by Ravi Patel
Quick overview This workflow takes a YouTube video URL, fetches its transcript via RapidAPI, uses Google Gemini to generate multiple repurposed content assets, stores everything in Google Sheets, and automatically publishes the LinkedIn post while logging posted/failed status and any errors. How it works Starts when a user submits a YouTube video URL through an n8n form. Requests the video transcript from the youtube-transcript3 RapidAPI endpoint and normalizes it into a single clean text block. Sends the transcript to Google Gemini to generate a JSON bundle containing a title, summary, blog article, LinkedIn post, X (Twitter) thread, newsletter, content ideas, hooks, and CTA suggestions. Parses and validates the Gemini response into consistent fields for downstream use. Appends the transcript and all generated content to Google Sheets (Sheet1) as a content database row. Publishes the generated LinkedIn post to your LinkedIn profile and updates the same Google Sheets row as Posted or Failed. Logs any errors from transcript fetching, AI generation/parsing, Google Sheets, or LinkedIn publishing to a Google Sheets “Errors” tab. Setup Create a RapidAPI subscription for youtube-transcript3 and replace the x-rapidapi-key value with your RapidAPI key. Add Google Gemini (PaLM) API credentials in n8n and connect them to the Google Gemini Chat Model node. Create a Google Sheets spreadsheet with “Sheet1” and an “Errors” sheet using the exact headers shown in the workflow notes, then set your Google Sheet ID in all Google Sheets nodes. Add Google Sheets OAuth2 credentials in n8n with access to that spreadsheet. Add LinkedIn OAuth2 credentials in n8n and confirm the workflow is permitted to post to the target LinkedIn account. Requirements I need an AI-powered content workflow that takes a YouTube URL, pulls the transcript automatically, and generates multiple content assets (blog, LinkedIn post, X thread, newsletter, hooks, CTAs) in one run. It should log all outputs into a Google Sheet as a structured content database and optionally auto-post to LinkedIn while tracking Posted/Failed status with error logs. Customization I want the system to be customizable for different niches and tones, so I can tweak prompts or add extra output formats without changing the overall workflow logic. It should also let me plug in my own API keys and credentials inside n8n, without hardcoding any secrets in the workflow JSON. Additional info This is built as an n8n workflow that starts from a form (YouTube URL input), calls a transcript API, uses a Gemini model node, and writes to Google Sheets plus LinkedIn. I’m comfortable editing nodes, expressions, and environment variables myself, so a clean template without bound credentials is actually preferred.
by Oneclick AI Squad
This workflow monitors brand mentions across multiple platforms (Twitter/X, Reddit, News) and automatically detects reputation crises based on sentiment analysis and trend detection. How it works Multi-platform monitoring: Every 10 minutes, scans Twitter/X, Reddit, and news sites for brand mentions Data normalization: Converts all platform data into unified format Smart filtering: Removes duplicates and already-analyzed mentions AI sentiment analysis: Analyzes each mention for: Sentiment score (positive/negative/neutral) Amplification factors (engagement, verified accounts, news sources) Crisis-level phrases and keywords Trend detection: Compares current sentiment to 24-hour baseline: Detects sharp sentiment drops Identifies negative mention spikes Calculates impact surge Crisis classification: Assigns severity (CRITICAL/HIGH/MEDIUM/LOW) Automated response: For crises, triggers immediate alerts: Executive crisis brief with action plan Slack alerts to crisis team Email to leadership and PR team JIRA ticket creation Crisis event logging Setup steps Connect platforms: Twitter/X: Add OAuth credentials to "Monitor Twitter/X" node Reddit: Add OAuth credentials to "Monitor Reddit" node News API: Get API key from newsapi.org and add to "Monitor News & Blogs" node Configure brand monitoring: Update brand name and handles in search queries Add additional platforms if needed (LinkedIn, Facebook, Instagram) Set up alerting: Slack: Add credentials and update channel names Email: Add SMTP settings and recipient lists JIRA: Add credentials and project ID Adjust sensitivity: Modify sentiment keyword dictionaries in "AI Sentiment Analysis Engine" Adjust crisis threshold scores Customize amplification factors Test thoroughly: Run manual execution with test data Verify alert routing and content Test false positive handling Activate: Enable for continuous 24/7 monitoring Key Features: Multi-platform monitoring** (every 10 minutes): Twitter/X, Reddit, and News sites Data normalization** that converts different platform formats into unified structure AI sentiment analysis** engine that evaluates: Sentiment keywords (critical, severe, moderate, mild negative/positive) Amplification factors (engagement, verified accounts, follower counts) Impact scoring based on reach and influence Baseline trend detection** that tracks 24-hour sentiment history and detects: Sharp sentiment drops (15+ points = crisis) Negative mention spikes (30%+ increase) Impact surges Automated crisis response workflow**: Aggregates crisis mentions into executive brief Generates detailed action plan based on severity Sends Slack alerts to crisis team Emails leadership with comprehensive brief Creates JIRA ticket for tracking Logs all events for analysis Two-path routing**: Crisis-level events trigger full response workflow, while routine mentions are logged for trend analysis
