Workflow Templates

What it does Automates code review by listening for a comment trigger on GitLab merge requests, summarising the diff, and using an LLM to post constructive, line‑specific feedback. If a JIRA ticket ID is found in the MR description, the ticket’s summary is used to inform the AI review. Use cases Quickly obtain high‑quality feedback on MRs without waiting for peers. Highlight logic, security or performance issues that might slip through cursory reviews. Incorporate project context by pulling in related JIRA ticket summaries. Good to know Triggered by commenting ai-review on a merge request. The LLM returns only high‑value findings; if nothing critical is detected, the workflow posts an “all clear” message. You can swap out the LLM (Gemini, OpenAI, etc.) or adjust the prompt to fit your team’s guidelines. AI usage may incur costs or be geo‑restricted depending on your provider n8n.io. How it works Webhook listener:** A Webhook node captures GitLab note events and filters for the trigger phrase. Fetch & parse:** The workflow retrieves MR details and diffs, splitting each change into “original” and “new” code blocks. Optional JIRA context:** If your MR description includes a JIRA key (e.g., PROJ-123), the workflow fetches the ticket (and parent ticket for subtasks) and composes a brief context summary. LLM review:** The parsed diff and optional context are sent to an LLM with instructions to identify logic, security or performance issues and suggest improvements. Post results:** Inline comments are posted back to the MR at the appropriate file/line positions; if no issues are found, a single “all clear” note is posted. How to use Import the template JSON and open the Webhook node. Replace the REPLACE_WITH_UNIQUE_PATH placeholder with your desired path and configure a GitLab project webhook to send MR comments to that URL. Select your LLM credentials in the Gemini (or other LLM) node, and optionally add JIRA credentials in the JIRA nodes. Activate the workflow and comment ai-review on any merge request to test it. For each review, the workflow posts status updates (“AI review initiated…”) and final comments. Requirements A GitLab project with a generate Personal Access Token (PAT) stored as an environment variable (GITLAB_TOKEN). LLM credentials (e.g., Google Gemini) and optional JIRA credentials. Customising this workflow Change the trigger phrase in the Trigger Phrase Filter node. Modify the LLM prompt to focus on different aspects (e.g., style, documentation). Filter out certain file types or directories before sending diffs to the LLM. Integrate other services (Slack, email) to notify teams when reviews are complete.

Description: Transform your health data into actionable meal plans with an Advanced AI Chain. 🥗🤖 This workflow goes beyond a simple prompt. It orchestrates a chain of Google Gemini agents to manage your blood pressure. It acts as a personal health assistant that analyzes your data, strategizes a diet plan, and finds real-world recipes. Key Features: Dual AI Logic: Uses Gemini (1.5-flash) in two stages—first to decide the search strategy based on BP status (High/Normal), and second to synthesize a 5-day meal plan. Real Recipe Search: Automatically searches Google for recipes that match the AI's dietary strategy (e.g., "Low sodium dinner"). Visual Tracking: Generates a blood pressure trend chart using QuickChart.io and attaches it to the email report. Organized Layout: Nodes are clearly grouped into sections (Data Collection, AI Strategy, Execution, Synthesis) for easy customization. How it works: Analyze: Fetches last 7 days of BP data from Google Sheets. Decide: AI determines the best search keywords (e.g., "Dash diet recipes") based on your average BP. Execute: Searches for recipes and generates a chart simultaneously. Synthesize: AI combines the recipes and health stats into a weekly plan. Deliver: Emails the plan and chart to you. Setup Requirements: Google Sheets: Create headers: date, systolic, diastolic. Google Gemini API Key Google Custom Search API Key & Engine ID Gmail

