Workflow Templates

This workflow is aimed at generating keywords for SEO and articles To get started, you need to use the workflow as it is. You just call the webhook URL with a query parameter as q={{ $keywords}} For example, you can call it using ?q=keyword research This will give you a list of keywords back as an array. This system can be used by SEO pros, content marketers and also social media marketers to generate relevant keywords for their user needs

Overview This workflow implements a privacy-preserving AI document processing pipeline that detects, masks, and securely manages Personally Identifiable Information (PII) before any AI processing occurs. Organizations often need to analyze documents such as invoices, forms, contracts, or reports using AI. However, sending documents containing personal data directly to AI models can create serious privacy, compliance, and security risks. This workflow solves that problem by automatically detecting sensitive information, replacing it with secure tokens, and storing the original values in a protected vault database. Only the masked version of the document is sent to the AI model for analysis. If required, a controlled PII re-injection mechanism can restore original values after processing. The workflow also records all operations in an audit log, making it suitable for environments requiring strong compliance such as GDPR, financial services, healthcare, or enterprise document processing systems. How It Works 1. Document Upload A webhook receives a document (typically a PDF) and triggers the workflow. 2. OCR Text Extraction The OCR Extract node extracts the text content from the document so it can be analyzed for sensitive information. 3. PII Detection Multiple detectors analyze the text to identify different types of sensitive data: Email addresses (regex detection) Phone numbers (multi-pattern detection) Identification numbers such as PAN, SSN, or bank accounts Physical addresses detected using an AI model Each detection includes: detected value location in the text confidence score 4. Detection Consolidation All detected PII results are merged into a single dataset. The workflow resolves overlapping detections and removes duplicates to produce a clean list of sensitive values. 5. Tokenization and Secure Vault Storage Each detected PII value is replaced with a secure token, for example: <<EMAIL_7F3A>> <<PHONE_A12B>> The original values are securely stored in a Postgres vault table. This ensures sensitive data is never exposed to AI models. 6. Masked AI Processing The masked document is sent to an AI model for structured analysis. Possible AI tasks include: Document classification Data extraction Document summarization Entity extraction Since all sensitive data has been tokenized, the AI processes the document without seeing any real personal data. 7. Controlled PII Re-Injection After AI processing, the workflow can optionally restore original values from the vault. The Re-Injection Controller determines which fields are allowed to restore PII based on defined permissions. 8. Compliance Audit Logging All events are recorded in an audit table, including: PII detection token generation AI processing PII restoration This provides traceability and compliance reporting. Setup Instructions 1. Configure Postgres Database Create two tables in your database. PII Vault Table Example structure: token original_value type document_id created_at This table securely stores original PII values mapped to tokens. Audit Log Table Example structure: document_id pii_types_detected token_count ai_access_confirmed re_injection_events timestamp actor This table records workflow activity for compliance tracking. 2. Configure AI Model Credentials This workflow supports multiple AI models: Anthropic Claude (used for AI document processing) Ollama local models (used for address detection) Configure credentials in n8n before running the workflow. 3. Configure Webhook Trigger The workflow starts when a document is sent to the webhook: POST /webhook/gdpr-document-upload Upload a PDF file to this endpoint to trigger processing. 4. Configure Alert Notifications (Optional) Replace the placeholder alert webhook URL with your monitoring or alerting system. Example use cases: Slack alert monitoring system incident notification Alerts are triggered if masking fails. Use Cases This workflow is useful for many privacy-sensitive automation scenarios. GDPR-Compliant Document Processing Safely process documents containing personal data without exposing PII to AI models. AI-Powered Document Analysis Use AI to summarize or extract data from documents while maintaining privacy. Enterprise Data Redaction Pipelines Automatically detect and tokenize sensitive data before sending documents to downstream systems. Financial Document Processing Process invoices, contracts, and financial reports securely. Healthcare Document Automation Analyze patient documents while ensuring sensitive data is protected. Requirements To run this workflow you need: n8n** Postgres database** Anthropic Claude API access** Ollama (optional for local AI address detection)** Webhook endpoint for document uploads** Optional integrations: Monitoring or alert system Compliance audit database Key Features Automated PII detection and tokenization AI-safe document processing** Secure vault storage for sensitive data Controlled PII restoration Full audit logging Works with multiple AI models Designed for GDPR and enterprise compliance Summary This workflow creates a secure bridge between sensitive documents and AI systems. By automatically detecting, masking, and securely storing personal data, it enables organizations to safely apply AI to document processing tasks without exposing sensitive information. The combination of tokenization, secure vault storage, controlled re-injection, and audit logging makes this workflow suitable for privacy-sensitive industries and enterprise automation pipelines.

