How to Auto-Generate SWOT Analysis PDF Reports with n8n and AI

Writing a SWOT analysis takes hours — researching the market, consulting stakeholders, structuring the findings, and then wrestling with formatting in Word or Google Docs. If you’re a consultant, analyst, or business owner who produces these reports regularly, that time adds up fast. This n8n workflow replaces that process with four specialized AI agents that analyze Strengths, Weaknesses, Opportunities, and Threats in parallel, then stitch the results into a professionally formatted PDF and deliver it straight to your inbox.

Prefer to skip the setup? Grab the ready-made template → and be up and running in under 10 minutes.

What You’ll Build

  1. You add a company’s profile (name, industry, size, market region) to a Google Sheet — one row per company you want analyzed.
  2. You trigger the workflow with one click. Four AI agents instantly spin up in parallel and each writes a deep analysis of one SWOT quadrant.
  3. A fifth agent writes the introduction, a sixth writes the conclusion, and a seventh assembles the table of contents and title page.
  4. All sections are saved back to your Google Sheet as a structured record, then merged and sent to APITemplate.io to render a polished PDF.
  5. The finished PDF lands in your Gmail inbox, ready to share with a client or stakeholder — no manual formatting required.

How It Works — The Big Picture

The workflow reads a single row of company data from Google Sheets, fans out to four parallel analysis agents, formats each section, then reconverges to generate the PDF and send it by email. The entire flow runs sequentially where needed and in parallel where possible, keeping generation time to a minimum.

+-------------------------------------------------------------------------+
|  SWOT ANALYSIS PDF REPORT GENERATOR                                     |
|                                                                         |
|  [Manual Trigger]                                                       |
|       |                                                                 |
|  [Google Sheets -- Read Company Row]                                    |
|       |                                                                 |
|  [AI Agent -- SWOT Coordinator]  <-- OpenAI GPT-4                      |
|       |                                                                 |
|  +----+--------------------------------------+                          |
|  v          v           v           v                                   |
| [Strengths] [Weaknesses] [Opportunities] [Threats]  <- parallel agents |
|  v          v           v           v                                   |
| [Format S] [Format W]  [Format O]  [Format T]                          |
|  +----+--------------------------------------+                          |
|       v                                                                 |
|  [Merge All Sections]                                                   |
|       |                                                                 |
|  [Write Introduction]  [Write Conclusion]  [Title Page + ToC]          |
|       +----------------------------------+------------------+           |
|                             [Pull from Sheets]                          |
|                                  |                                      |
|                        [Combine All Content]                            |
|                                  |                                      |
|                    [Generate PDF via APITemplate.io]                    |
|                                  |                                      |
|                        [Download PDF File]                              |
|                                  |                                      |
|                      [Send Report via Gmail]                            |
+-------------------------------------------------------------------------+
  

What You’ll Need

  • n8n instance — self-hosted or n8n Cloud (v1.60+ recommended)
  • OpenAI API key — GPT-4 or GPT-4o access required
  • DeepSeek API key — used for the reasoning-heavy analysis phase (optional but improves depth)
  • Google Sheets — with OAuth2 connected to n8n; one sheet for input data, one for storing generated sections
  • APITemplate.io account — free plan works for testing; paid plan for production volume
  • Gmail account — connected to n8n via OAuth2 for report delivery

Estimated build time: 45-90 minutes from scratch, or under 10 minutes with the template.

Part 1 — Reading Company Data

1 Manual Trigger (Trigger)

This workflow starts manually — you click “Test workflow” (or call the workflow via another automation). The trigger passes no data; it simply kicks off the flow so the next node can read from your Google Sheet.

💡

Tip: You can easily swap this for a Schedule Trigger to run the analysis automatically every Monday morning, or a Webhook Trigger so an external system (like a CRM) can fire it on demand.