Generate a security audit report from an n8n instance to a web form This workflow provides a deep-dive security assessment of an n8n instance using the native Audit API and AI analysis. Who’s it for This template is for n8n administrators and DevSecOps engineers who need to maintain a high security standard across their automation infrastructure. It is particularly useful for teams managing self-hosted instances with multiple users. How it works The workflow triggers via an n8n Form where you provide your instance URL and API key. It calls the official n8n Audit API to scan for five categories of risk: instance settings, credentials, database (SQL injection), nodes, and filesystem access. A Code node parses this data, which is then analyzed by Google Gemini to create a prioritized remediation plan. Requirements n8n version v1.0 or higher. A Google Gemini API Key. An n8n API Key with 'Audit' scope permissions. How to set up Create a Google Gemini API credential in n8n. Ensure your n8n API key has the correct scopes. Execute the workflow and enter your credentials into the trigger form. How to customize the workflow You can easily swap the Google Gemini node for OpenAI or Anthropic. You can also add a 'Send Email' or 'Slack' node at the end to automatically route the report to your security channel instead of just viewing it in the browser.

Who’s it for Freelancers and agencies who track new Upwork leads via Vollna RSS and want clean logging to Google Sheets with instant Slack alerts. What it does Polls a Vollna RSS feed every few minutes, parses each job (title, budget, link, skills, categories), dedupes against your sheet, appends only new jobs, and notifies Slack with a compact alert. How it works Schedule Trigger fires on an interval. RSS Read pulls new items from Vollna. Filter (optional) skips non-ASCII titles. Code node normalizes fields (title/budget split, clean Upwork link, “Posted x mins ago”, etc.). Sheets Lookup + Compare prevents duplicates by job URL. Sheets Append writes new rows; Slack posts a job alert. Set up In ⚙️ Config, set: VOLLNA_RSS_URL, GOOGLE_SHEETS_DOC_ID, GOOGLE_SHEET_NAME, SLACK_CHANNEL_ID, EMAIL_TO (optional). Add OAuth credentials for Google Sheets, Slack, and Gmail (optional). Create sheet columns: TITLE, BUDGET, UPWORK JOB LINK, CATEGORIES, SKILLS, DATE, JOB DESCRIPTION, POSTED. (Optional) Adjust polling interval on the Schedule Trigger. Requirements • Vollna RSS feed URL (your tokenized link) • n8n (cloud or self-hosted) with Google Sheets + Slack creds Customize • Remove the ASCII filter for broader coverage. • Swap Gmail/Slack with your preferred notifier. • Add keyword filters before appending to Sheets.

How it works Expected Image Download The expected image’s Dropbox URL is passed directly into an HTTP Request node, which downloads the image as binary data. Actual Image Extraction The HTML node extracts the src of the image from the email (e.g., hero image or other targeted image sections). This src is passed into another HTTP node to download the actual email image in binary format. OCR Processing Both binary images are sent separately to OCR.Space API via POST requests. OCR returns extracted text for each image. Comparison A JS node compares the Expected Image Text vs Actual Image Text. If the texts match, the result is marked Match; otherwise Mismatch. Write Back to Google Sheets The workflow writes ExpectedText, ActualText, and Result back into the Google Sheet, creating a clear audit trail for validation. Setup steps 1. Google Sheets Create a sheet with the following columns: SectionId ExpectedImageURL ExpectedText ActualText (output) Result (output) Add the expected text that should appear inside each image. 2. Email HTML Source Use one of the following: Gmail node — fetches the email HTML via unread or filtered messages HTTP Request / binary file input — if HTML is being pulled from storage or a URL Ensure the HTML extraction node can find the image src correctly 3. Expected Image (Dropbox URL) Paste the public Dropbox URL directly into the Google Sheet This URL is fed into an HTTP Download node The resulting binary is used for OCR extraction 4. OCR Setup Add your OCR.Space API key in the HTTP POST node Set the request body to include: apikey the binary property of the image desired OCR settings (language, text extraction mode) 5. Merge & Compare Use a Merge node to align: ExpectedImageURL + ExpectedText ActualImageSrc OCR outputs 6. In the Code node: Normalize both texts Compare and assign Match or Mismatch 7. Write Output Use a Google Sheets Append/Update node to write: ActualText Result back into the corresponding row, using SectionId or ExpectedImageURL as the matching key.

