Workflow Templates

Who is this template for? Growth teams, SDRs, recruiters, or anyone who routinely hunts for hard‑to‑find business emails and would rather spend time reaching out than guessing formats. What problem does this workflow solve? Manually piecing together email patterns, cross‑checking them in a verifier, and updating a tracking sheet is slow and error‑prone. This template automates the entire loop—research, guess, verify, and log—so you hit Start and watch rows fill up with ready‑to‑send addresses. What this workflow does Pull fresh leads – Grabs only the rows in your Google Sheet where Status = FALSE. Find the company pattern – Queries Serper.dev for snippets and feeds them to Gemini Flash (via OpenRouter) to spot the dominant email format. Build the address – Constructs a likely email for every first/last name. Verify in real time – Pings Prospeo by default (API) or lets you bulk‑clean in Sparkle.io. Write it back – Updates the sheet with pattern, email, confidence, verification status, and flips Status to TRUE. Loop until done – Runs batch‑by‑batch so you never hit API limits. 🆓 Work free‑tier magic (up to \~2,500 contacts/month) | Service | Free allowance | How this template uses it | | -------------- | ----------------------------- | ------------------------------------------------------------------------------------ | | Serper.dev | 2,500 searches/mo | Scrapes three public email snippets per domain to learn the pattern | | Sparkle.io | 10,000 bulk verifications/day | Manual upload‑download option—perfect to clean your first 2.5k emails at zero cost | | Prospeo | 75 API calls/mo | Built‑in if you prefer fully automated verification | Quick Sparkle workflow: Let the template generate emails. Export the “Email” column to CSV → upload to Sparkle.io. Download the results and paste the "verification\_status" back into the sheet (or add a small n8n import sub‑flow). Setup (5 minutes) Copy the Google Sheet linked in the sticky note and paste its ID into the Get Rows and Update Rows nodes. Add credentials for Google Sheets, Serper (X‑API‑KEY), OpenRouter, and optionally Prospeo. Hit Execute Workflow—that’s it. How to customise Prefer Sparkle for volume:** Skip the Prospeo node, export emails in one click, bulk‑verify in Sparkle, and re‑import results. Swap the search source:* Replace the *Get Email Pattern HTTP node with Bing, Brave, etc. Extend enrichment:* Add phone look‑ups or LinkedIn scrapers before the *Update Rows node. Auto‑run:** Replace the Manual Trigger with a Cron node so the sheet cleans itself every morning. Additional resources | Tool | Purpose | Link | | --------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------- | -------------------------------------------------------- | | Prospeo – API‑ready email verificationSpecial offer: 20 % free credits for the first 3 months on any plan using this link! | Real‑time, single‑call mailbox validation | prospeo.io | | Sparkle.io – high‑volume bulk verifier (manual upload) | Free daily quota of 10 000 verifications | app.sparkle.io/sign‑up | | OpenRouter – API gateway for Gemini Flash & other LLMs | One key unlocks multiple frontier models | openrouter.ai | | Serper.dev – Google Search API | 2 500 searches/month on the free tier | serper.dev | Add the relevant keys or signup details from these links, drop them into the matching n8n credentials, and you’re all set to enrich your first 2 500 contacts at zero cost. Happy building!

5 nodes760 views

Automatically Create Linear Issues from Gmail Support Request Messages

by Jimleuk

This n8n template watches a Gmail inbox for support messages and creates an equivalent issue item in Linear. How it works A scheduled trigger fetches recent Gmail messages from the inbox which collects support requests. These support requests are filtered to ensure they are only processed once and their HTML body is converted to markdown for easier parsing. Each support request is then triaged via an AI Agent which adds appropriate labels, assesses priority and summarises a title and description of the original request. Finally, the AI generated values are used to create an issue in Linear to be actioned. How to use Ensure the messages fetched are solely support requests otherwise you'll need to classify messages before processing them. Specify the labels and priorities to use in the system prompt of the AI agent. Requirements Gmail for incoming support messages OpenAI for LLM Linear for issue management Customising this workflow Consider automating more steps after the issue is created such as attempting issue resolution or capacity planning.