2 Google Sheets — Read Company Row

This node reads your input spreadsheet and pulls the company profile for analysis. Configure it to read a single row at a time — either the first row, or use a filter to target a specific company name.

{
  "Company Name": "Apex Logistics Inc.",
  "Industry": "Third-Party Logistics (3PL)",
  "Business Size": "Mid-market (250-500 employees)",
  "Market Region": "Southeast United States"
}
📌

Important: The column names in your sheet must exactly match what the AI agent nodes reference in their prompts. If you rename a column, update the corresponding agent prompt too.

Part 2 — Parallel SWOT Analysis

3 AI Agent — SWOT Coordinator

This central agent receives the full company profile and fans out to the four specialized analysis agents. It uses OpenAI GPT-4 and a Structured Output Parser to ensure the data passed downstream is consistently formatted.

{
  "companyName": "Apex Logistics Inc.",
  "industry": "Third-Party Logistics (3PL)",
  "businessSize": "Mid-market (250-500 employees)",
  "marketRegion": "Southeast United States",
  "analysisContext": "Focus on competitive landscape, operational efficiency, and regional market dynamics."
}

4 Strengths Analysis Agent

One of four parallel agents. This one is prompted to identify the company’s internal competitive advantages — things like proprietary technology, strong customer relationships, operational efficiencies, or brand recognition. It draws on the industry and business size context to make the analysis specific rather than generic.

{
  "section": "strengths",
  "points": [
    "Established network of 12 regional distribution centers across the Southeast",
    "Proprietary real-time shipment tracking system with 99.4% accuracy",
    "Long-term contracts with 3 of the top 10 US e-commerce retailers",
    "Low driver turnover rate (8%) compared to industry average (35%)"
  ],
  "summary": "Apex Logistics benefits from deep regional infrastructure and technology investments that create significant switching costs for key clients."
}
💡

Tip: All four analysis agents share the same OpenAI Chat Model node — n8n lets multiple agents reference one credential/model without duplicating the node. This keeps your workflow clean and makes it easy to swap models globally.

5 Weaknesses Analysis Agent

Prompts the model to think critically about internal limitations — gaps in technology, talent, financial resources, or operational coverage. The output mirrors the same JSON structure as the Strengths agent for easy merging downstream.

6 Opportunities Analysis Agent

Shifts focus externally: what market trends, regulatory changes, customer segments, or partnership opportunities could this company exploit? This agent benefits most from the “Market Region” field — it allows the AI to tailor its recommendations to specific geographic dynamics.

7 Threats Analysis Agent

Identifies external risks: new competitors, regulatory headwinds, supply chain vulnerabilities, macroeconomic factors. This agent uses the DeepSeek Reasoner model by default (you can configure it to use GPT-4) because threat analysis benefits from deeper causal reasoning.

Part 3 — Formatting and Assembly

8 Section Formatting Agents (x4)

After analysis, four formatting agents take each raw JSON section and convert it into polished prose — proper paragraphs, transitions, and a professional tone suitable for an executive report. Each formatting agent saves its output back to a dedicated Google Sheet tab, creating a persistent record of every analysis run.

{
  "section": "strengths",
  "formattedText": "Apex Logistics has built a formidable operational foundation across the Southeast United States. The company's network of 12 regional distribution centers ensures next-day delivery coverage for over 85% of the regional population -- a geographic footprint that would take years and significant capital for a new entrant to replicate.\n\nThe proprietary tracking system, developed in-house over six years, delivers 99.4% shipment accuracy and has become a key differentiator in contract renewals..."
}

9 Merge All SWOT Sections

The n8n Merge node waits for all four formatting branches to complete, then combines their outputs into a single item that flows forward. This is the synchronization point — nothing moves to the introduction or conclusion until all four SWOT sections are ready.

10 Write Introduction & Conclusion Agents

Two additional AI agents generate the bookends of the report. The introduction agent receives a summary of all four sections and writes a context-setting executive overview. The conclusion agent synthesizes the findings into strategic recommendations. Both use GPT-4o for speed.