Quick overview This workflow runs nightly, reads today’s Amazon invoice URLs from Google Sheets, captures each invoice in an Airtop cloud browser, stores the screenshot in Google Drive, uses OpenAI to extract invoice fields from the image, and appends the structured results to a month-named sheet tab. How it works Runs every night on a schedule. Reads invoice-link rows from Google Sheets and keeps only rows whose Date value matches today. Processes invoices one at a time by opening each Invoice URL in an Airtop cloud browser session, zooming the page, and taking a screenshot. Finds the current month’s folder in Google Drive, uploads the screenshot, downloads it back, and builds shareable file and folder links. Uses OpenAI to read the invoice image and then converts the extracted content into strict structured JSON with an auto-fixing parser. Appends the extracted invoice fields and Google Drive links to a Google Sheets tab named for the current month, then closes the Airtop browser session. Setup Add credentials for Airtop, OpenAI, Google Sheets, and Google Drive. Update the Google Sheets document ID and ensure the source tab contains columns named “Invoice URL ” (including the trailing space) and “Date” formatted like “DD Mon YYYY” (en-GB). Set your Airtop browser profile name and make sure that profile is already logged into Amazon so the invoice pages can load. Set the Google Drive target drive/shared drive ID and create/find monthly folders named in the format YYYY-MM so the workflow can file invoices into the current month’s folder. Ensure your destination Google Sheet has (or can accept) the output columns used when appending to the month-named tab (for example Company Name, Invoice Number, taxes, totals, PDF URL, and Drive Link).