Tired of shelling out big bucks for newsletters? This n8n workflow automates the delivery of personalized newsletters by leveraging BrowserAI for task management and scheduling. It simplifies the process of staying updated with daily news summaries, ensuring efficiency and consistency. BrowserAI is a serverless tool for web automation, solving CAPTCHAs, enabling seamless data extraction. Overview This workflow provides a structured approach to automate newsletter delivery, perfect for anyone desiring regular updates without high costs. It's ideal for tech enthusiasts, marketers, or any individual or organization seeking timely, curated content. Setup Instructions Pre-conditions BrowserAI Account: Ensure you have a BrowserAI account. If not, register! API Key: Obtain your API key from your BrowserAI dashboard. Step-by-Step Setup 🗓️ Start the Workflow and Get Yesterday’s Date Initiates every morning at 8 AM. Dynamically calculates and formats yesterday’s date to use as a reference for news content. 🌐 Create a BrowserAI Task Utilizes BrowserAI to gather relevant news articles and updates from various sources. Ensures the latest information is compiled efficiently through BrowserAI’s web extraction capabilities. ⏳ Wait for Task Completion Includes a control mechanism to pause until the BrowserAI task successfully completes. Regular status checks verify task completion to ensure smooth progression. 🔍 Retrieve and Verify Task Completion Retrieves task metadata with essential news article information upon completion. Evaluates completion status: If finalized, moves to the next step. If in fallback status, waits for fulfillment to ensure reliability. 📩 Send It to Your Email/WhatsApp/Telegram Prepares summarized news content for preferred communication channels. Reformats into an engaging newsletter format. Sends via email, WhatsApp, or Telegram for timely delivery. Customization Guidance Personalize Content:** Tailor the newsletter content by specifying keywords or themes in BrowserAI. Adjust Schedule:** Change the delivery time in n8n according to your preference. This workflow efficiently automates the newsletter creation and distribution process, solving the problem of costly and manually-intensive updates.

AI Sales Battle Card Generator (Research + Personalized Pitch Assets) This n8n template automatically generates high-quality sales battle cards for any prospect company using real-time research and AI. It analyzes company news, website content, and your product’s value proposition to create personalized outreach hooks, talk tracks, and objection handling — all delivered as a ready-to-use document. Who’s it for Sales reps and SDRs preparing for outreach Founders doing high-quality cold outreach Sales teams building personalized pitches at scale Agencies doing outbound lead generation Anyone who wants deeper, research-driven sales conversations How it works / What it does Form Input Enter: Company name Company website URL Your product’s value proposition Company Research (Olostep) Searches for the latest company news, hiring trends, and challenges. Identifies signals like growth, funding, or operational pressure. Website Scraping Scrapes the company’s website to understand positioning, messaging, and offerings. AI Research Analysis AI identifies: Key business triggers (why now?) Opportunities where your product fits Maps your value proposition to real company needs. Pitch Asset Generation Generates personalized sales assets: Cold outreach hook (email/LinkedIn opener) High-impact discovery questions Likely objection + smart rebuttal Battle Card Generation Combines everything into a structured Sales Battle Card including: Executive summary Outreach assets Objection handling Research sources Document Creation (Google Docs) Converts the output into a clean document. Automatically creates a Google Doc with the final battle card. Share & Notify Shares the document via Google Drive. Sends an email with the link to the generated battle card. This workflow turns raw company data into a ready-to-use sales playbook in minutes. How to set up Import the template into your n8n workspace. Add your Olostep API key. Connect your Google Drive account. Add your AI model provider (Gemini or OpenAI). Run the form and generate your first battle card. Requirements n8n account (cloud or self-hosted) Olostep API key Google Drive / Google Docs access AI model provider (Gemini or OpenAI) How to customize the workflow Adjust prompts to match your sales style or industry. Add CRM integration (HubSpot, Salesforce). Generate multiple variations of outreach hooks. Add scoring for lead qualification. Store battle cards in Notion or a database. This template helps you go from generic outreach to highly personalized, research-driven sales conversations instantly.