11 Combine All Content (Code Node)

A JavaScript code node pulls all sections from Google Sheets (via several “Pull from Sheets” nodes), assembles them in the correct order — Title Page, ToC, Introduction, Strengths, Weaknesses, Opportunities, Threats, Conclusion — and formats the combined content into the JSON structure APITemplate.io expects.

// Combine all report sections in order
const sections = {
  titlePage: $('Extract Company Name').item.json.companyName,
  tableOfContents: $('Save Table of Contents to Sheets').item.json.tocContent,
  introduction: $('Upload Introduction').item.json.formattedText,
  strengths: $('Upload Strengths').item.json.formattedText,
  weaknesses: $('Upload Weaknesses').item.json.formattedText,
  opportunities: $('Upload Opportunities').item.json.formattedText,
  threats: $('Upload Threats').item.json.formattedText,
  conclusion: $('Upload Conclusion').item.json.formattedText
};

return [{ json: { reportData: sections, generatedAt: new Date().toISOString() } }];

Part 4 — PDF Generation and Delivery

12 Generate PDF via APITemplate.io

This HTTP Request node sends the assembled report data to APITemplate.io’s PDF generation API. APITemplate renders the content using a pre-built professional template (think letterhead, consistent typography, section dividers) and returns a download URL for the finished PDF.

💡

Tip: APITemplate.io lets you design your own PDF templates using a drag-and-drop editor. You can match the report to your brand colors, add a logo, and create custom section styles — all without touching CSS or LaTeX.

13 Download PDF & Send via Gmail

The Download PDF node fetches the binary file from APITemplate’s URL, and the Gmail node attaches it to an email addressed to the analyst or stakeholder. The subject line and body are dynamically populated with the company name and generation timestamp.

The Data Structure

Your Google Sheet needs two tabs: an Input tab (one row per company to analyze) and an Output tab (where generated sections are stored). The input schema is simple:

Column Type Example Description
Company Name Text Apex Logistics Inc. The full company name — used in the report title and throughout the analysis
Industry Text Third-Party Logistics (3PL) The industry sector — helps AI agents contextualize competitive dynamics
Business Size Text Mid-market (250-500 employees) Company size — affects which strengths/weaknesses are relevant
Market Region Text Southeast United States Geographic focus — used for market-specific opportunity and threat analysis
Status Text Pending / Completed Optional status field — useful if you process a queue of companies
📌

Column names must match exactly (including capitalization and spaces) — the AI agent prompts reference them by name using n8n expressions like {{ $json["Company Name"] }}.

Full System Flow

  Google Sheet (Input Tab)
         |
         v
  +------------------+
  |  Read Company    |  -> Company Name, Industry, Size, Region
  |  Profile         |
  +------------------+
         |
         v
  +----------------------------------------------------------+
  |              SWOT Coordinator Agent (GPT-4)              |
  +----------------------------------------------------------+
    |           |              |              |
    v           v              v              v
 [Strengths] [Weaknesses] [Opportunities] [Threats]
  (GPT-4)    (GPT-4)        (GPT-4)      (DeepSeek)
    |           |              |              |
    v           v              v              v
 [Format S] [Format W]   [Format O]    [Format T]
    |           |              |              |
    +-----------+-------+------+--------------+
                        v
                [Merge All Sections]
                        |
           +------------+------------+
           v            v            v
     [Introduction] [Conclusion] [Title + ToC]
           |            |            |
           +------------+----+-------+
                            v
              Google Sheets (Output Tab -- persist all sections)
                            |
                            v
                 [Combine All Content]
                            |
                            v
              [APITemplate.io -- Generate PDF]
                            |
                            v
                    [Download PDF]
                            |
                            v
              [Gmail -- Send Report to Inbox]
  

Testing Your Workflow

  1. Add one row to your Google Sheet with a real company you know well (e.g., a local business or well-known brand in your industry).
  2. Open the workflow in n8n and click Test workflow.
  3. Watch the execution — each agent node should light up green within 30-60 seconds as the AI generates content.
  4. Check your Google Sheets Output tab — you should see the formatted sections appear as the agents complete.
  5. After all nodes complete successfully, check your Gmail inbox for the PDF report.
Problem Likely Cause Fix
AI Agent node fails with 400 error OpenAI credential not configured or invalid API key Go to n8n Credentials → OpenAI → re-enter your API key and test connection
Google Sheets node returns empty data Spreadsheet ID or sheet name not updated after import Open the Google Sheets node, click the Spreadsheet URL field, and reselect your sheet
APITemplate.io returns 401 Unauthorized APITemplate API key missing or expired Log in to APITemplate.io → Account → API Keys → copy the key into n8n’s HTTP Request node header
Gmail node fails to send OAuth scope doesn’t include “Send email” Reconnect the Gmail credential in n8n and ensure “Compose and send” scope is granted
PDF is blank or missing sections One of the SWOT agents timed out or returned empty output Re-run the workflow; if it persists, add error handling (IF node) after each agent to catch empty responses

Frequently Asked Questions

Can I analyze multiple companies in one run?

The current template processes one company at a time to stay within OpenAI rate limits and keep execution predictable. To process a batch, add a Loop node before the Google Sheets read step and iterate through each row with a status of “Pending”. Update the status to “Completed” after the PDF is sent.

How much does this workflow cost to run per report?

Using GPT-4o for the four SWOT agents, introduction, conclusion, and table of contents, a single full report typically uses 8,000-14,000 tokens across all calls — roughly $0.08-$0.14 at current GPT-4o pricing. APITemplate.io’s free plan includes 50 PDF renders per month. So for moderate use, the ongoing cost is very low.

Can I use a different AI model instead of GPT-4?

Yes. Each AI Agent node lets you swap the connected language model independently. You can use GPT-4o mini for faster, cheaper runs, Claude via OpenRouter for a different analytical style, or Gemini if you prefer Google’s ecosystem. The Structured Output Parser will still enforce the expected JSON shape regardless of which model you use.

Does the workflow work on n8n Cloud, or only self-hosted?

It works on both n8n Cloud and self-hosted instances running n8n v1.60 or later. The only requirement is that your n8n instance can reach the OpenAI API, Google APIs, and APITemplate.io over HTTPS — which any standard deployment supports.

Can I customize the PDF template design?

Absolutely. Log in to APITemplate.io and open your template in the editor. You can change fonts, colors, add your company logo, modify section layouts, and add a cover page image. Once you save the template, the workflow will automatically use the updated design the next time it runs.

What if I don’t want to use APITemplate.io?

You have two alternatives: use the n8n HTML node to render the content as an HTML file and convert it with a headless Chrome service like Browserless, or export the sections to a Google Doc and use the Google Drive API to export it as PDF. The APITemplate.io approach is recommended because it requires no additional infrastructure and produces the most polished output.

🚀 Get the SWOT Analysis PDF Report Template

Skip the build — get the fully configured workflow JSON, a pre-built Google Sheets input template, and step-by-step setup and credentials guides so you’re generating professional SWOT reports in minutes.

Get the Template →

Instant download · Works on n8n Cloud and self-hosted · $14.99

What’s Next?

  • Competitor comparison mode: Analyze 3-5 competitors in one run and add a comparison table to the PDF showing how your company stacks up across each SWOT quadrant.
  • CRM integration: Trigger the workflow from HubSpot or Salesforce when a new prospect is added, and automatically attach the SWOT PDF to their contact record.
  • Slack/Teams delivery: Add a Slack or Teams node after the Gmail step to post a summary of the key findings to a team channel as soon as the report is ready.
  • Scheduled competitive intelligence: Run the workflow monthly on your key accounts to track how their SWOT profile evolves over time, building a longitudinal record in Google Sheets.
n8n
OpenAI
Google Sheets
APITemplate.io
SWOT Analysis
PDF Report
AI Agents
Business Automation

How to Auto-Extract Invoice Data from PDF with AI Using n8n

Every month, the same grind: open an email, download the PDF, squint at the invoice number, manually type the amount into a spreadsheet, and pray you didn’t transpose a digit. If your business processes more than a handful of invoices per week, that manual routine is silently eating hours you could spend on work that actually matters. What if every PDF invoice that landed in your inbox was automatically read, parsed, and filed into a clean database — without you touching it once?

That’s exactly what you’ll build in this guide. Using n8n, OpenAI’s GPT-4o mini, and Airtable, you’ll create a workflow that watches your Gmail inbox for invoice emails, extracts text from attached PDFs, sends that text to AI for structured parsing, and logs every field — vendor name, invoice number, amounts, line items, due dates — into an Airtable base. The whole thing runs on autopilot every 30 minutes.

Prefer to skip the setup? Grab the ready-made template → and be up and running in under 10 minutes.

What You’ll Build

  1. A schedule trigger checks your Gmail inbox every 30 minutes for unread emails with PDF attachments matching invoice-related subjects.
  2. The workflow downloads the PDF, extracts raw text, and sends it to OpenAI with a carefully tuned prompt that returns structured JSON — vendor name, invoice number, dates, amounts, line items, and payment status.
  3. A Code node validates and formats the AI output, then pushes a clean record into your Airtable base with 13 fields covering every detail you’d normally type by hand.
  4. The source email is marked as read so it won’t be processed twice.

How It Works — The Big Picture

The workflow runs as a single linear pipeline with one conditional branch. Emails without PDF attachments are silently skipped, while PDFs flow through extraction, AI parsing, and database logging.

┌──────────────────────────────────────────────────────────────────────────┐
│  INVOICE DATA EXTRACTOR — AI POWERED                                     │
│                                                                          │
│  [Schedule]  →  [Gmail: Fetch]  →  [IF: Has PDF?]                       │
│                                         │ Yes          │ No              │
│                                         ↓              ↓                │
│                                  [Extract PDF]    [Skip]                │
│                                         ↓                               │
│                                  [OpenAI: Parse]                        │
│                                         ↓                               │
│                                  [Code: Format]                         │
│                                         ↓                               │
│                                  [Airtable: Save]                       │
│                                         ↓                               │
│                                  [Gmail: Mark Read]                     │
└──────────────────────────────────────────────────────────────────────────┘
  

What You’ll Need

  • n8n — self-hosted or cloud (version 1.0 or higher)
  • Gmail account — with OAuth2 credentials configured in n8n
  • OpenAI API key — with access to the gpt-4o-mini model (or gpt-4o for higher accuracy on complex invoices)
  • Airtable account — free tier works fine; you’ll need one base with a table matching the schema below

Estimated build time: 30–45 minutes from scratch, or under 10 minutes with the template.

Building the Workflow

1 Check Inbox Every 30 Minutes (Schedule Trigger)

This node kicks off the workflow on a regular interval. Open n8n, create a new workflow, and add a Schedule Trigger node. Set it to run every 30 minutes. You can adjust this later — every 15 minutes if you process high volumes, or once per hour if invoices trickle in slowly.

💡

Tip: During testing, switch this to “manual” execution so you can trigger runs on demand without waiting for the timer.

2 Fetch Unread Invoice Emails (Gmail)

Add a Gmail node and set the operation to Get Many. This node searches your inbox for unread emails that have PDF attachments and match invoice-related subject lines. Configure it as follows:

  • Limit: 10 (processes up to 10 emails per run)
  • Search query: has:attachment filename:pdf is:unread subject:(invoice OR receipt OR bill)
  • Download Attachments: Enabled, with prefix attachment_

The search query is the key here — it filters for only unread emails containing a PDF file whose subject mentions “invoice,” “receipt,” or “bill.” You can customize these keywords to match the vocabulary your vendors use.