⚠️ Important: This workflow uses the Autype community node and requires a self-hosted n8n instance. Send an email with a document request and optional PDF attachments. The AI assistant can summarize documents, compare multiple PDFs, draft new content, or create documents from scratch with internet research — all output as professionally branded PDFs using Autype. The finished document is delivered back to the sender via email. Who is this for? Consultants, analysts, project managers, and teams who need on-demand document generation. Send an email and get a branded PDF back — whether it's a summary, comparison, draft, or a freshly researched document. Concrete example: Attach 3 PDF proposals and write "Compare these proposals and recommend the best option" — each PDF is OCR'd via Autype Lens, the AI assistant produces a structured comparison with tables, and you receive a branded PDF within minutes. This also works as an additional skill for an AI agent. Instead of an email trigger, connect the workflow to a webhook or chat trigger so an agent can call it when a user asks "create a summary of these documents." What this workflow does On each incoming email, the workflow: Extracts the email subject + body as the document request, and detects PDF attachments Processes each attached PDF sequentially: uploads to Autype, extracts text via Lens OCR Combines all OCR results into a single context Downloads the Autype Extended Markdown syntax reference so the AI knows the output format Passes the request text + all PDF content to an AI Document Assistant with Firecrawl and SerpAPI as research tools The assistant determines the task type (summarize, compare, draft, or create from scratch) and produces the document in Autype Extended Markdown Autype renders the markdown to a branded PDF with company styling (fonts, colors, heading styles, tables, header with logo, footer with page numbers) The PDF is delivered back to the original sender via email Output structure How it works New Email Received — An IMAP Email Trigger monitors your inbox for incoming document requests. The email subject and body become the request text; PDF attachments are automatically detected. Set Company Config — A Set node defines your company name, logo URL, and brand color. Edit these values once. Extract & Split PDFs — A Code node extracts the sender email, combines subject + body as request text, and detects PDF attachments. Each PDF is split into a separate item for loop processing. If no PDFs are attached, a single item with just the text is output. Has PDFs? — An IF node routes the flow: emails with PDF attachments enter the processing loop, text-only emails skip directly to the AI Assistant. Loop Over PDFs — A Split In Batches node processes each PDF sequentially (one at a time to avoid API rate limits). Upload PDF to Autype — Each PDF is uploaded to Autype via the community node (resource: file). Autype Lens OCR — An HTTP Request node triggers Autype Lens OCR on the uploaded file with outputFormat: "md". This uses Generic Auth Type → Header Auth with X-API-Key set to your Autype API key. Cost: 4 credits per page. A dedicated community node for Lens is planned. Wait for OCR → Poll OCR Status — Waits 8 seconds, then polls the job status via HTTP Request (same Header Auth credential). The loop continues to the next PDF after each OCR completes. Extract OCR Text — Extracts the markdown text from each OCR result and stores it with the original filename. Combine All OCR Results — After the loop completes, collects all OCR texts and combines them into a single context string with labeled sections per PDF. Prepare Text Only — For emails without PDFs, passes just the request text forward. Download Markdown Syntax — Fetches the Autype Extended Markdown syntax reference so the AI knows the output format. Merge Context — Combines the request text, all OCR content, and the markdown syntax reference into a single item for the AI Agent. AI Document Assistant — An n8n AI Agent (OpenRouter) with two tools: Firecrawl Scrape — Scrapes specific URLs to extract page content as markdown. SerpAPI — Web search for current information, statistics, and facts. The assistant determines the task type (summarize, compare, draft, or create from scratch). The system prompt limits tool usage to max 5 calls and prioritizes attached PDF content. Prepare Render Payload — Cleans the AI output (strips code fences), generates a filename, and prepares branding variables. Render Branded PDF — Autype Render from Markdown generates the PDF with a full defaults JSON for company styling: Roboto font, heading colors from brand color, styled tables with colored headers, header with company logo, and footer with page numbers. See the defaults schema for all options. Send Report via Email — SMTP sends the PDF as an attachment back to the original email sender. Setup Install the Autype community node (n8n-nodes-autype) via Settings > Community Nodes. Create an Autype API credential with your API key from app.autype.com. See API Keys in Settings. Create a Header Auth credential for the Lens OCR HTTP Request nodes: Go to Credentials > New > Header Auth Name: X-API-Key Value: your Autype API key (same key as step 2) Assign this credential to the "Autype Lens OCR" and "Poll OCR Status" nodes. Create an OpenRouter API credential (or replace the chat model with OpenAI/Anthropic). Create an IMAP credential for the email inbox to monitor. Create an SMTP credential for sending emails. Get a Firecrawl API key from firecrawl.dev and create a Firecrawl credential. Get a SerpAPI key from serpapi.com and create a SerpAPI credential. Import this workflow and assign your credentials to each node. Edit the Set Company Config node: companyName — Your company name (appears in header/footer) companyLogoUrl — URL to your company logo (PNG/JPEG, publicly accessible) brandColor — Hex color for headings and table headers (e.g. #1a5276) Update the Send Report via Email node with your sender email address. Activate the workflow — any new email to the monitored inbox triggers document generation. > Note: This is a community node. It is not maintained by the n8n team. You need a self-hosted n8n instance to use community nodes. Requirements Self-hosted n8n instance (community nodes are not available on n8n Cloud) Autype account with API key (Lens OCR costs 4 credits/page, Render from Markdown costs 1 credit) n8n-nodes-autype community node installed OpenRouter API key (or OpenAI/Anthropic — configurable chat model) IMAP credentials for the monitored inbox SMTP credentials for sending emails Firecrawl API key (free tier: 500 pages/month) SerpAPI key (serpapi.com) How to customize Change AI model:** Replace the OpenRouter Chat Model sub-node with OpenAI, Anthropic Claude, Google Gemini, or any LangChain-compatible chat model. Add more research tools:** Add additional tool nodes for specialized APIs — Google Scholar, SEC filings, PubMed, or internal knowledge bases. Customize styling:** Edit the defaults JSON in the Render Branded PDF node to change fonts, colors, heading styles, table designs, header/footer content, and spacing. See the defaults schema for all available options. Replace email trigger:** Swap the IMAP Email Trigger with a Form Trigger, Webhook, or Chat Trigger to accept input from different sources. Add watermark:** Insert an Autype Watermark step after rendering to stamp "DRAFT" or "CONFIDENTIAL" on every page. Save to cloud storage:** Add a Google Drive, S3, or SharePoint upload step after rendering (before or instead of SMTP). Adjust OCR wait time:** For large PDFs (10+ pages), increase the Wait node from 8 to 15-20 seconds, or add a retry loop that polls until status is COMPLETED. Use Autype community node for Lens:** Once the Autype community node adds Lens OCR support, replace the HTTP Request OCR/poll chain with a single Autype node. Change output format:** Switch from Render from Markdown to Render from JSON for a better manipulation experience