by Davide
The Video Grok Agent is an AI-powered video generation and editing workflow that uses Grok 4.1 Fast (via OpenRouter) and Grok Imagine Video to create and modify videos through natural language. This workflow enables seamless AI-driven video creation and editing through a conversational interface, with built-in validation, async processing, and secure credential management. Key Advantages 1. ✅ Unified Video Creation Pipeline A single workflow supports text-to-video, image-to-video, and video editing, reducing complexity and avoiding duplicated logic across multiple automations. 2. ✅ AI-Guided User Interaction The conversational agent ensures: the correct tool is selected, all mandatory parameters are provided, errors due to missing inputs are minimized. This makes the workflow usable even by non-technical users. 3. ✅ Asynchronous & Scalable Execution The workflow is designed around queued, non-blocking requests: wait nodes + status polling no execution timeouts scalable for multiple concurrent video jobs 4. ✅ Automatic Media Handling Uploaded images are: detected automatically, uploaded to external storage, converted into usable URLs without manual steps. This enables smooth image-to-video generation directly from chat uploads. 5. ✅ Clear Separation of Responsibilities Each step is modular: orchestration (agent), decision routing (switch), media processing (Fal.run APIs), status monitoring (HTTP + wait loops). This makes the workflow easy to maintain, extend, or debug. 6. ✅ Strong Guardrails & Validation The agent enforces: correct tool usage (e.g. video-to-video only for editing), duration limits (1–15 seconds), mandatory URLs before execution. This prevents incorrect API calls and wasted compute. 7. ✅ Extensible Architecture New tools (e.g. different models, resolutions, aspect ratios, or providers) can be added without redesigning the whole system—just plug them into the existing agent + switch logic. How it works User Interaction The workflow starts with a chat trigger (When chat message received), where users can upload images and submit text prompts. If an image is uploaded, it is automatically stored via FTP (BunnyCDN) and its URL is passed to the AI agent. AI Agent Orchestration The Grok Imagine Video Agent processes the user’s request and determines which action to perform: Text-to-Video: Create a new video from a text prompt. See test result Image-to-Video: Animate an existing image. See test result Video-to-Video: Edit an existing video. See test result The agent follows strict rules to ensure all required parameters (e.g., duration, URLs, prompts) are collected before proceeding. Video Processing via Fal.run API Depending on the selected tool, the workflow calls the corresponding Fal.run endpoint: text-to-video image-to-video edit-video Each request returns a request_id used to poll for completion. Asynchronous Processing & Polling After submission, the workflow enters a polling loop: Waits 10–30 seconds. Checks the request status via Fal.run’s status endpoint. Once the status is COMPLETED, it retrieves the final video URL. Result Delivery The final video URL is returned to the user via the chat interface. The agent does not proceed further once the video is ready. Set Up Steps To deploy and use this workflow in n8n: Credentials Configuration Set up the following credentials in n8n: OpenRouter API (for Grok 4.1 Fast) Fal.run API (HTTP Header Auth) FTP/BunnyCDN (for image uploads) Workflow Activation Ensure all nodes are correctly connected as per the connections mapping. Activate the workflow via the Execute Workflow Trigger (Run Text-to-Video1). Chat Interface Setup The workflow is designed to be triggered via a chat message. Configure the When chat message received node to connect to your frontend or chat platform. Parameter Validation The AI agent includes validation rules to ensure: Duration is between 1–15 seconds. Required URLs (image/video) are provided where needed. The correct tool is invoked based on user intent. Testing & Monitoring Test each tool separately (text, image, video) to ensure Fal.run API responses are handled correctly. Monitor the polling loops to avoid timeouts and ensure video URLs are retrieved successfully. 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. Need help customizing? Contact me for consulting and support or add me on Linkedin.