Generate AI blog posts with human review using SE Ranking and Claude Who is this for Content teams scaling blog production with AI SEO agencies creating client content at scale Marketing teams with editorial calendars What this workflow does Find high-opportunity keywords, generate AI content briefs and draft articles, then send everything to a human reviewer before anything gets published. What you'll get Keyword opportunities scored by volume, difficulty, and ranking potential AI-generated content briefs with outlines and related keywords Full draft articles written by Claude based on the briefs Email-based human review with one-click approve/reject Everything tracked in Google Sheets How it works Pulls keyword opportunities for your domain from SE Ranking Scores and filters the best targets by volume and difficulty Grabs related keywords and "People Also Ask" questions AI creates a detailed content brief for each keyword AI writes a full draft article based on the brief Sends a review email with approve/reject buttons Updates Google Sheets with the decision Approved articles are split and ready for publishing Requirements Self-hosted n8n instance SE Ranking community node v1.3.5+ (Install from npm) SE Ranking API token (Get one here) Anthropic API key (for Claude) SMTP credentials for review emails Google Sheets account (optional) Setup Install the SE Ranking community node Add your SE Ranking, Anthropic, and SMTP credentials Update the Configuration node with your domain, brand, and reviewer email Connect Google Sheets for tracking (optional) Customization Change min_volume and max_difficulty to adjust keyword targeting Edit articles_per_run to generate more or fewer articles per batch Swap Claude models in the AI nodes for different quality/cost tradeoffs

How It Works Daily triggers automatically fetch fleet data and simulate key performance metrics for each vehicle. An AI agent analyzes maintenance requirements, detects potential issues, and routes alerts according to urgency levels. Fleet summaries are aggregated, logged into the database for historical tracking, and AI-enhanced insights are parsed to provide actionable information. Slack notifications are then sent to relevant teams, ensuring timely monitoring, informed decisions, and proactive fleet management. Setup Steps Configure daily triggers to automatically fetch, process, and update fleet data. Connect Slack, the database, and AI APIs to enable notifications and analytical processing. Set AI parameters and provide API keys for accessing the models and ensuring proper scoring. Configure PostgreSQL to log all fleet data, summaries, and alerts for historical tracking. Define Slack channels to receive real-time alerts, summaries, and actionable insights for the team. Prerequisites Slack workspace, database access, AI account (OpenRouter or compatible), fleet data source, n8n instance Use Cases Fleet monitoring, predictive maintenance, multi-vehicle management, cost optimization, emergency alerts, compliance tracking Customization Adjust AI parameters, alert thresholds, Slack message formatting, integrate alternative data sources, add email notifications, expand logging Benefits Prevent breakdowns, reduce manual monitoring, enable data-driven decisions, centralize alerts, scale across vehicles, AI-powered insights