🤖AI & Machine Learning

5 nodes568 views

AI Research Assistant via Telegram (GPT-4o mini + DeepSeek R1 + SerpAPI)

by Arlin Perez

AI Research Assistant via Telegram (GPT-4o mini + DeepSeek R1 + SerpAPI) 👥 Who’s it for This workflow is perfect for anyone who wants to receive AI-powered research summaries directly on Telegram. Ideal for people asking frequent product, tech, or decision-making questions and want up-to-date answers sourced from the web. 🤖 What it does Users send a question via Telegram. An AI agent (DeepSeek R1) reformulates and understands the intent, while a second agent (GPT-4o mini) performs live research using SerpAPI. The most relevant answers, including links and images, are delivered back via Telegram. ⚙️ How it works 📲 Telegram Trigger – Starts when a user sends a message to your Telegram bot. 🧠 DeepSeek R1 Agent – Understands, clarifies, or reformulates the user query. 🧠 Research AI Agent (GPT-4o mini + SerpAPI) – Searches the web and summarizes the best results. 📤 Send Telegram Message – Sends the response back to the same user. 📋 Requirements Telegram bot (via BotFather) with API token set in n8n credentials OpenAI account with API key and balance for GPT-4o mini SerpAPI account (100 free searches/month) with API key DeepSeek account with API key and balance 🛠️ How to set up Create your Telegram bot using BotFather and connect it using the Telegram Trigger node Set up DeepSeek credentials and add a Chat Model AI Agent node using DeepSeek R1 to reformulate the user’s question Set up OpenAI credentials and add a second ChatGPT AI Agent node using GPT-4o mini In the GPT-4o node, enable the SerpAPI Tool and add your SerpAPI API key Pass the reformulated question from DeepSeek to the GPT-4o agent for live search and summarization Format the response (text, links, optional images) Send the final reply to the user using the Telegram Send Message node Ensure your n8n instance is publicly accessible Test the workflow by sending a message to your Telegram bot ✅

🤖AI & Machine Learning

6 nodes30 views

Automatic Subscriber Creation in Beehiiv from Systeme.io Funnel Optins

by Vincent Belmehel

Purpose This workflow automatically creates a subscriber in a given Beehiiv publication when a new opt-in is registered in a given Systeme.io sales funnel. Good to know: the integration with Systeme.io is done at the sales funnel level, not at the account level. If you have several sales funnels, you can use the same workflow several times. Quick Setup Configure your sales funnel in Systeme.io to create and trigger a webhook after an opt-in Open the “On New Systeme.io Optin” node to find the webhook URL needed to configure your sales funnel on Systeme.io Configure the “Configure Workflow” node Add your Beehiiv publication ID If you know the subscriber's first and last name and want to send it to Beehiiv, configure the custom field names for first and last name Add one or more email addresses to which to send alert notifications in the event of a problem (separated by commas). If you have not already done so : Connect your Beehiiv account in the “Create New Beehiiv Subscriber” node Connect your Gmail account in the “Send Email Alert (Beehiiv API error)” node How It Works As soon as a new opt-in is registered on your sales funnel, Systeme.io triggers the workflow (via a webhook) Only requests actually coming from Systeme.io are considered (whitelisting of their IP addresses for security reasons) A new subscriber is added to your Beehiiv publication (via an API call) If available in Systeme.io, UTM tags (utm_source, utm_medium and utm_campaign) are transferred to Beehiiv to correctly track where your subscribers are coming from If an error occurs during the Beehiiv API call, an alert notification is sent to you (via email) Requirements A Systeme.io account A Beehiiv account with an active publication A Gmail account Benefits Automate & scale your email marketing efforts seamlessly No more manual tasks to keep your subscriber list always up-to-date Focus on creating a newsletter that stands out, not on the technical side Check Out My Other Templates 👉 https://n8n.io/creators/belmehel/