by Sona Labs
Generate Sora videos, stitch clips, and post to Twitter Generate creative ASMR cutting video concepts with GPT-5.1, create high-quality video clips using Sora v2, stitch them together with Cloudinary, and automatically post to Twitter/X—transforming ideas into viral content without manual video editing. How it works Step 1: Generate Video Concepts Schedule Trigger activates the workflow automatically GPT-5.1 AI agent generates 3 unique ASMR cutting scene prompts with unusual objects Creates structured video prompts optimized for Sora v2 (frontal camera angle, cutting actions) Generates Twitter-ready captions with relevant hashtags Saves all concepts and scripts to Google Sheets for tracking Step 2: Create Video Clips with Sora v2 Generates 3 separate Sora v2 video clips in parallel (8-12 seconds each) Each clip uses unique prompts from GPT-5.1 output Videos render at 720x1280 resolution (vertical format for social media) System waits 30 seconds for rendering to complete Step 3: Monitor & Download Videos Loops through all 3 video generation requests Checks Sora API status every 30 seconds until rendering completes Automatically skips failed renders (continues workflow with successful videos) Downloads completed videos from Sora API Uploads each clip to Cloudinary for storage and processing Step 4: Stitch Videos Together Collects all uploaded Cloudinary video IDs Builds Cloudinary transformation URL to stitch 3 clips into one seamless video Applies Twitter-compatible encoding (H.264 baseline, AAC audio, MP4 format) Downloads the final stitched video Step 5: Upload to Twitter/X Prepares video file data and calculates total file size Uses Twitter's chunked upload API (INIT → APPEND → FINALIZE) Waits for Twitter's video processing to complete Checks processing status until video is ready Posts tweet with AI-generated caption and attached video Updates Google Sheets status to "Posted" What you'll get AI-Generated Concepts**: Creative ASMR cutting ideas with unusual objects (glass avocados, lava rocks, rainbow soap) Professional Video Clips**: Three 8-12 second Sora v2 videos per concept with 720x1280 resolution Seamless Stitching**: Single combined video optimized for Twitter/X specifications Engaging Captions**: GPT-5.1 generated tweets with hashtags designed for virality Automated Posting**: Direct upload to Twitter/X without manual intervention Cloud Backup**: All videos stored in Cloudinary with metadata Progress Tracking**: Google Sheets integration shows workflow status (In Progress → Posted) Error Handling**: Failed Sora renders are automatically skipped Why use this Save 4+ hours per video**: Eliminate scripting, shooting, editing, and posting time Consistent posting schedule**: Set it and forget it with the Schedule Trigger Scale content creation**: Generate multiple video variations in 20-30 minutes Professional quality**: Leverage Sora v2's AI video generation for realistic cutting scenes Optimize for virality**: GPT-5.1 creates concepts and captions designed for engagement Reduce creative burnout**: AI handles ideation, execution, and distribution No video editing skills needed**: Complete automation from concept to post Test multiple concepts**: Generate 3 variations per run to see what resonates Setup instructions Required accounts and credentials: OpenAI API Key (GPT-5.1 and Sora v2 access required) Sign up at https://platform.openai.com Ensure your account has Sora v2 API access enabled Generate API key from API Keys section Note: Sora v2 is currently in limited beta Google Sheets OAuth (for tracking video ideas and status) Free Google account required Create a spreadsheet with columns: Category, Scene 1, Scene 2, Scene 3, Status n8n will request OAuth permissions during setup Cloudinary Account (for video storage and stitching) Sign up at https://cloudinary.com (free tier available) Note your cloud name from the dashboard Create an upload preset named n8n_integration Enable unsigned uploads for the preset Twitter OAuth 1.0a Credentials (for automated posting) Apply for Twitter Developer access at https://developer.twitter.com Create a new app in the Developer Portal Generate: API Key, API Secret, Access Token, Access Token Secret Enable "Read and Write" permissions (not just Read) OAuth 1.0a is required for media uploads (OAuth 2.0 won't work) Configuration steps: Update OpenAI API Key: Add your OpenAI API key to these nodes: "OpenAI Chat Model" credentials "Create Sora Video Scene - 1" (Authorization header) "Create Sora Video Scene - 2" (Authorization header) "Create Sora Video Scene - 3" (Authorization header) "Check Video Status" (Authorization header) "Download Completed Video" (Authorization header) Replace Bearer API KEY with Bearer YOUR_ACTUAL_API_KEY Configure Google Sheets: Open "Save Category and Clip Scripts" and "Update Status" nodes Authenticate with your Google account (OAuth 2.0) Select your spreadsheet and sheet name Ensure columns match: Category, Scene 1, Scene 2, Scene 3, Status The workflow will update Status from "In Progress" to "Posted" Update Cloudinary Settings: In "Upload to Cloudinary" node: Replace {Cloud name here} in the URL with your Cloudinary cloud name Verify upload preset is set to n8n_integration In "Build Stitch URL" node: Open the Code node Replace dph9n4uei on line 1 with your cloud name This builds the video stitching transformation URL Add Twitter OAuth 1.0a Credentials: Configure OAuth 1.0a in these nodes: "Twitter Upload - INIT" "Twitter Upload - APPEND" "Finalize Upload" "Check Twitter Processing Status" "Post a Tweet" Use the same OAuth 1.0a credential for all nodes Ensure your Twitter app has "Read and Write" permissions Adjust Schedule Trigger (optional): Default: Runs on every interval Modify in "Schedule Trigger" node to set specific times Recommended: Once per day or every few hours to avoid rate limits Test the workflow: Click "Execute Workflow" to test manually first Verify GPT-5.1 generates 3 video concepts Check that Sora v2 creates