✔ Short Description Automate your lead qualification pipeline — capture Typeform Webhook leads, enrich with APIs, score intelligently, and route to HubSpot, Slack, and Sheets in real-time. 🧩 Description Automate your lead management pipeline from form submission to CRM enrichment and routing. This workflow intelligently processes Typeform Webhook submissions, enriches leads using Hunter.io and Abstract API, scores them with dynamic logic, and routes them into HubSpot while keeping your sales team and tracking sheets up to date. It’s a full-stack automation designed to turn raw form submissions into prioritized, qualified CRM-ready leads — without manual intervention. 💡 Who’s it for Marketing teams managing inbound leads from web forms Sales operations teams that qualify and route leads CRM administrators automating lead data entry and scoring Automation professionals building data enrichment systems ⚙️ How it works / What it does Trigger: Receives new Typeform Webhook submissions via Webhook. Data Extraction: Parses name, email, and company info. Email Verification: Validates email deliverability with Hunter.io. Company Enrichment: Fetches company data (industry, size, country) using Abstract API. Lead Scoring Logic: Calculates a lead score and assigns a tier (Hot / Warm / Cold). Conditional Routing: Hot Leads (≥70) → Sent to HubSpot as Qualified. Warm/Cold Leads (<70) → Sent to HubSpot as Nurture stage. Revalidation Loop: Waits (e.g., 3 days) → Rechecks Nurture leads in HubSpot. Logs them to Google Sheets and alerts your Slack channel. 🧰 How to set up Connect accounts: Typeform Webhook (for inbound lead capture) Hunter.io (API key for email verification) Abstract API (for company enrichment) HubSpot (via OAuth2 credentials) Slack (for notifications) Google Sheets (for logging) Customize the Webhook URL inside your Typeform Webhook integration. Replace API keys with your own (Hunter.io, Abstract). Adjust scoring logic inside the Lead Scoring & Routing Logic node to fit your business. Set Wait duration (default: 10 seconds for testing → change to 3 days for production). Activate the workflow and test it with a sample form submission. 🔧 Requirements Typeform account with webhook capability Hunter.io account + API key Abstract API account + API key HubSpot account with OAuth2 credentials Slack workspace & channel Google Sheets integration 🎨 How to customize the workflow Scoring rules:** Modify the “Lead Scoring & Routing Logic” node to adjust how points are calculated (e.g., country, industry, employee size). CRM target:** Replace HubSpot nodes with another CRM (e.g., Pipedrive, Salesforce). Notification channel:** Swap Slack for Email, Discord, or MS Teams. Data source:** Replace Typeform Webhook with another trigger like Webflow Forms, Airtable, or custom API input. Tracking:** Add Google Analytics or Notion API for additional reporting. 🧭 Summary End-to-end lead automation workflow that combines form data, enrichment APIs, CRM updates, and Slack alerts into one intelligent system. Ideal for any team looking to centralize and qualify leads automatically — from submission to sales. 🧑‍💻 Creator Information Developed by: Adem Tasin 🌐 Website: ademtasin 💼 LinkedIn: Adem Tasin

This n8n template from Intuz provides a complete and automated solution for powerful cold outreach campaigns. It connects a Google Sheet of prospect data with Google Gemini to automatically generate highly personalized emails. By analyzing specific keywords and data points like company name, industry, or job title from your sheet, this automated workflow crafts unique, relevant messages that feel one-to-one, creating a complete system to dramatically improve your engagement and response rates. How it Works Manually writing personalized emails for a long list of leads is a significant bottleneck. This workflow eliminates that friction by creating an automated system that reads your lead list, understands the context, and writes compelling drafts for you. Scheduled Lead Processing:** On a schedule you define (e.g., daily), the workflow automatically activates to process your lead list. Fetches Your Lead List:** It connects to your designated Google Sheet and reads all the lead data you've prepared, such as names, companies, roles, and any custom notes or pain points. Intelligent Filtering:** The workflow is smart enough to know which leads have already been processed. Using an "If" node, it filters out any rows that already contain a generated email, ensuring it only works on new, untouched leads. AI-Driven Personalization (Google Gemini):** This is the core of the engine. For each new lead, it sends the relevant data to the Google Gemini Chat Model. The AI follows a custom prompt you define to draft a completely unique email, including a compelling subject line and a personalized body. Structured Data Output:** The workflow uses a Structured Output Parser to ensure the AI's response is always in a clean, predictable JSON format (e.g., {"subject": "...", "body": "..."}), making the data easy to handle in the next steps. Seamlessly Updates Your Spreadsheet:** Finally, the generated subject line and email body are written back into the correct row for that lead in your Google Sheet, ready for your team to copy, paste, and send. How to Use: Quick Start Guide 1. Import Workflow Template: Download the template’s JSON file and import it into your n8n instance via “File” > “Import from JSON.” 2. Configure Credentials: Google Gemini: Create and apply your API key credentials to the “Google Gemini Chat Model” node. Google Sheets: Set up and apply OAuth credentials for the Google account that owns your lead spreadsheet. Apply this credential to both the "Read Leads from Sheet" and "Update Sheet with Email" nodes. 3. Customize Nodes & Spreadsheet: Prepare Your Google Sheet:** Ensure your sheet has columns for lead data (e.g., FirstName, Company, Role) and empty columns to receive the output (e.g., GeneratedSubject, GeneratedEmail). Read Leads from Sheet:** Double-click this node and select your spreadsheet and sheet name from the list. If Node:** Update the condition to check your specific output column. For example, if your output column is named GeneratedEmail, the condition should check if {{$json.GeneratedEmail }} is empty. Basic LLM Chain Node:** This is the most important step. Edit the Template prompt to match your product, service, and desired tone. In the Template Variables section, make sure the values (e.g., {{ $('Read Leads from Sheet').item.json.FirstName }}) match the exact column names from your Google Sheet. Update Sheet with Email Node:** Select your spreadsheet and sheet name. Set the Lookup Column to a unique identifier for each lead (like their Email address). Then, map the output from the Prepare Data for Sheet node to the correct destination columns in your sheet. 4. Test & Activate: Test Run:** Click “Execute Workflow” to perform a test run. Check your Google Sheet to see if the first unprocessed lead was updated correctly with a new subject and body. Activate:** Once satisfied, toggle the workflow “Active” switch to enable it to run on your defined schedule. Requirements To use this workflow template, you will need: 1. n8n Instance: A running n8n instance (cloud or self-hosted). 2. Google Gemini Account: For generating the email content (requires a Google Gemini API Key from Google AI Studio). 3. Google Sheets Account: With a prepared spreadsheet containing your lead list and columns for the generated output. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started

Who is this for? This workflow is built for B2B marketers, consultants, founders, and agency owners who need to produce high-quality, research-backed thought leadership content — without spending hours on research and writing. What this workflow does This agent-powered workflow takes a simple topic input and transforms it into a comprehensive, professionally formatted lead magnet article saved directly to Google Docs. It runs parallel deep research across 5 strategic angles, compiles the findings, and produces a polished long-form article ready for LinkedIn, your blog, or a downloadable PDF. How it works Topic Input — You submit a topic via the built-in chat trigger. Strategic Query Generation — An AI agent refines your topic into 5 targeted research queries covering market context, pain points, frameworks, case studies, and future trends. Parallel Deep Research — Each query is researched independently by an AI agent, producing 400–600 words of data-rich content per section. Compilation & Structuring — All research is merged into a structured article with a table of contents, statistics, and sources. Final Writing & Editing — A writing agent produces the complete 2,500–4,000 word article with proper formatting. Google Docs Output — The article is created as a formatted Google Doc with bold text, headings, and a shareable link. Tracking — Each generated article is logged to a Google Sheet for tracking. Setup steps Connect your Ollama instance — Set up your Ollama API credentials (or swap the LLM node for OpenAI, Anthropic, etc.). Connect Google Docs OAuth2 — Create OAuth2 credentials for the Google Docs API. Connect Google Drive OAuth2 — Create OAuth2 credentials for the Google Drive API (used to make the doc shareable). Connect Google Sheets OAuth2 — Create OAuth2 credentials and update the Sheet URL in the "Log to Tracking Sheet" node to point to your own spreadsheet. Update author name — In the "Validate Queries" Code node, change YOUR_AUTHOR_NAME to your name. Activate and test — Open the chat trigger URL and submit a topic. Requirements n8n instance (self-hosted or cloud) Ollama running locally (or substitute with any supported LLM provider) Google Cloud project with Docs, Drive, and Sheets APIs enabled OAuth2 credentials for Google services How to customize Swap the LLM** — Replace the Ollama Chat Model node with OpenAI, Anthropic, Google Gemini, or any LangChain-compatible model. Change the output format** — Modify the "Final Editor and Polish" system prompt to produce blog posts, whitepapers, or email sequences instead. Adjust research depth** — Edit the number of strategic queries or word count targets in the agent prompts. Add distribution** — Extend the workflow to post directly to LinkedIn, send via email, or upload to your CMS.