"level\": \"h3\", \"text\": \"Portfolio Summary\" },\n { \"type\": \"table\", \"header\": { \"cells\": [{ \"text\": \"Metric\" }, { \"text\": \"Value\" }] }, \"rows\": [{ \"cells\": [{ \"text\": \"Total AUM\" }, { \"text\": \"EUR 14,250,000\" }] }, { \"cells\": [{ \"text\": \"Monthly Return\" }, { \"text\": \"+1.8%\" }] }] },\n { \"type\": \"separator\" },\n { \"type\": \"paragraph\", \"runs\": [{ \"text\": \"Confidential — Prepared by Northbridge Analytics.\" }] }\n ]\n}"
},
"type": "n8n-nodes-iterationlayer.iterationLayer",
"typeVersion": 1,
"position": [500, 300],
"id": "d6e7f8a9-b0c1-2345-defa-345678901204",
"name": "Generate Report",
"credentials": {
"iterationLayerApi": {
"id": "1",
"name": "Iteration Layer API"
}
}
}
],
"connections": {
"Manual Trigger": {
"main": [
[
{
"node": "Generate Report",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
Generate a white-label PDF report for [client name]. Use the generate_document tool to create an A4 PDF with:
- Client company name as the main heading
- Report title and period as a subheading
- A portfolio summary table with metrics (AUM, monthly return, YTD return, benchmark, alpha)
- An asset allocation table with asset classes, percentages, and values
- A commentary section with market analysis
- A confidentiality footer with the preparing agency name
{
"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.