all 3 videos Confirm Cloudinary stitches videos correctly Ensure Twitter post appears with video and caption Important notes: Sora API Rate Limits**: Sora v2 may have rendering quotas. Monitor your usage Video Rendering Time**: Each Sora clip takes 2-5 minutes. Total workflow: 15-25 minutes Failed Videos**: The workflow automatically skips failed renders and continues Twitter Video Limits**: Maximum 512MB per video, MP4 format required Cloudinary Free Tier**: 25 credits/month includes video transformations Cost Estimate**: ~$1-3 per run (Sora API pricing varies) Troubleshooting: "Sora API access required"**: Contact OpenAI to enable Sora v2 API on your account Twitter upload fails**: Verify OAuth 1.0a credentials have "Read and Write" permissions Cloudinary upload fails**: Check cloud name and ensure upload preset exists Videos don't stitch**: Verify all 3 videos uploaded successfully to Cloudinary Google Sheets not updating**: Confirm OAuth permissions and sheet column names match Next steps: Enable the Schedule Trigger to automate daily/weekly posts Monitor Google Sheets to track posted content Adjust GPT-5.1 prompts in "ASMR Cutting Ideas" for different content themes Experiment with different video durations (8 vs 12 seconds) Add error notifications using Email or Slack nodes
by iamvaar
Quick overview Youtube Video Explanation: https://youtu.be/GNAplBWdCDE?si=fX31M-nu3sP2b276 This workflow receives an authenticated webhook with an audio file and mobile number, looks up the matching contact and recent notes in GoHighLevel, transcribes the audio with Deepgram, generates a structured CRM call note using Gemini, and logs the results to Google Sheets before responding. How it works Receives an authenticated POST webhook request containing a contact mobile number and an uploaded audio file. Looks up the contact in GoHighLevel (LeadConnector) by the provided mobile number and continues only if a matching contact ID is found. Extracts the uploaded audio from the webhook payload and sends it to Deepgram’s transcription API to produce a call transcript. Retrieves the contact’s notes from GoHighLevel and uses only notes from the last 30 days as context. Sends the recent notes and transcript to Google Gemini to generate a structured CRM interaction note. Appends or updates a row in Google Sheets with the contact details, recent notes, execution link, and the AI-generated note. Returns the workflow result back to the original webhook request. Setup Configure the Webhook trigger URL in your calling app and include the required header authentication plus a POST body field named mobile_number and a binary audio upload. Add GoHighLevel (HighLevel OAuth2) credentials with access to contacts and notes for your location/account. Add a Deepgram API key (HTTP Header Auth) and ensure the webhook uploads an audio format supported by Deepgram. Add Google Gemini (Google PaLM) credentials for the Gemini chat model used to generate the CRM note. Add Google Sheets service account credentials, select the target spreadsheet and sheet, and replace https://enter-your-n8n-instance-url-here with your n8n base URL for the execution link.
by Ghufran Barcha
UGC Ads Factory — Automated AI Video Pipeline This n8n workflow turns a script and character/setting description from Google Sheets into a complete stitched UGC-style video ad, fully automated from intake to final delivery. --- Overview The workflow runs a full production pipeline in four stages: Image Generation An AI agent creates a photorealistic selfie prompt from the character/setting description. The image is generated with Kie (Nano Banana), then uploaded to Google Drive and shared. Scene Scripting The generated image is analyzed by Claude-4o-mini for visual consistency. Claude Opus then converts the user script into structured 8-second scenes with consistent visuals and environment-aware motion prompts. Video Clip Generation Each scene is sent to Kie VEO3 for video generation. The workflow polls until each clip is complete, then uploads clips to Google Drive and updates status per scene. Video Stitching After all scene clips are completed, clips are sorted and merged into one final video using fal.ai FFmpeg. The stitched output is uploaded to Drive, and the final links are written back to Sheets. --- Google Sheets Structure This workflow uses two tabs in one spreadsheet: Videos (campaign-level tracking) Main input/output tab with script, character description, aspect ratio, and global run status (Create → Processing → Completed / Failed), plus final video links. Video Data (scene-level tracking) One row per scene with scene script JSON, scene number, image URL, clip links, and per-scene status. This tab enables robust scene retries and progress visibility. --- Triggers Every 30 minutes: processes new rows in Videos where LAUNCH CREATION = Create Every 15 minutes: reprocesses rows in Video Data where LAUNCH = Redo Execute Workflow Trigger: allows orchestration from another workflow --- Error Handling API nodes retry on failure with a 5-second delay Failed image or clip generations are written to Sheets with error details Individual failed scenes can be retried by setting LAUNCH = Redo in Video Data Final stitching runs only after verifying all required scenes are completed --- External Services Kie API — image generation (Nano Banana) and video generation (VEO3) OpenRouter (Claude Opus) — prompt engineering and scene script generation OpenAI (Claude-4o-mini) — image analysis for visual continuity fal.ai — FFmpeg-based clip stitching Google Drive — asset storage and share links Google Sheets — input/output control plane and status tracking --- Usage Add a row in Videos with script, character/setting description, and aspect ratio. Set LAUNCH CREATION to Create. Wait for the scheduled run (or trigger from another workflow). Track scene progress in Video Data. Retrieve final video links in Videos once status is Completed. To retry failed scenes, set scene status to Redo in Video Data.
by Akshay Chug
Overview Stop recording, editing, and posting manually. This workflow takes any topic or idea as input, uses Claude to write a punchy short-form script, ElevenLabs to generate a natural voiceover, and Creatomate to render the finished video with captions and your brand visuals and then stores it in Google Drive and alerts your team. Built for TikTok, Instagram Reels, and YouTube Shorts. How it works Submit a video topic via the built-in form or replace it with a Schedule Trigger to pull topics from a Google Sheet automatically Claude Sonnet writes a 45-60 second script with a strong hook, clear value points, and a call to action ElevenLabs converts the script to a natural-sounding MP3 voiceover in your chosen voice The audio is uploaded to Google Drive and sent to Creatomate, which renders the final video with animated captions and your brand template The workflow waits for Creatomate to finish rendering, then retrieves the completed video file The finished video is uploaded to Google Drive for team access A Slack alert is sent with the Drive link and every run is logged to Google Sheets Setup steps Settings node — Open Configure Brand Settings and fill in your brand name, niche, tone, ElevenLabs Voice ID, Creatomate Template ID, and Drive folder name. This is the only node you need to personalise Claude AI — Add your Anthropic API key to the Claude Sonnet sub-node from console.anthropic.com ElevenLabs — Get your API key from elevenlabs.io and replace YOUR_ELEVENLABS_API_KEY in Generate Voiceover. Find your Voice ID under Voices in ElevenLabs Creatomate — Sign up at creatomate.com, create a short-form video template with Voiceover, Caption, Title, and Brand elements, then add your API key and Template ID Google Drive — Connect your Google account in Upload Audio to Drive and Upload Video to Drive. Create two folders and add their IDs to each node Slack — Connect Slack in Notify Team - Video Ready and set your channel. Right-click and Disable if unused Google Sheets — Create a sheet called Video Log with columns: Timestamp, Video ID, Topic, Platform, Script Preview, Status, Drive Link TEST : Submit a test topic through the form to verify the full pipeline end to end
by Muhammad Nouman
How it works This workflow turns a Google Drive folder into a fully automated YouTube publishing pipeline. Whenever a new video file is added to the folder, the workflow generates all YouTube metadata using AI, uploads the video to your YouTube channel, deletes the original file from Drive, sends a Telegram confirmation, and can optionally post to Instagram and Facebook using permanent system tokens. High-level flow: Detects new video uploads in a specific Google Drive folder. Downloads the file and uses AI to generate: • a polished first-person YouTube description • an SEO-optimized YouTube title • high-ranking YouTube tags Uploads the video to YouTube with the generated metadata. Deletes the original Drive file after upload. Sends a Telegram notification with video details. (Optional) Posts to Instagram & Facebook using permanent system user tokens. Set up steps Setup usually takes a few minutes. Add Google Drive OAuth2 credentials for the trigger and download/delete nodes. Add your OpenAI (or Gemini) API credentials for title/description/tag generation. Add YouTube OAuth2 credentials in the YouTube Upload node. Add Facebook/Instagram Graph API credentials if enabling cross-posting. Replace placeholder IDs (Drive folder ID, Page ID, IG media endpoint). Review sticky notes in the workflow—they contain setup guidance and token info. Activate the Google Drive trigger to start automated uploads.
by Mind-Front
Description: The closest definition to this workflow is a cheaper Modular Version of Perplexity online API empowered by LLM models that outperform the Perplexity Lama Model. This flow provides a seamless way to conduct detailed web searches, extract data, and generate insightful reports based on real-time information. It provides a webhook-based flow that gets any search question and reports back the results via a multi-level web search analysis and domain-specific emulation of an agent to deliver an unbiased expert report. This Flow is Ideal for market research, competitive analysis, or any scenario where actionable, structured insights are needed. A more complete, step-by-step guide is provided within the workflow, ensuring you have all the details to set up and customize each component. This tool is designed to function similarly to Perplexity by performing semantic search, reranking, and follow-up queries. However, it offers a unique advantage—complete customization at every stage. Modify any part of the process, from query refinement to data extraction, allowing you to tailor the workflow to your specific needs. Key Features: AI-Powered Query Generation and Expert Emulation**: Uses Google Gemini to transform user queries into expert-level searches, providing accurate and context-aware results. Dual-Stage Semantic Search with Intelligent Reranking**: Performs an initial search, reranks results, and refines the query based on findings to conduct a second, more targeted search. Top-Result Data Extraction**: Extracts content from the top three results of each search, capturing relevant insights from six total sources. Customizable API Options**: Pre-configured with free APIs (Google Gemini, DuckDuckGo, and Article Extraction APIs) but easily adaptable to other APIs if preferred. Automated, Insightful Reporting**: Synthesizes data into a cohesive report, providing expert-level insights tailored to the user’s query. Instructions for API Setup: This workflow is designed to work with free-tier APIs, offering a cost-effective way to retrieve high-quality data. Here’s how to set up each API, with detailed instructions included in the workflow: Google Gemini API (for Query Generation and Analysis): Visit Google AI Studio and log in. Create a free API key under "Get API Key" → "Create API Key in New Project." The free tier includes up to 15 requests per minute, 1 million tokens per minute, and up to 1,500 requests per day. Brave Search API (for Web Search): To attain the free web search API tier from Brave, follow these steps: Visit api.search.brave.com Create an account Subscribe to the free plan (no charge) Navigate to the API Keys section Generate an API key. For the subscription type, choose "Free". Article Extraction API (for Content Extraction): Register on RapidAPI.com and subscribe to the Article Extraction API. The free plan allows up to 300 extractions per month. Enter your API key in each of the 6 extraction nodes for content retrieval. Alternative: In the workflow, we have provided the full instructions on how to replace the current flow with alternative API Keys and provided suggestions such as Scraper Tech API. Additional Tip: To use other APIs, you can generate a cURL request in RapidAPI’s playground, and then paste it into the HTTP Request node in n8n. This approach streamlines integration by automatically filling in headers and request details. Why Choose This Workflow? The Intelligent Online Web Researcher offers an all-in-one solution for complex, customizable online research. Unlike other tools that provide automated semantic search, this workflow is fully modifiable, allowing you to tailor each step, from the initial query and reranking to data extraction and reporting. With built-in instructions and a structure that’s easy to adapt, it’s ideal for commercial applications that require real-time, high-quality insights. Tags: Online Research, Web Search, Market Analysis, Web Search Automation, Data Extraction, Semantic Search, API Integration, Competitive Intelligence, Business Intelligence, Real-Time Reporting, Web Scrape, Data Crawler, Perplexity
by scrapeless official
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This n8n workflow helps you build a fully automated SEO content engine using Scrapeless and AI. It’s designed for teams running international websites—such as SaaS products, e-commerce platforms, or content-driven businesses—who want to grow targeted search traffic through high-conversion content, without relying on manual research or hit-or-miss topics. The flow runs in three key phases: 🔍 Phase 1: Topic Discovery Automatically find high-potential long-tail keywords based on a seed keyword using Google Trends via Scrapeless. Each keyword is analyzed for trend strength and categorized by priority (P0–P3) with the help of an AI agent. 🧠 Phase 2: Competitor Research For each P0–P2 keyword, the flow performs a Google Search (via Deep SerpAPI) and extracts the top 3 organic results. Scrapeless then crawls each result to extract full article content in clean Markdown. This gives you a structured, comparable view of how competitors are writing about each topic. ✍️ Phase 3: AI Article Generation Using AI (OpenAI or other LLM), the workflow generates a complete SEO article draft, including: SEO title Slug Meta description Trend-based strategy summary Structured JSON-based article body with H2/H3 blocks Finally, the article is stored in Supabase (or any other supported DB), making it ready for review, API-based publishing, or further automation. Set up steps This flow requires intermediate familiarity with n8n and API key setup. Full configuration may take 30–60 minutes. ✅ Prerequisites Scrapeless** account (for Google Trends and web crawling) LLM provider** (e.g. OpenAI or Claude) Supabase* or *Google Sheets** (to store keywords & article output) 🧩 Required Credentials in n8n Scrapeless API Key OpenAI (or other LLM) credentials Supabase or Google Sheets credentials 🔧 Setup Instructions (Simplified) Input Seed Keyword Edit the “Set Seed Keyword” node to define your niche, e.g., "project management". Google Trends via Scrapeless Use Scrapeless to retrieve “related queries” and their interest-over-time data. Trend Analysis with AI Agent AI evaluates each keyword's trend strength and assigns a priority (P0–P3). Filter & Store Keyword Data Group and sort keywords by priority, then store them in Google Sheets. Competitor Research Use Deep SerpAPI to get top 3 Google results. Crawl each using Scrapeless. AI Content Generation Feed competitor content + trend data into AI. Output a structured SEO blog article. Store Final Article Save full article JSON (title, meta, slug, content) to Supabase.
by Blaine Holt
B2B Lead Enrichment | Attio CRM This n8n template automates B2B lead research and enrichment for Attio CRM. It combines data from Apollo.io, LinkedIn scraping, and news sources with AI-powered analysis to generate actionable sales intelligence - turning hours of manual BDR research into minutes. Who is this for? Sales teams using Attio CRM who want to reduce time spent on lead research BDRs/SDRs who need rich prospect context before outreach Revenue operations teams looking to automate CRM enrichment at scale What problem does this workflow solve? Before reaching out to a prospect, sales reps typically spend 15-30 minutes researching company background, recent news, leadership team, and LinkedIn activity. This workflow automates that entire research process, freeing BDRs to focus on relationship building instead of data gathering. How it works Trigger: Manually execute (adapt to webhook or form trigger for automation) Apollo Enrichment: Fetches comprehensive company data by domain Parallel Processing: Three branches run simultaneously: News articles → Tavily extraction → AI summary LinkedIn company page → Scrape Creators → AI summary Leadership search (with web search) → Apollo person lookup → LinkedIn profiles → AI summary Validation: An LLM Critic agent verifies all claims using web search Final Output: Lead Enrichment Agent generates a structured dossier CRM Sync: Updates Attio company and people records Good to Know Estimated API Costs (per enrichment): Apollo.io: Varies by plan (credits-based) Scrape Creators: ~$0.01-0.05 per profile Tavily: ~$0.01 per extraction OpenAI GPT-4o: ~$0.10-0.30 depending on content length Rate Limits: Leadership profiles are processed sequentially to respect API limits. For bulk enrichment, consider adding delays between executions. Requirements Apollo.io account with API access Scrape Creators API key (for LinkedIn scraping) Tavily API key (for article extraction) OpenAI API key (GPT-4o model access) Attio CRM account with API access Setup Import the workflow into n8n Configure credentials for each service: Apollo API (HTTP Header Auth with x-api-key) Scrape Creators API Tavily API OpenAI API Attio API Add these custom fields to your Attio Companies object: positioning (text) conversation_points (text) leadership_conversations (text) enrichment_status (select with "complete" option) Test with a single domain before running at scale Customizing this workflow Trigger: Replace manual trigger with a webhook (real-time enrichment on new leads) or schedule node (batch processing) AI Prompts: Adjust the system prompts in AI agents to match your industry or ideal customer profile Output Fields: Modify the final Code node to map to your specific Attio field structure News Timeframe: Change the 6-month lookback in Apollo:LatestNews to your preferred range Leadership Depth: Adjust the number of leadership profiles to enrich based on your needs Made by www.fenrirlabs.nl
by iamvaar
Project Overview: Automated Climate-Driven HVAC Upsell & AI Concierge This project is specifically built for an HVAC business to automatically upsell to old customers when their locality has a heatwave or snow wave forecast in the upcoming five days. Prerequisites & Setup 1. GoHighLevel (GHL) Create Custom Fields:** stop_whatsapp: Used when a user replies "STOP" to remove them from the marketing list. opp_type: To track the campaign type (e.g., heatwave or snowwave). Create Two Pipelines:** Pipeline A: HEATWAVE Pipeline B: SNOWWAVE Note: Both pipelines require 4 stages: New Lead, Contacted, Scheduled, and Closed. Grab the Calendar ID:** Keep your GHL Calendar ID handy, as the workflow will need it to search for free slots and book appointments. 2. WhatsApp (Meta Business Suite) Create and approve two marketing templates for proactive outreach: A. Heatwave Template > Hello {{1}}, > With temperatures expected to rise soon, we wanted to share a few tips to keep your home comfortable and your AC running efficiently. > Maintenance Tips: > • Keep blinds closed during peak sun hours. > • Check your air filters; a clean filter prevents overworking. > • If you leave the house, raise the thermostat a few degrees rather than turning it off. > Need help? > If your system is struggling to keep up, we are here to assist. > Stay cool and safe! B. Snow Wave Template > Hello {{1}}, > With a cold front and freezing temperatures expected soon, we wanted to share a few tips to keep your home warm and your heating system running efficiently. > Winter Comfort Tips: > • Keep curtains and blinds open during the day to let sunlight naturally warm your home, then close them at night to trap the heat. > • Check your air filters; a clogged filter makes your heater work much harder in freezing weather. > • Ensure your outdoor vents and heat pump units are clear of snow or debris to maintain proper airflow. > Need help? > If your heating system is struggling to stay warm or making unusual noises, we are here to assist. > Stay warm and safe! 3. API Integrations Nominatim OpenStreetMap API:** Review the documentation. This open-source tool will be used to extract exact cities from customer street addresses. WeatherAPI:** Obtain a free API key. Add this to your workflow's generic credentials (Type: Query Auth > Name: key > Value: your-api-key). Gemini API:** Obtain your API key to power the AI Service Concierge. Part 1: The Climate-Driven Lead Generation Engine (Proactive Outreach) This sub-workflow acts as a proactive scraper. It monitors your CRM contacts, cross-references their locations with live weather data, and triggers targeted upsell campaigns. 1. Schedule Trigger & Fetch Contacts Schedule Trigger:** Kicks off the workflow every morning at 7:00 AM. Fetch Contacts (HighLevel):** Pulls your entire list of previous customers and leads from GoHighLevel. 2. Geocoding & Data Cleaning If Node (City Set):** Checks if the CRM contact already has a city populated. Nominatim API (Loop & Fetch):** If a city is missing, the workflow runs the address through the Nominatim OpenStreetMap API to extract the exact city. Update Contact (HighLevel):** Saves the extracted city back to the GHL contact profile to prevent redundant geocoding in the future. 3. Weather Data Aggregation Code Node (Group by City):** A vital step to optimize API usage. Instead of making 1,000 separate calls for 1,000 contacts, custom JavaScript groups all contacts by their respective cities. HTTP Request (Fetch Forecast):** Pings WeatherAPI.com to grab the 5-day forecast for each unique city. 4. Hazard Detection & Routing Code Node (Detect Weather Hazards):** A script evaluates the 5-day forecast against dynamic, seasonal temperature thresholds (e.g., a "heatwave" threshold in May might be >85°F, but >95°F in August). It tags the grouped contacts with a campaign type (HEATWAVE or SNOWWAVE). If Node (Check Campaign Type):** Routes the qualified leads into the appropriate pipeline logic. 5. CRM Execution & WhatsApp Outreach Create Opportunity (HighLevel):** Drops the qualified lead into the "New Lead" stage of the respective GHL pipeline. Send Template (WhatsApp):** Dispatches the pre-approved Meta marketing template to the customer. Update & Upsert (HighLevel):** Moves the Opportunity to the "Contacted" stage and updates the opp_type custom field so the system tracks the reason for outreach. Part 2: The AI-Powered Service Concierge (Inbound Handling) When a customer replies to the proactive blast (e.g., "My AC is making a weird noise, can someone come out?"), this sub-workflow seamlessly takes over to assist the customer and autonomously book an appointment. 1. Trigger & Validation Trigger (WhatsApp Message Received):** Listens for inbound replies from customers. Fetch & Validate (HighLevel):** Looks up the sender's phone number in GHL. If the number does not exist in the CRM, the workflow ignores the message to prevent spam handling. 2. The Opt-Out Filter If Node (Stop Command):** Scans the inbound message for the keyword "STOP". Upsert Contact (HighLevel):** If "STOP" is detected, the workflow immediately updates the user's stop_whatsapp custom field to TRUE, excluding them from all future blasts, and terminates the flow. 3. The Agentic Core Customer Service AI Agent (LangChain + Gemini):** If the user is requesting assistance, the message is routed to an AI Agent powered by the Gemini Chat Model. Redis Chat History Memory:** Connects to a Redis instance so the AI retains conversation context, which is crucial for natural, back-and-forth scheduling. Agent Tools (HighLevel Integration):** The Gemini agent is equipped with specific tools it can trigger autonomously: Fetch Available Calendar Slots: The AI is strictly instructed to check live GHL availability before suggesting times to the user. Book Calendar Appointment: Automatically secures the timeslot in GHL if the user agrees. Close Deal: If the user declines service ("I'm good, no thanks"), the AI triggers this tool to mark the GHL opportunity as "Closed/Lost". Update Pipeline Stage: If an appointment is successfully booked, the AI moves the pipeline stage to "Scheduled" without any manual human intervention. 4. Final Response Send Response (WhatsApp):** The AI formulates a conversational, friendly reply—utilizing WhatsApp's native formatting like bolding and bullet points—and sends it back to the customer to confirm the action taken.