Quick overview This workflow turns an Upmeet meeting transcript or newly uploaded Google Drive audio/PDF discovery files into a validated consulting proposal by extracting BEBEDC fields with Google Gemini, selecting and pricing consultants and options from Google Sheets, and generating one Google Slides offer deck per recommended profile. How it works Receives a POST webhook from Upmeet or detects a new audio recording/PDF discovery file added to specific Google Drive folders. Downloads the new Drive file when applicable and uses Google Gemini to extract a structured BEBEDC-style client dossier as strict JSON. Normalizes and validates the extracted JSON dossier and stops the flow when the dossier cannot be parsed. Uses Google Gemini agents with Google Sheets tools to select matching consultant profiles and retrieve pricing from consultant, TJM (régie), forfait, and options tables. Builds a three-tier proposal (économique/intermédiaire/premium), then runs a separate Google Gemini quality check that flags blocking inconsistencies and triggers a remediation step to replace rejected profiles. For each resulting profile, copies a Google Slides template in Google Drive, replaces placeholders with client/profile/pricing content, inserts the consultant photo and pictograms, and loops to generate the next profile deck. Setup Create Google OAuth credentials for Google Drive, Google Slides, and Google Sheets, and add a Google Gemini (Google PaLM) API credential. Replace all REPLACE_WITH_* values with your Google Drive folder IDs (audio/PDF input and output), the Google Slides template ID, and the Google Sheets document IDs for profiles, TJM régie, forfait, and options. Ensure your Google Slides template contains the exact placeholders used in the workflow (for example {{ENTREPRISE}}, {{PROFIL}}, {{TJM_HT}}, {{PHOTO}}, {{PICTO1}}–{{PICTO4}}, {{BESOINS_CLIENT}}, {{SOLUTIONS_PROPOSEES}}). Copy the Upmeet webhook URL from the trigger and configure Upmeet to POST the meeting transcript payload to that endpoint (and adjust the mapping if your transcript field differs). Requirements Google Workspace (Drive, Sheets, Slides) + accès API Google Gemini Additional info Each full run of the workflow triggers several calls to the Gemini API (dossier extraction, consultant selection, options pricing, proposal generation, quality control, and possibly remediation), so plan your API quota accordingly. The workflow stops cleanly and routes to a dedicated node if the client dossier is unreadable, if no profile matches the needs, or if quality control rejects a proposal and no valid replacement can be found.

This workflow downloads all files from a specific folder in a S3 Bucket and compresses them so you can download it via n8n or do further processings. Fill in your Credentials and Settings in the Nodes marked with "*". Might serve well as Blueprint or as manual Download for S3 Folders. Since I found it rather tricky to compress all binary files into one zip file I figured might it be an interesting Template. Hint: This is the expression to get every binary key to compress them dynamically. (used in the "Compress"-Node) Enjoy the Workflow! ❤️ https://let-the-work-flow.com Workflow Automation & Development

This n8n workflow allows you to update user roles in Zammad based on data from an Excel file. The workflow automates role assignments, ensuring efficient and consistent updates. Features Excel Integration**: Import user data from an Excel file containing emails and role assignments. Dynamic Updates**: Match Zammad users by email and update their roles. Error Handling**: Continue workflow execution even if some updates fail. Customizable Variables**: Configure Zammad API URL, API key, and Excel file URL. Usage Import the Workflow: Upload the provided .json file into your n8n instance. Set Variables: zammad_base_url: Your Zammad instance URL. excel_source_url: URL of the Excel file containing user data. Authentication for Zammad Create in the Node "Find Zammad User by email" and "Update User Roles" a Header Auth Authentication Name**: Authorization Value**: Bearer <put here your zammad api token> Run the Workflow: Execute the workflow to update user roles based on the Excel data. Issues and Suggestions For issues or suggestions, visit the GitHub Repository.