{
  "id": "18e3a5b7c9d2f100",
  "subject": "Invoice #INV-2026-0847 from Acme Supplies",
  "from": { "emailAddress": "billing@acmesupplies.com" },
  "attachment_0": {
    "fileName": "INV-2026-0847.pdf",
    "mimeType": "application/pdf"
  }
}
💡

Tip: If you receive invoices from specific vendors, tighten the query with from:billing@vendor.com to avoid picking up random PDFs like flight confirmations.

3 Has PDF Attachment? (IF Node)

Add an IF node to verify that the attachment is actually a PDF. Check that attachment_0.mimeType equals application/pdf. Emails that pass go to the extraction step. Emails that fail (wrong attachment type, or the attachment was an image) are routed to a No Operation node and silently skipped.

📌

This guard prevents errors downstream. Some emails match the search query but attach Excel files or images instead of PDFs — the IF node filters those out cleanly.

4 Extract Text from PDF (Extract From File)

Add an Extract From File node. Set the operation to PDF and the binary property name to attachment_0 (matching the prefix you set in the Gmail node). This node converts the PDF binary data into raw text that the AI can read.

After this node runs, the output looks like this:

{
  "data": "INVOICE\nAcme Supplies Inc.\n742 Evergreen Terrace\nSpringfield, IL 62704\n\nBill To: Carter & Associates LLC\nInvoice #: INV-2026-0847\nDate: March 28, 2026\nDue Date: April 27, 2026\n\nDescription          Qty    Price     Amount\nConsulting Services    40   $150.00   $6,000.00\nSoftware License        1   $499.00     $499.00\n\nSubtotal: $6,499.00\nTax (8.25%): $536.17\nTotal: $7,035.17\n\nPayment Terms: Net 30"
}
💡

Tip: The Extract From File node works well with text-based PDFs. If your invoices are scanned images (no selectable text), you’ll need to add an OCR step before this node — tools like Google Cloud Vision or AWS Textract can handle that.

5 Parse Invoice with AI (OpenAI)

This is where the magic happens. Add an OpenAI node configured for the Chat resource. Set the model to gpt-4o-mini (fast, cheap, and surprisingly accurate for structured extraction) and the temperature to 0.1 (low randomness = consistent output).

The prompt instructs the AI to return a strict JSON object with 12 fields covering every piece of data you’d want from an invoice. Here’s what the prompt asks for:

Field Type Example
vendor_name String Acme Supplies Inc.
vendor_address String 742 Evergreen Terrace, Springfield, IL 62704
invoice_number String INV-2026-0847
invoice_date Date 2026-03-28
due_date Date 2026-04-27
subtotal Number 6499.00
tax_amount Number 536.17
total_amount Number 7035.17
currency String USD
payment_status String unpaid
line_items Array [{description, qty, unit_price, amount}]
notes String Payment Terms: Net 30
💡

Tip: For invoices with complex layouts or non-English text, switch the model to gpt-4o. It costs a bit more per call but handles edge cases much better. At typical invoice lengths (under 1,000 tokens), even gpt-4o costs less than a penny per invoice.

6 Format Extracted Data (Code Node)

The AI returns a JSON string inside its message content. This Code node does three things: extracts the JSON from the response (handling cases where the AI wraps it in markdown code blocks), validates each field with fallback defaults, and formats the line items array into a human-readable string for Airtable’s long text field.

The node also carries forward metadata from the original email — the subject line and sender address — so you always know where each invoice came from.

{
  "vendor_name": "Acme Supplies Inc.",
  "invoice_number": "INV-2026-0847",
  "invoice_date": "2026-03-28",
  "due_date": "2026-04-27",
  "subtotal": 6499.00,
  "tax_amount": 536.17,
  "total_amount": 7035.17,
  "currency": "USD",
  "payment_status": "unpaid",
  "line_items_text": "1. Consulting Services — Qty: 40 × $150 = $6000\n2. Software License — Qty: 1 × $499 = $499",
  "notes": "Payment Terms: Net 30",
  "source_email_from": "billing@acmesupplies.com",
  "processed_at": "2026-04-08T14:30:00.000Z"
}

7 Save to Airtable

Add an Airtable node set to the Create operation. Point it at your base and table, then map each field from the Code node output to the corresponding Airtable column. The mapping uses n8n expressions like ={{ $json.vendor_name }} to pull values dynamically.

Every processed invoice becomes a new row in your Airtable base — fully structured, searchable, and ready for reporting.

📌

Make sure your Airtable column names match exactly — including capitalization and spaces. “Invoice Number” is not the same as “invoice_number” in Airtable.

8 Mark Email as Read (Gmail)

The final node marks the original email as read so it won’t be picked up again on the next run. It references the email ID from the “Fetch Unread Invoice Emails” node using the expression ={{ $('Fetch Unread Invoice Emails').item.json.id }}.

💡

Tip: Want extra safety? Add a Gmail “Add Label” step before this one to move processed emails into a “Processed Invoices” label. That gives you an audit trail even if something goes wrong with Airtable.

The Data Structure

Before activating the workflow, create an Airtable base called “Invoice Tracker” with a single table named “Invoices” using this schema:

Column Type Example Description
Vendor Name Single line text Acme Supplies Inc. Company that issued the invoice
Invoice Number Single line text INV-2026-0847 Unique invoice identifier
Invoice Date Date 2026-03-28 Date the invoice was issued
Due Date Date 2026-04-27 Payment deadline
Subtotal Currency $6,499.00 Amount before tax
Tax Currency $536.17 Tax amount
Total Amount Currency $7,035.17 Final amount due
Currency Single line text USD Currency code
Payment Status Single select unpaid Options: paid, unpaid, unknown
Line Items Long text 1. Consulting — 40 × $150 Formatted breakdown of charges
Notes Long text Net 30 Payment terms, PO numbers, etc.
Source Email Email billing@acmesupplies.com Sender of the original email
Processed At Date 2026-04-08 Timestamp when the workflow ran
📌

Column names must match the mapping in the Airtable node exactly. The easiest way: duplicate the table from the template’s included Airtable CSV, or create columns one by one following this schema.

Full System Flow

┌──────────────────────────────────────────────────────────────────────────────┐
│                                                                              │
│   GMAIL INBOX                          AIRTABLE                             │
│   ┌──────────────┐                     ┌──────────────────┐                 │
│   │ Unread email  │                     │ Invoice Tracker   │                │
│   │ + PDF attach  │                     │ ┌──────────────┐ │                │
│   └──────┬───────┘                     │ │ Vendor: Acme │ │                │
│          ↓                             │ │ #INV-0847    │ │                │
│   [Schedule: 30 min]                   │ │ $7,035.17    │ │                │
│          ↓                             │ └──────────────┘ │                │
│   [Gmail: Fetch unread]                 └────────▲─────────┘                │
│          ↓                                       │                          │
│   [IF: Has PDF?]──No──→ [Skip]                   │                          │
│          │ Yes                                   │                          │
│          ↓                                      │                          │
│   [Extract PDF Text]                            │                          │
│          ↓                                      │                          │
│   [OpenAI: Parse JSON]                          │                          │
│          ↓                                      │                          │
│   [Code: Format Data]──────────────────────────→┘                          │
│          ↓                                                                 │
│   [Gmail: Mark Read]                                                       │
│                                                                              │
└──────────────────────────────────────────────────────────────────────────────┘
  

Testing Your Workflow

  1. Send yourself a test email with a sample PDF invoice attached. Use a subject line like “Invoice #TEST-001 from Test Vendor” so it matches the search query.
  2. In n8n, click Test Workflow (the play button) to trigger a manual run.
  3. Watch the execution — each node should show a green checkmark. Click any node to inspect its output data.
  4. Check your Airtable base. You should see a new row with all 13 fields populated from the test invoice.
  5. Verify the original email is now marked as read in Gmail.
Problem Likely Cause Fix
Gmail node returns 0 items No unread emails match the search query Send a test email with “invoice” in the subject and a PDF attached, then wait a moment for Gmail to index it
Extract From File returns empty text The PDF is a scanned image, not text-based Add an OCR step (Google Cloud Vision or AWS Textract) before the extraction node
OpenAI returns malformed JSON Invoice text was too garbled or incomplete Check the extracted text — if it’s unreadable, the source PDF may need OCR. Also try switching to gpt-4o for better handling
Airtable node fails with “field not found” Column name mismatch between n8n mapping and Airtable Compare column names character by character — watch for extra spaces, capitalization differences, or missing columns
Same invoice processed twice Mark as Read step failed or email wasn’t marked before the next scheduled run Check the Gmail node credentials have write permissions. Consider adding a label-based filter as a secondary guard

Frequently Asked Questions

How much does each invoice cost to process with OpenAI?

Very little. A typical invoice is 300–800 tokens of input text. With GPT-4o mini at $0.15 per million input tokens, processing one invoice costs roughly $0.0001 — less than a hundredth of a penny. Even at 1,000 invoices per month, your OpenAI bill would be under $0.50.

Does this work with scanned PDF invoices (images, not text)?

The Extract From File node handles text-based PDFs natively. For scanned invoices where the text is embedded in an image, you’ll need to add an OCR step before extraction. Google Cloud Vision, AWS Textract, or the n8n HTTP Request node calling an OCR API all work. The rest of the workflow stays the same.

Can I use Google Sheets instead of Airtable?

Yes. Replace the Airtable node with a Google Sheets “Append Row” node and map the same fields to spreadsheet columns. The rest of the workflow doesn’t need any changes. Airtable gives you richer field types (currency, single select, date pickers), but Sheets is perfectly functional.

What if I use Outlook instead of Gmail?

Swap the two Gmail nodes for their Microsoft Outlook equivalents — “Microsoft Outlook Trigger” for fetching emails and “Microsoft Outlook” for marking as read. The search query syntax differs slightly, but the concept is identical. Update the credential type in n8n accordingly.

Can the workflow handle invoices in languages other than English?

GPT-4o mini handles most major languages well. The prompt asks for specific JSON field names in English, but the AI will extract data from French, Spanish, German, and many other languages and map it into the English schema. For best results with non-Latin scripts, consider upgrading to GPT-4o.

What happens if two invoices arrive in the same email?

The current workflow processes the first PDF attachment per email. If a sender regularly attaches multiple PDFs to one email, you can modify the workflow to loop through all attachments by adding a “Split In Batches” node after the IF check and adjusting the binary property name dynamically.

Get the Invoice Data Extractor Template

Stop building from scratch — get the complete workflow JSON, Airtable schema, and step-by-step setup guides. Import it, add your credentials, and start processing invoices in under 10 minutes.

Get the Template →

Instant download · Works on n8n Cloud and self-hosted

What’s Next?

  • Add Slack notifications — send a message to your #accounting channel whenever a high-value invoice (over $5,000) is processed.
  • Auto-flag overdue invoices — add a second scheduled workflow that checks Airtable daily and flags rows where the due date has passed and payment status is still “unpaid.”
  • Build a payment approval flow — route invoices above a threshold to a manager via email for approval before marking them as “approved” in Airtable.
  • Connect to accounting software — push the structured data into QuickBooks, Xero, or FreshBooks via their APIs to eliminate double entry entirely.
n8n
PDF
OpenAI
Airtable
invoice processing
automation
AI
accounts payable