2 nodes

Transcribing Bank Statements To Markdown Using Gemini Vision AI

by Jimleuk

This n8n workflow demonstrates an approach to parsing bank statement PDFs with multimodal LLMs as an alternative to traditional OCR. This allows for much more accurate data extraction from the document especially when it comes to tables and complex layouts. Multimodal Parsing is better than traditiona OCR because: It reduces complexity and overhead by avoiding the need to preprocess the document into text format such as markdown before passing to the LLM. It handles non-standard PDF formats which may produce garbled output via traditional OCR text conversion. It's orders of magnitude cheaper than premium OCR models that still require post-processing cleanup and formatting. LLMs can format to any schema or language you desire! How it works You can use the example bank statement created specifically for this workflow here: https://drive.google.com/file/d/1wS9U7MQDthj57CvEcqG_Llkr-ek6RqGA/view?usp=sharing A PDF bank statement is imported via Google Drive. For this demo, I've created a mock bank statement which includes complex table layouts of 5 columns. Typically, OCR will be unable to align the columns correctly and mistake some deposits for withdrawals. Because multimodal LLMs do not accept PDFs directly, well have to convert the PDF to a series of images. We can achieve this by using a tool such as Stirling PDF. Stirling PDF is self-hostable which is handy for sensitive data such as bank statements. Stirling PDF will return our PDF as a series of JPGs (one for each page) in a zipped file. We can use n8n's decompress node to extract the images and ensure they are ordered by using the Sort node. Next, we'll resize each page using the Edit Image node to ensure the right balance between resolution limits and processing speed. Each resized page image is then passed into the Basic LLM node which will use our multimodal LLM of choice - Gemini 1.5 Pro. In the LLM node's options, we'll add a "user message" of type binary (data) which is how we add our image data as an input. Our prompt will instruct the multimodal LLM to transcribe each page to markdown. Note, you do not need to do this - you can just ask for data points to extract directly! Our goal for this template is to demonstrate the LLMs ability to accurately read the page. Finally, with our markdown version of all pages, we can pass this to another LLM node to extract required data such as deposit line items. Requirements Google Gemini API for Multimodal LLM. Google Drive access for document storage. Stirling PDF instance for PDF to Image conversion Customising the workflow At time of writing, Gemini 1.5 Pro is the most accurate in text document parsing with a relatively low cost. If you are not using Google Gemini however you can switch to other multimodal LLMs such as OpenAI GPT or Antrophic Claude. If you don't need the markdown, simply asking what to extract directly in the LLM's prompt is also acceptable and would save a few extra steps. Not parsing any bank statements any time soon? This template also works for Invoices, inventory lists, contracts, legal documents etc.

Daily Google Search Console SEO Pulse: Catch Top Movers Across Keyword Segments

by MattF

This workflow helps SEO teams catch top movers in Google Search Console by comparing daily performance across keyword segments like brand, nonbrand, and content categories. Instead of serving as a routine check, it highlights the queries and pages with the biggest jumps or drops, making it ideal for spotting wins, losses, or unexpected shifts early. How It Works Runs daily on a scheduled trigger (e.g. every morning). Pulls GSC data for the prior two days (e.g. yesterday vs. day before). Segments traffic by keyword type or URL pattern (e.g. brand, nonbrand, recipes, blogs, etc.). Calculates changes in clicks, impressions, CTR, and average position. Flags top movers with the biggest positive or negative deltas. Sends structured reports via Slack or email, grouped by segment and sorted by impact. Setup Steps Connect your Google Search Console account and optionally Gmail or Slack. Swap in your own domain(s) and customize segmentation logic (e.g. brand terms, path filters). By default, the workflow includes Slack alerts, but these can be easily switched to or combined with email, webhook, or other channels. Full setup takes around 15–20 minutes with working GSC credentials. Note: The “recipes” segment is included as an example of how to segment content. This can be changed to match blog, FAQ, product pages, or any other category.

3 nodes

Personalized Tour Package Recommendations with GPT-4o, Pinecone & Lovable UI

by Mohan Gopal

Personalized Tour Package Recommendations via n8n + Pinecone + Lovable UI I've created an intelligent Travel Itinerary Planner that connects a Lovable front-end UI with a smart backend powered by n8n, Pinecone, and OpenAI to deliver personalized tour packages based on natural language queries. What It Does Users type in their travel destination and duration (e.g., "Paris 5 days trip" or "Bali Trip for 7 Days, would love water sports, adventures and trekking included, also some historical monuments") through a Lovable UI. This triggers a webhook in n8n, which processes the request, searches vectorized tour data in Pinecone, and generates a personalized itinerary using OpenAI’s GPT. The results are then structured and sent back to the frontend UI for display in an interactive, reorderable format. Workflow Architecture Lovable UI ➝ Webhook ➝ Tour Recommendation Agent ➝ Vector Search ➝ OpenAI Response ➝ Structured Output ➝ Response to Lovable Tools & Components Used Webhook Acts as the entry point between the Lovable frontend and n8n. Captures the user query (destination, duration) and forwards it into the workflow. OpenAI Chat Model To interpret the user query. To generate a user-friendly, structured tour package from the matched results. Simple Memory Keeps chat state and context for follow-up queries (extendable for future features like multi-step planning or saved itineraries). Question Answering with Vector Store Searches vector embeddings of pre-loaded tour data. Finds the most relevant tour packages by comparing query embeddings. Pinecone Vector Store Stores tour packages and activity data in vectorized format. Enables fast and scalable semantic search across destinations, themes (e.g., "adventure", "cultural"), and duration. OpenAI Embeddings Embeds all tour and activity documents stored in Pinecone. Converts input user queries into embedding vectors for semantic search. Structured Output Parser Parses the final OpenAI-generated response into a consistent, frontend-consumable JSON format. Frontend (Lovable UI) User types in destination or their travel package needs in the Tour Search. Lovable queries the n8n workflow. Displays beautifully structured, editable itineraries. How to Set It Up Webhook Setup in n8n Create a POST webhook node. Set Webhook URL and connect it with Lovable frontend. Pinecone & Embeddings Convert your static tour package documents (PDFs, JSON, CSV, etc.) into embeddings using OpenAI. Store the embeddings in a Pinecone namespace (e.g., kuala-lumpur-3-days). Configure “Answer with Vector Store” Tool Connect the tool to your Pinecone instance and pass query embedding for matching. Connect to OpenAI Chat Use the GPT model to process query + context from Pinecone to generate an engaging itinerary description. Optionally chain a second model to format it into UI-consumable output. Output Parser & Return Use Structured Output Parser to parse the response and pass it to Respond to Webhook node for UI display. Ideal Use Cases Smart itinerary planning for OTAs or DMCs Personalized travel recommendations in chatbots or apps Travel advisors and agents automating package generation Benefits Highly relevant, contextual travel suggestions Natural query understanding via OpenAI Seamless frontend-backend integration via Webhook If you’re building personalized experiences for travelers using AI, give this approach a try! Let me know if you’d like the JSON for this workflow or help setting up the Pinecone data pipeline.

🤖AI & Machine Learning

6 nodes1 views

Automate LLM Testing with GPT-4 Judge & Google Sheets Tracking

by Adam Janes

How it works The workflow loads a list of test cases from a Google Sheet (previous results stored from an LLM) For each test case, we execute a call to an LLM judge in parallel (using HTTP Request + Webhook nodes) The judge uses the Input, Output, and Reference Answer fields from the spreadsheet to mark each LLM response as Pass/Fail The results are logged into a separate sheet in the same Sheets file. Set up steps: Add your credentials for Google Sheets and OpenRouter (or replace the OpenRouter node with your favourite chat model). Make a copy of the example Sheet to populate it with you own test data. Run the workflow with the Execute Workflow button next to the Manual Trigger node.

Collect & Process Trip Feedback with Google Sheets and Email Notifications

by Oneclick AI Squad

This n8n workflow automates the collection and processing of trip feedback data using Google Sheets as the backend. When new users are added to the system, they automatically receive feedback forms via email, and all responses are systematically processed and stored in Google Sheets for analysis and record-keeping. Good to know The delay buffer prevents system overload and ensures data integrity before sending notifications. All feedback data is automatically organized and maintained in Google Sheets for easy access and analysis. The workflow handles both new user onboarding and trip feedback submission seamlessly. How it works The Trigger - New User Entry node detects when a new user is added to the Google Sheets feedback form database. The Delay - Process Buffer node introduces a processing delay to ensure data is fully processed before sending notifications, avoiding premature actions. The Send Email To That New User node automatically sends a feedback form email to the newly registered user. When a user submits their trip feedback, the Trigger - Trip Form Submission node captures the submission. The Tack All Feedback Item node iterates over each form submission item to process multiple entries if present, ensuring all feedback data is handled. The Update - Trip Feedback Sheet node appends or updates the trip feedback data in the Google Sheets, maintaining an organized record of all responses. How to use Import the workflow into n8n and configure the nodes with your Google Sheets API credentials and email service settings. Set up your Google Sheets with the appropriate columns for user data and feedback responses. Test the workflow by adding a new user entry to verify email delivery and feedback processing. Requirements Google Sheets API credentials with read/write permissions Email service configuration (SMTP or email API) Access to Google Sheets containing user data and feedback forms Customising this workflow Modify the email template in the Send Email To That New User node to match your branding and feedback requirements. Adjust the delay timing in the Delay - Process Buffer node based on your system's processing needs. Customize the Google Sheets structure and update the Update - Trip Feedback Sheet node accordingly to match your data organization preferences.

2 nodes

Automate Event Registration & Follow-ups with Gmail Reminders & Google Sheets

by Rodrigue Gbadou

How it works Simplified registration: Automatically captures sign-ups via optimized web forms. Instant confirmations: Immediately sends confirmation emails with event details and calendar invites. Scheduled reminders: Automatic reminder sequence before the event to maximize attendance. Post-event follow-up: Automatically collects feedback and nurtures participants. Set up steps Registration form: Create or connect your event registration form. Calendar system: Integrate with Google Calendar or Outlook to manage time slots. Email service: Set up your sending platform (Gmail, SendGrid, Mailchimp). CRM integration: Sync with your CRM for participant tracking. Feedback survey: Prepare your post-event satisfaction questionnaire. Personalized sequences: Tailor messages based on event type. Key Features 🎯 Optimized registration: Responsive forms with real-time validation 📅 Automatic calendar management: Instantly adds to calendars and manages time slots ⏰ Smart reminders: Progressive sequence (D-7, D-1, H-2) with personalized content 📊 Complete tracking: Monitors sign-ups, attendance, and participation rates 🎤 Multi-event support: Manage multiple events and formats simultaneously 📱 Mobile notifications: Push alerts and SMS for urgent reminders 🔄 Automatic feedback: Collects and analyzes participant feedback automatically 📈 Detailed analytics: Performance reports and improvement insights Supported Event Types Webinars**: Online sessions with auto-generated access links Conferences**: In-person events with seat and logistics management Trainings**: Learning sessions with progress tracking Meetings**: Internal meetings with invite coordination Workshops**: Practical sessions with materials and prerequisites Automated Sequence Sign-up → Immediate confirmation + calendar invitation D-7 → Reminder email with detailed program D-1 → Final reminder with practical info H-2 → Last-minute notification with access links/details Post-event → Satisfaction survey + additional content

3 nodes

Automate Candidate Evaluation with GPT-4 Scoring and Gmail Notifications

by Rodrigue Gbadou