Description This workflow automatically searches multiple flight booking websites to find the cheapest flights for your desired routes. It leverages web scraping to compare prices across platforms, helping you save money on air travel. Overview This workflow automatically searches multiple flight booking websites to find the cheapest flights for your desired routes. It uses Bright Data to scrape flight prices and can notify you when prices drop below your target threshold. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping flight prices from booking websites. Notification Services:** Email, SMS, or other messaging platforms. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Notifications: Configure your preferred notification method. Customize: Set your routes, date ranges, and price thresholds. Use Cases Frequent Travelers:** Find the best deals for your regular routes. Travel Agencies:** Monitor flight prices for client bookings. Budget Travelers:** Get notified when flights to your dream destination become affordable. Connect with Me YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #travel #flights #brightdata #dealalerts #webscraping #flightdeals #cheapflights #travelhacks #budgettravel #travelplanning #airfare #flightprices #travelautomation #n8nworkflow #workflow #nocode #traveltech #flightbooking #savemoney #traveltools #flightcomparison #bestflightdeals #travelsmarter #automatedtravel

Prunaai Hidream E1.1 Image Generator Description Edit an image with a prompt. This is the hidream-e1.1 model accelerated with the pruna optimisation engine. Overview This n8n workflow integrates with the Replicate API to use the prunaai/hidream-e1.1 model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Prompt Optional Parameters seed** (integer, default: -1): Random seed (-1 for random) image** (string, default: None): Input image to edit. speed_mode** (string, default: Juiced 🔥 (more speed)): Speed optimization level clip_cfg_norm** (boolean, default: True): Whether to use CLIP CFG normalization output_format** (string, default: webp): Output format guidance_scale** (number, default: 2.5): Guidance scale output_quality** (integer, default: 100): Output quality (for jpg and webp) refine_strength** (number, default: 0.3): Strength of refinement num_inference_steps** (integer, default: 28): Number of inference steps image_guidance_scale** (number, default: 1): Image guidance scale How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: prunaai/hidream-e1.1 API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters

Aihilums Sehatsanjha AI Generator Description None Overview This n8n workflow integrates with the Replicate API to use the aihilums/sehatsanjha model. This powerful AI model can generate high-quality other content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Optional Parameters cookie** (string, default: None): Cookie to be returned unchanged user_id** (string, default: ): Unique session identifier audio_file** (string, default: None): Audio file user_state** (string, default: None): User state end_session** (boolean, default: False): End the current recording new_session** (boolean, default: False): Start a new recording How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate other content Access the generated output from the final node API Reference Model: aihilums/sehatsanjha API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of other generation parameters

Description This workflow automatically monitors and tracks trending topics across multiple platforms and websites. It helps content creators and marketers stay ahead of the curve by identifying emerging trends before they go mainstream. Overview This workflow automatically monitors and tracks trending topics across multiple platforms and websites. It uses Bright Data to scrape trend data from social media, news sites, and other sources, then compiles the information into a structured format. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping trend data from various websites without getting blocked. Spreadsheets/Databases:** For storing and analyzing trend information. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Data Storage: Configure where you want to store the trend data. Customize: Specify which platforms to monitor and what topics to focus on. Use Cases Content Creators:** Stay on top of trending topics for content ideas. Marketers:** Identify emerging trends for timely campaigns. Researchers:** Track the evolution of topics and conversations over time. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #trends #trendtracking #brightdata #contentmarketing #trendanalysis #trendalerts #markettrends #trendmonitoring #n8nworkflow #workflow #nocode #trendresearch #emergingtrends #socialmediatrends #trendscraping #trenddata #contentideas #digitalmarketing #marketresearch #trendforecasting #trendspotting #dataanalysis #marketintelligence #trendautomation

Fire Part Crafter Image Generator Description PartCrafter is a structured 3D mesh generation model that creates multiple parts and objects from a single RGB image. Overview This n8n workflow integrates with the Replicate API to use the fire/part-crafter model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters image** (string): Input image for 3D mesh generation Optional Parameters seed** (integer, default: 0): Random seed for reproducibility. Use 0 for random seed num_parts** (integer, default: 16): Number of parts to generate num_tokens** (string, default: 2048): Number of tokens for generation guidance_scale** (number, default: 7): Guidance scale for generation remove_background** (boolean, default: False): Remove background from input image use_flash_decoder** (boolean, default: False): Use flash decoder for faster inference (Tempermental?) num_inference_steps** (integer, default: 50): Number of inference steps How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: fire/part-crafter API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters