by Miha
This n8n template drafts customer-ready email replies using Google Gemini, enriched with HubSpot context (contact, deals, companies, tickets). Each draft is routed to Slack for one-click approval before it’s sent from Gmail—so you move fast without losing control. Ideal for support and sales teams that want speedy, personalized responses while keeping humans in the loop. How it works Gmail Trigger** watches for new inbound emails. Sender filter** excludes internal domains (e.g., n8n.io) to avoid auto-replying to teammates. HubSpot contact lookup* finds the sender and fetches associated *deals/companies/tickets** via association + batch read. CRM context is normalized** into clean, LLM-friendly fields (no IDs or sensitive noise). Gemini (Google AI Studio)** generates a concise, friendly reply using: Sender name, subject, and message snippet Safe, relevant HubSpot context (e.g., top 1–2 deals or an open ticket) Style constraints (≤ \~150 words, single CTA, optional clarifying question) Slack approval* posts the draft to a channel; if *approved, n8n **replies via Gmail in the original thread. How to use Gmail: Connect the same account for the trigger and reply nodes. HubSpot: Connect OAuth on the search + HTTP request nodes. Gemini: Add your Google AI Studio API key to the Google Gemini Chat Model node. Slack: Connect and select the channel for draft approvals. (Optional) Filter: Adjust the Allowed Sender filter before going live. (Optional) Prompt: Edit “Draft Reply (AI Agent)” tone/length or how much CRM detail to include. Activate the workflow. New emails will produce Slack-approved replies automatically. Requirements Gmail** (trigger + send) HubSpot** (OAuth2) for contact + associations Slack** for approval step Google Gemini** (Google AI Studio API key) Notes & customization Safety rails:** The prompt avoids exposing IDs/raw JSON and caps CRM details to what’s useful. Auto-send mode:** Skip Slack if you want fully automated replies for specific senders/labels. Richer context:** Extend the batch read to pull more properties (e.g., next step, renewal date). Triage:** Branch on subject/labels to route billing vs. technical requests to different prompts. QA queue:* If the model asks a clarifying question, keep it to *one**—the node enforces that.
by yu-ya
Schedule and optimize social media posts to Twitter and LinkedIn using AI This workflow automates the entire lifecycle of social media management—from fetching draft content to AI-driven optimization and multi-platform publishing. Who’s it for Social media managers, marketing teams, and content creators who use Google Sheets to plan their content but want to leverage AI for better engagement and automate the repetitive task of cross-platform posting. How it works The workflow is triggered either hourly or manually via a webhook. It fetches scheduled content from a designated Google Sheet and identifies posts ready for publication. An AI Agent (OpenAI) then analyzes the raw content to generate two optimized versions: a punchy, character-limited post for Twitter and a more professional, detailed version for LinkedIn. After generating relevant hashtags and engagement tips, the workflow publishes the posts simultaneously. Finally, it logs the live URLs back to your spreadsheet and sends a performance summary to a Slack channel for easy tracking. How to set up Google Sheet: Create a sheet with columns for status, content, platforms, scheduled_time, hashtags, and tone. Credentials: Connect your Google Sheets, OpenAI, Twitter (X), LinkedIn, and Slack accounts. Node Configuration: Select your specific spreadsheet and worksheet in both the "Fetch Content" and "Update Content" nodes. Slack: Specify the channel name or ID in the Slack node to receive notifications. Activation: Test with the Manual Webhook, then toggle the workflow to "Active." Requirements Google Sheets OAuth2** OpenAI API Key** (using GPT-4o-mini or higher) Twitter (X) OAuth2** LinkedIn OAuth2** Slack Bot Token** How to customize the workflow AI Tone**: Modify the "System Message" in the AI Content Optimizer node to match your brand's unique voice. Additional Platforms**: Extend the branching logic after the AI Parse node to include platforms like Discord, Facebook, or Mastodon. Advanced Scheduling**: Adjust the Filter node's JavaScript code if you use a different date format or status labels in your spreadsheet.
by Servify
This n8n template demonstrates how to build an autonomous AI assistant that handles real business tasks through natural conversation on Telegram. The example shows meeting scheduling with CRM lookup and calendar management, but the architecture supports any business automation you can imagine - simply add tools and the AI learns to use them automatically. Use cases are many: Try automating appointment scheduling, customer support tickets, invoice generation, lead qualification, email management, report generation, data entry, or task coordination! Good to know OpenAI API costs are minimal at ~$0.001 per conversation with GPT-4o-mini The AI agent makes autonomous decisions and can chain multiple tool calls to complete complex tasks Conversation context is not persisted between sessions (can be extended with a memory database) Calendar availability is checked for business hours (9 AM - 4 PM) by default The workflow assumes contacts are stored in Google Sheets with Name and Email columns This is production-ready code that can be deployed immediately for real business use How it works User sends a natural language message to the Telegram bot requesting a meeting The workflow extracts message content, chat ID, and user information CRM database is loaded from Google Sheets containing contact information The AI agent analyzes the request and autonomously decides which tools to use AI searches CRM for contacts, checks Google Calendar availability, and proposes 3 available time slots User confirms their preferred time through conversational reply Upon confirmation, the workflow creates a Google Calendar event with both parties invited A professional confirmation email is automatically sent via Gmail to the meeting attendee The entire multi-step process executes autonomously through simple conversation How to use Set up a Google Sheet as your CRM with columns: Name, Email, Phone Create a Telegram bot via BotFather and get your bot token Import this workflow and connect your credentials (Telegram, OpenAI, Google Sheets, Calendar, Gmail) Replace placeholder IDs with your actual Google Sheet ID and Calendar ID in the workflow nodes Activate the workflow to start listening for Telegram messages Test with: "Schedule a meeting with [contact name] tomorrow at 2 PM" Customize the AI Agent system prompt to match your scheduling preferences and timezone Requirements Telegram Bot Token (free from BotFather) OpenAI API account with GPT-4o-mini access Google Sheets OAuth2 credentials for CRM database access Google Calendar OAuth2 credentials for availability checking and event creation Gmail OAuth2 credentials for sending confirmation emails Customising this workflow Add new tools (APIs, databases, services) and the AI automatically learns to use them - no code changes needed Replace Telegram with Slack, WhatsApp, or SMS for different communication channels Extend capabilities beyond scheduling: invoice generation, customer support, lead qualification, report generation Connect external systems like HubSpot, Salesforce, QuickBooks, Asana, or custom APIs Add conversation memory by integrating a vector database for context-aware multi-turn conversations Implement approval workflows where AI drafts actions for human review before execution Build multiple specialized assistants with different tools and expertise for various business functions
by Juan Carlos Cavero Gracia
This automation workflow is designed for e-commerce businesses, digital marketers, and entrepreneurs who need to create high-quality promotional content for their products quickly and efficiently. From a single product image and description, the system automatically generates 4 promotional carousel-style images, perfect for social media, advertising campaigns, or web catalogs. Note: This workflow uses Gemini 2.5 Flash API for image generation, imgbb for image storage, and upload-post.com for automatic Instagram, Tiktok, Facebook and Youtube publishing* Who Is This For? E-commerce Owners:** Transform basic product photos into professional promotional content featuring real people using products in authentic situations. Digital Marketers & Agencies:** Generate multiple advertising content variations for Facebook Ads, Instagram Stories, and digital marketing campaigns. Small Businesses & Entrepreneurs:** Create professional promotional material without expensive photo shoots or graphic designers. Social Media Managers:** Produce engaging and authentic content that drives engagement and conversions across all social platforms. What Problem Does This Workflow Solve? Creating quality promotional content requires time, resources, and design skills. This workflow addresses these challenges by: Automatic Carousel Generation:** Converts a single product photo into 4 promotional images featuring people using the product naturally. Authentic & Engaging Content:** Generates images showing real product usage, increasing credibility and conversions. Integrated Promotional Text:** Automatically includes visible offers, benefits, and call-to-actions in the images. Social Media Optimization:** Produces vertical 9:16 format images, perfect for Instagram, TikTok, and Facebook Stories. Automatic Publishing:** Optionally publishes the complete carousel directly to Instagram with AI-generated optimized descriptions. How It Works Product Upload: Upload a product image and provide detailed description through the web form. Smart Analysis: The AI agent analyzes the product and creates a storyboard of 4 different promotional images. Image Generation: Gemini 2.5 Flash generates 4 variations showing people using the product in authentic contexts. Automatic Processing: Images are automatically processed, optimized, and stored in imgbb. Promotional Description: GPT-4 generates an attractive, social media-optimized description based on the created images. Optional Publishing: The system can automatically publish the complete carousel to Instagram. Setup fal.ai Credentials: Sign up at fal.ai and add your API token to the Gemini 2.5 Flash nodes. imgbb API: Create an account at imgbb.com Get your API key and configure it in the "Set APIs Vars" node Upload-Post (Optional): For automatic Instagram publishing: Register your account at upload-post.com Connect your Instagram business account Configure credentials in the "Upload Post" node OpenAI API: Configure your OpenAI API key for promotional description generation. Requirements Accounts:** n8n, fal.ai, imgbb.com, OpenAI, upload-post.com (optional), Instagram business (optional). API Keys:** fal.ai token, imgbb API key, OpenAI API key, upload-post.com credentials. Image Format:** Any standard image format (JPG, PNG, WebP) of the product to promote. Features Advanced Generative AI:** Uses Gemini 2.5 Flash to create realistic images of people using products Smart Storyboard:** Automatically creates 4 different concepts to maximize engagement Integrated Promotional Text:** Includes offers, benefits, and CTAs directly in the images Optimized Format:** Generates vertical 9:16 images perfect for social media Parallel Processing:** Generates all 4 images simultaneously for maximum efficiency Automatic Publishing:** Option to publish directly to Instagram with optimized descriptions Use this template to transform basic product photos into complete promotional campaigns, saving time and resources while generating high-quality content that converts visitors into customers.
by Avkash Kakdiya
How it works This workflow automatically generates personalized follow-up messages for leads or customers after key interactions (e.g., demos, sales calls). It enriches contact details from HubSpot (or optionally Monday.com), uses AI to draft a professional follow-up email, and distributes it across multiple communication channels (Slack, Telegram, Teams) as reminders for the sales team. Step-by-step 1. Trigger & Input Schedule Trigger – Runs automatically at a defined interval (e.g., daily). Set Sample Data – Captures the contact’s name, email, and context from the last interaction (e.g., “had a product demo yesterday and showed strong interest”). 2. Contact Enrichment HubSpot Contact Lookup – Searches HubSpot CRM by email to confirm or enrich contact details. Monday.com Contact Fetch (Optional) – Can pull additional CRM details if enabled. 3. AI Message Generation AI Language Model (OpenAI) – Provides the underlying engine for message creation. Generate Follow-Up Message – Drafts a short, professional, and friendly follow-up email: References previous interaction context. Suggests clear next steps (call, resources, etc.). Ends with a standardized signature block for consistency. 4. Multi-Channel Communication Slack Reminder – Posts the generated message as a reminder in the sales team’s Slack channel. Telegram Reminder – Sends the follow-up draft to a Telegram chat. Teams Reminder – Shares the same message in a Microsoft Teams channel. Benefits Personalized Outreach at Scale – AI ensures each follow-up feels tailored and professional. Context-Aware Messaging – Pulls in CRM details and past interactions for relevance. Cross-Platform Delivery – Distributes reminders via Slack, Teams, and Telegram so no follow-up is missed. Time-Saving for Sales Teams – Eliminates manual drafting of repetitive follow-up emails. Consistent Branding – Ensures every message includes a unified signature block.
by explorium
Inbound Agent - AI-Powered Lead Qualification with Product Usage Intelligence This n8n workflow automatically qualifies and scores inbound leads by combining their product usage patterns with deep company intelligence. The workflow pulls new leads from your CRM, analyzes which API endpoints they've been testing, enriches them with firmographic data, and generates comprehensive qualification reports with personalized talking points—giving your sales team everything they need to prioritize and convert high-quality leads. DEMO Template Demo Credentials Required To use this workflow, set up the following credentials in your n8n environment: Salesforce Type:** OAuth2 or Username/Password Used for:** Pulling lead reports and creating follow-up tasks Alternative CRM options: HubSpot, Zoho, Pipedrive Get credentials at Salesforce Setup Databricks (or Analytics Platform) Type:** HTTP Request with Bearer Token Header:** Authorization Value:** Bearer YOUR_DATABRICKS_TOKEN Used for:** Querying product usage and API endpoint data Alternative options: Datadog, Mixpanel, Amplitude, custom data warehouse Explorium API Type:** Generic Header Auth Header:** Authorization Value:** Bearer YOUR_API_KEY Used for:** Business matching and firmographic enrichment Get your API key at Explorium Dashboard Explorium MCP Type:** HTTP Header Auth Used for:** Real-time company intelligence and supplemental research Connect to: https://mcp.explorium.ai/mcp Anthropic API Type:** API Key Used for:** AI-powered lead qualification and analysis Get your API key at Anthropic Console Go to Settings → Credentials, create these credentials, and assign them in the respective nodes before running the workflow. Workflow Overview Node 1: When clicking 'Execute workflow' Manual trigger that initiates the lead qualification process. Type:** Manual Trigger Purpose:** On-demand execution for testing or manual runs Alternative Trigger Options: Schedule Trigger:** Run automatically (hourly, daily, weekly) Webhook:** Trigger on CRM updates or new lead events CRM Trigger:** Real-time activation when leads are created Node 2: GET SF Report Pulls lead data from a pre-configured Salesforce report. Method:** GET Endpoint:** Salesforce Analytics Reports API Authentication:** Salesforce OAuth2 Returns: Raw Salesforce report data including: Lead contact information Company names Lead source and status Created dates Custom fields CRM Alternatives: This node can be replaced with HubSpot, Zoho, or any CRM's reporting API. Node 3: Extract Records Parses the Salesforce report structure and extracts individual lead records. Extraction Logic: Navigates report's factMap['T!T'].rows structure Maps data cells to named fields Node 4: Extract Tenant Names Prepares tenant identifiers for usage data queries. Purpose: Formats tenant names as SQL-compatible strings for the Databricks query Output: Comma-separated, quoted list: 'tenant1', 'tenant2', 'tenant3' Node 5: Query Databricks Queries your analytics platform to retrieve API usage data for each lead. Method:** POST Endpoint:** /api/2.0/sql/statements Authentication:** Bearer token in headers Warehouse ID:** Your Databricks cluster ID Platform Alternatives: Datadog:** Query logs via Logs API Mixpanel:** Event segmentation API Amplitude:** Behavioral cohorts API Custom Warehouse:** PostgreSQL, Snowflake, BigQuery queries Node 6: Split Out Splits the Databricks result array into individual items for processing. Field:** result.data_array Purpose:** Transform single response with multiple rows into separate items Node 7: Rename Keys Normalizes column names from database query to readable field names. Mapping: 0 → TenantNames 1 → endpoints 2 → endpointsNum Node 8: Extract Business Names Prepares company names for Explorium enrichment. Node 9: Loop Over Items Iterates through each company for individual enrichment. Node 10: Explorium API: Match Businesses Matches company names to Explorium's business entity database. Method:** POST Endpoint:** /v1/businesses/match Authentication:** Header Auth (Bearer token) Returns: business_id: Unique Explorium identifier matched_businesses: Array of potential matches Match confidence scores Node 11: Explorium API: Firmographics Enriches matched businesses with comprehensive company data. Method:** POST Endpoint:** /v1/businesses/firmographics/bulk_enrich Authentication:** Header Auth (Bearer token) Returns: Company name, website, description Industry categories (NAICS, SIC, LinkedIn) Size: employee count range, revenue range Location: headquarters address, city, region, country Company age and founding information Social profiles: LinkedIn, Twitter Logo and branding assets Node 12: Merge Combines API usage data with firmographic enrichment data. Node 13: Organize Data as Items Structures merged data into clean, standardized lead objects. Data Organization: Maps API usage by tenant name Maps enrichment data by company name Combines with original lead information Creates complete lead profile for analysis Node 14: Loop Over Items1 Iterates through each qualified lead for AI analysis. Batch Size:** 1 (analyzes leads individually) Purpose:** Generate personalized qualification reports Node 15: Get many accounts1 Fetches the associated Salesforce account for context. Resource:** Account Operation:** Get All Filter:** Match by company name Limit:** 1 record Purpose: Link lead qualification back to Salesforce account for task creation Node 16: AI Agent Analyzes each lead to generate comprehensive qualification reports. Input Data: Lead contact information API usage patterns (which endpoints tested) Firmographic data (company profile) Lead source and status Analysis Process: Evaluates lead quality based on usage, company fit, and signals Identifies which Explorium APIs the lead explored Assesses company size, industry, and potential value Detects quality signals (legitimate company email, active usage) and red flags Determines optimal sales approach and timing Connected to Explorium MCP for supplemental company research if needed Output: Structured qualification report with: Lead Score:** High Priority, Medium Priority, Low Priority, or Nurture Quick Summary:** Executive overview of lead potential API Usage Analysis:** Endpoints used, usage insights, potential use case Company Profile:** Overview, fit assessment, potential value Quality Signals:** Positive indicators and concerns Recommended Actions:** Next steps, timing, and approach Talking Points:** Personalized conversation starters based on actual API usage Node 18: Clean Outputs Formats the AI qualification report for Salesforce task creation. Node 19: Update Salesforce Records Creates follow-up tasks in Salesforce with qualification intelligence. Resource:** Task Operation:** Create Authentication:** Salesforce OAuth2 Alternative Output Options: HubSpot:** Create tasks or update deal stages Outreach/SalesLoft:** Add to sequences with custom messaging Slack:** Send qualification reports to sales channels Email:** Send reports to account owners Google Sheets:** Log qualified leads for tracking Workflow Flow Summary Trigger: Manual execution or scheduled run Pull Leads: Fetch new/updated leads from Salesforce report Extract: Parse lead records and tenant identifiers Query Usage: Retrieve API endpoint usage data from analytics platform Prepare: Format data for enrichment Match: Identify companies in Explorium database Enrich: Pull comprehensive firmographic data Merge: Combine usage patterns with company intelligence Organize: Structure complete lead profiles Analyze: AI evaluates each lead with quality scoring Format: Structure qualification reports for CRM Create Tasks: Automatically populate Salesforce with actionable intelligence This workflow eliminates manual lead research and qualification, automatically analyzing product engagement patterns alongside company fit to help sales teams prioritize and personalize their outreach to the highest-value inbound leads. Customization Options Flexible Triggers Replace the manual trigger with: Schedule:** Run hourly/daily to continuously qualify new leads Webhook:** Real-time qualification when leads are created CRM Trigger:** Activate on specific lead status changes Analytics Platform Integration The Databricks query can be adapted for: Datadog:** Query application logs and events Mixpanel:** Analyze user behavior and feature adoption Amplitude:** Track product engagement metrics Custom Databases:** PostgreSQL, MySQL, Snowflake, BigQuery CRM Flexibility Works with multiple CRMs: Salesforce:** Full integration (pull reports, create tasks) HubSpot:** Contact properties and deal updates Zoho:** Lead enrichment and task creation Pipedrive:** Deal qualification and activity creation Enrichment Depth Add more Explorium endpoints: Technographics:** Tech stack and product usage News & Events:** Recent company announcements Funding Data:** Investment rounds and financial events Hiring Signals:** Job postings and growth indicators Output Destinations Route qualification reports to: CRM Updates:** Salesforce, HubSpot (update lead scores/fields) Task Creation:** Any CRM task/activity system Team Notifications:** Slack, Microsoft Teams, Email Sales Tools:** Outreach, SalesLoft, Salesloft sequences Reporting:** Google Sheets, Data Studio dashboards AI Model Options Swap AI providers: Default: Anthropic Claude (Sonnet 4) Alternatives: OpenAI GPT-4, Google Gemini Setup Notes Salesforce Report Configuration: Create a report with required fields (name, email, company, tenant ID) and use its API endpoint Tenant Identification: Ensure your product usage data includes identifiers that link to CRM leads Usage Data Query: Customize the SQL query to match your database schema and table structure MCP Configuration: Explorium MCP requires Header Auth—configure credentials properly Lead Scoring Logic: Adjust AI system prompts to match your ideal customer profile and qualification criteria Task Assignment: Configure Salesforce task assignment rules or add logic to route to specific sales reps This workflow acts as an intelligent lead qualification system that combines behavioral signals (what they're testing) with firmographic fit (who they are) to give sales teams actionable intelligence for every inbound lead.
by Intuz
This n8n template from Intuz provides a complete end-to-end content factory to automate the entire lifecycle of creating and publishing AI-driven videos. It transforms a single text prompt into a fully scripted, visually rich video with AI-generated images and voiceovers, then distributes it across multiple social media platforms. Who's this workflow for? Content Creators & YouTubers Social Media Managers & Agencies Digital Marketers & Entrepreneurs Brands looking to scale video content production Objective Generate viral video scripts with Gemini AI (via LangChain). Break scripts into structured scenes(hooks, retention, CTA). Create image prompts and high-quality background visuals automatically. Store all scenes, prompts, images, and metadata into Airtable. Handle file formatting, uploads, and naming automatically. Add error handling and retry logic for smooth execution. Uploading into Social Media platforms. How it works 1. AI Script Generation: The workflow starts with a single command. A powerful Google Gemini AI model, acting as a "Content Brain," generates a complete, viral video script with a title, description, and multiple scenes. 2. Content Management in Airtable: The entire script is broken down and saved systematically into an Airtable base, which acts as the central Content Management System (CMS) for the video production pipeline. 3. AI Image Generation: The workflow loops through each scene in Airtable. It uses an AI agent to enhance the image prompts and sends them to an image generation API (like Pollinations.ai) to create a unique, high-quality image for each scene. These images are then automatically uploaded back into Airtable. 4. Automated Video Rendering: Once all images are ready, the workflow gathers the script text and the corresponding image URLs from Airtable and sends them to Creatomate. Creatomate uses a pre-defined template to assemble the final video, complete with AI-generated voiceovers for each scene. 5. Multi-Platform Publishing: After a brief wait for the video to render, the workflow retrieves the final video file and automatically publishes it across your connected social media channels, including YouTube and Instagram. Key Requirements to Use This Template Before you start, please ensure you have the following accounts and assets ready: 1. n8n Instance & Required Nodes: An active n8n account (Cloud or self-hosted). This workflow relies on the official n8n LangChain integration (@n8n/n8n-nodes-langchain). If you are using a self-hosted version of n8n, please ensure this package is installed on your instance. 2. AI & Video Accounts: Google Gemini AI Account: A Google Cloud account with the Vertex AI API enabled and an API Key. Creatomate Account: It's platform to generate videos. An account with Creatomate for video rendering, and your API key and a pre-designed video template ID. 3. Content & Social Media Accounts: Airtable Account: An Airtable base set up to manage the video content. Using the complementary Airtable template is highly recommended. YouTube Account: A YouTube channel with API access enabled via Google Cloud Console. Upload-Post.com Account: An account for posting to other platforms like Instagram. Workflow Steps 1.▶️ Trigger (Manual/Auto) Start workflow manually or via schedule. 2.🧠 Content Brain (Gemini + LangChain) Role-trained viral strategist prompt. Generates 6 scene scripts with: Hook → Retention → Value → CTA. Follows viral content rules (engagement triggers, curiosity gaps, shareable moments). 3.📑 Structured Output Parser Enforces JSON schema: video_id video_title description scenes[] → scene_number, text, image_prompt 4.📄 Airtable – Store Scenes Each scene stored with: Video ID, Title, Description Scene Number & Text Image Prompt & Generated Image link 5.🤖 AI Agent – Image Prompt Creator Transforms scene text →optimized image prompts using structured rules. 6.🎨 Pollination AI – Image Generation Generates vertical 9:16 visuals with parameters: Model: flux Resolution: 1080x1920 Steps: 12 Guidance Scale: 3.5 Safety Checker: Enabled Options: seed=42, nologo=true 7.📂 File Handling & Conversion Assigns filenames automatically (e.g., images_001.png). Converts binary image → base64 for Airtable storage. 8.📤 Airtable Upload – Store Images Attaches generated visuals directly into Generated Image field. 9.⚡ Switch & Error Handling Branches for: ✅ Success → continue ❌ Failed → stop with error message ⏳ Processing → wait/retry 10.Social Media Upload In YouTube via YouTube API from official documentation In Instagram Via Upload Post API Setup Instructions 1. AI Configuration: In the Google Gemini Chat Model nodes, connect your Google Gemini API account. In the Content Brain node, you can customize the core prompt to change the video's niche, style, or topic. 2. Airtable Setup (Crucial): Connect your Airtable account in the Airtable nodes. Set up your Airtable base using the provided template or ensure your base has identical table and field names. Update the Base ID and Table IDs in the Airtable nodes. Airtable Schema: 3. Video Rendering Setup (Creatomate): In the Video Rendering - Creatomate node, add your Creatomate API key to the header authorization. In the Template for Creatomate node, replace the template_id with the ID of your own video template from your Creatomate account. 4. Social Media Connections: In the Upload on YouTube node, connect your YouTube account via OAuth2. In the Upload on Instagram node, replace the API key in the header authorization with your key from Upload-Post.com. 5. Execute the Workflow: Click "Execute workflow" to kick off your automated video content factory. 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
by Madame AI
Automate social media content aggregation to a Telegram channel This n8n template automatically aggregates and analyzes key updates from your social media platforms Home Page, delivering them as curated posts to a Telegram channel. This workflow is perfect for digital marketers, brand managers, or data analysts and Busy people, seeking to monitor real-time trends and competitor activity without manual effort. How it works The workflow is triggered automatically on a schedule to aggregate the latest social media posts. A series of If and Wait nodes monitor the data processing job until the full data is ready. An AI Agent, powered by Google Gemini, refines the content by summarizing posts and removing duplicates. An If node checks for an image in the post to decide if a photo or a text message should be sent. Finally, the curated posts are sent to your Telegram channel as rich media messages. How to use Set up BrowserAct Template: In your BrowserAct account, set up “Twitter/X Content Aggregation” template. Set up Credentials: Add your credentials for BrowserAct In Run Node , Google Gemini in Agent Node, and Telegram in Send Node. Add Workflow ID: Change the workflow_id value inside the HTTP Request inside the Run Node, to match the one from your BrowserAct workflow. Activate Workflow: To enable the automated schedule, simply activate the workflow. Requirements BrowserAct** API account BrowserAct* *“Twitter/X Content Aggregation”** Template Gemini** account Telegram** credentials customizing this workflow This workflow provides a powerful foundation for social media monitoring. You could: Replace the Telegram node with an email or Slack node to send notifications to a different platform. Add more detailed prompts to the AI Agent for more specific analysis or summarization. customize BrowserAct Workflow to reach your desire. Need Help ? How to Find Your BrowseAct API Key & Workflow ID How to Connect n8n to Browseract How to Use & Customize BrowserAct Templates Workflow Guidance and Showcase Automate Your Social Media: Get All X/Twitter Updates Directly in Telegram!
by Bhuvanesh R
Your Cold Email is Now Researched. This pipeline finds specific bottlenecks on prospect websites and instantly crafts an irresistible pitch 🎯 Problem Statement Traditional high-volume cold email outreach is stuck on generic personalization (e.g., "Love your website!"). Sales teams, especially those selling high-value AI Receptionists, struggle to efficiently find the one Unique Operational Hook (like manual scheduling dependency or high call volume) needed to make the pitch relevant. This forces reliance on expensive, slow manual research, leading to low reply rates and inefficient spending on bulk outreach tools. ✨ Solution This workflow deploys a resilient Dual-AI Personalization Pipeline that runs on a batch basis. It uses the Filter (Qualified Leads) node as a cost-saving Quality Gate to prevent processing bad leads. It executes a Targeted Deep Dive on successful leads, using GPT-4 for analytical insight extraction and Claude Sonnet for coherent, human-like copy generation. The entire process outputs campaign-ready data directly to Google Sheets and sends a critical QA Draft via Gmail. ⚙️ How It Works (Multi-Step Execution) 1\. Ingestion and Cost Control (The Quality Gate) Trigger and Ingestion:* The workflow starts via a *Manual Trigger, pulling leads directly from **Get All Leads (Google Sheets). Cost Filtering:* The *Filter (Qualified Leads)** node removes leads that lack a working email or website URL. Execution Isolation:* The *Loop Over Leads* node initiates individual processing. The *Capture Lead Data (Set)** node immediately captures and locks down the original lead context for stability throughout the loop. Hybrid Scraping:* The *Scrape Site (HTTP Request)* and *Extract Text & Links (HTML)* nodes execute the *Hybrid Scraping* strategy, simultaneously capturing *website text* and *external links**. Data Shaping & Status:* The *Filter Social & Status (Code)* node is the control center. It filters links, bundles the context, and critically, assigns a *status** of 'Success' or 'Scrape Fail'. Cost Control Branch:* The *If (IF node)* checks this status. Items with 'Scrape Fail' bypass all AI steps (saving *100% of AI token costs) and jump directly to **Log Final Result. Successful items proceed to the AI core. 2\. Dual-AI Coherence & Dispatch (The Executive Output) Analytical Synthesis:* The *Summarize Website (OpenAI)* node uses *GPT-4* to synthesize the full context and extract the *Unique Operational Hook** (e.g., manual booking overhead). Coherent Copy Generation:* The *Generate Subject & Body (Anthropic)* node uses the *Claude Sonnet* model to generate the subject and the multi-line body, guaranteeing *coherence** by creating both simultaneously in a single JSON output. Final Parsing:* The *Parse AI Output (Code)* node reliably strips markdown wrappers and extracts the clean *subject* and *body** strings. Final Delivery:* The data is logged via *Log Final Result (Google Sheets), and the completed email is sent to the user via **Create a draft (Gmail) for final Quality Assurance before sending. 🛠️ Setup Steps Before running the workflow, ensure these credentials and data structures are correctly configured: Credentials Anthropic:** Configure credentials for the Language Model (Claude Sonnet). OpenAI:** Configure credentials for the Analytical Model (GPT-4/GPT-4o). Google Services:* Set up OAuth2 credentials for *Google Sheets* (Input/Output) and *Gmail** (Draft QA and Completion Alert). Configuration Google Sheet Setup:* Your input sheet must include the columns *email, **website\_url, and an empty Icebreaker column for initial filtering. HTTP URL:* Verify that the *Scrape Site** node's URL parameter is set to pull the website URL from the stabilized data structure: ={{ $json.website\_url }}. AI Prompts:** Ensure the Anthropic prompt contains your current Irresistible Sales Offer and the required nested JSON output structure. ✅ Benefits Coherence Guarantee:* A single *Anthropic** node generates both the subject and body, guaranteeing the message is perfectly aligned and hits the same unique insight. Maximum Cost Control:* The *IF node* prevents spending tokens on bad or broken websites, making the campaign highly *budget-efficient**. Deep Personalization:* Combines *website text* and *social media links**, creating an icebreaker that implies thorough, manual research. High Reliability:* Uses robust *Code nodes** for data structuring and parsing, ensuring the workflow runs consistently under real-world conditions without crashing. Zero-Risk QA:* The final *Gmail (Create a draft)** step ensures human review of the generated copy before any cold emails are sent out.
by Muhammad Farooq Iqbal
This n8n template demonstrates how to create authentic-looking User Generated Content (UGC) advertisements using AI image generation, voice synthesis, and lip-sync technology. The workflow transforms product images into realistic customer testimonial videos that mimic genuine user reviews and social media content. Use cases are many: Generate authentic UGC-style ads for social media campaigns, create customer testimonial videos without hiring influencers, produce localized UGC content for different markets, automate TikTok/Instagram-style product reviews, or scale UGC ad production for e-commerce brands! Good to know The workflow creates UGC-style content that appears genuine and authentic Uses multiple AI services: OpenAI GPT-4o for analysis, ElevenLabs for voice synthesis, and WaveSpeed AI for image generation and lip-sync Voice synthesis costs vary by ElevenLabs plan (typically $0.18-$0.30 per 1K characters) WaveSpeed AI pricing: ~$0.039 per image generation, additional costs for lip-sync processing Processing time: ~3-5 minutes per complete UGC video Optimized for Malaysian-English content but easily adaptable for global markets How it works Product Input: The Telegram bot receives product images to create UGC ads for AI Analysis: ChatGPT-4o analyzes the product to understand brand, colors, and target demographics UGC Content Creation: AI generates authentic-sounding testimonial scripts and detailed prompts for realistic customer scenarios Character Generation: WaveSpeed AI creates believable customer avatars that look like real users reviewing products Voice Synthesis: ElevenLabs generates natural, conversational audio using gender-appropriate voice models UGC Video Production: WaveSpeed AI combines generated characters with audio to create TikTok/Instagram-style review videos Content Delivery: Final UGC videos are delivered via Telegram, ready for social media posting The workflow produces UGC-style content that maintains authenticity while showcasing products in realistic, relatable scenarios that resonate with target audiences. How to use Setup Credentials: Configure OpenAI API, ElevenLabs API, WaveSpeed AI API, Cloudinary, and Telegram Bot credentials Deploy Workflow: Import the template and activate the workflow Send Product Images: Use the Telegram bot to send product images you want to create UGC ads for Automatic UGC Generation: The workflow will automatically create authentic-looking customer testimonial videos Receive UGC Content: Get both testimonial images and final UGC videos ready for social media campaigns Pro tip: The workflow automatically detects product demographics and creates appropriate customer personas. For best UGC results, use clear product images that show the item in use. Requirements OpenAI API** account for GPT-4o product analysis and UGC script generation ElevenLabs API** account for authentic voice synthesis (requires voice cloning credits) WaveSpeed AI API** account for realistic character generation and lip-sync processing Cloudinary** account for UGC content storage and hosting Telegram Bot** setup for content input and delivery n8n** instance (cloud or self-hosted) Customizing this workflow Platform-Specific UGC: Modify prompts to create UGC content optimized for TikTok, Instagram Reels, YouTube Shorts, or Facebook Stories. Brand Voice: Adjust testimonial scripts and character personas to match your brand's target audience and tone. Regional Adaptation: Customize language, cultural references, and character demographics for different markets and demographics. UGC Style Variations: Create different UGC formats - unboxing videos, before/after comparisons, day-in-the-life content, or product demonstrations. Influencer Personas: Develop specific customer personas (age groups, lifestyles, interests) to create targeted UGC content for different audience segments. Content Scaling: Set up batch processing to generate multiple UGC variations for A/B testing different approaches and styles.
by zawanah
Categorise and route emails with GPT 5 This workflow demonstrates how to use AI text classifier to classify incoming emails, and uses a multi-agent architecture to respond for each email category respectively. Use cases Business owners with a lot of incoming emails, or anyone who has huge influx of emails How it Works Any incoming emails will be read by the text classifier powered by GPT 5, and routed according to the defined categories where respective agents will take next steps. Workflow is triggered when an email comes in GPT will read email's "subject","from" and "content" to route it accurately to respective designated categories For customer support enquiries, customer support agent will take knowledge from the pinecone vector database about FAQs and policies, reply via gmail, and label the email as "Customer Support" For finance-related queries, finance agent will label email as "Finance" and assess if email is about making payment or receiving from customers. If payment-related, email will be sent to the payments team to take action. If receipts-related, email will be sent to the receivables team to take action. User will be notified via telegram after any email is sent. For sales/leads enquiries, leads agent will label the email as "Sales Opportunities", take knowledge from the pinecone vector database about the business to generate a response and draft into gmail and user will be notified via telegram to review and send. If there is lack of information for agent to generate a response, user will be notified of this via telegram as well. Any internal team member emails will be routed to the internal agent. The agent will label message as "Internal" and send user a summary of the email message via telegram. How to set up Set up Telegram bot via Botfather. See setup instructions here Setup OpenAI API for transcription services (Credits required) here Set up Openrouter account. See details here Set up Pinecone database. See details here Customization Options Other than Gmail, it is possible to connect to Outlook as well. Other than Pinecone vector database, there are other vector database that should serve the same purpose eg. supabase, qdrant, weviate Requirements Gmail account Telegram bot Pinecone account Open router account
by Pratyush Kumar Jha
Video → Newsletter AI Agent This n8n workflow converts a YouTube video into a polished, email-ready newsletter. It scrapes the transcript, extracts a thumbnail/logo and brand color theme, uses multiple AI agents to (1) clean & summarize the transcript into three newsletter sections, (2) convert that content into a styled HTML newsletter (color-aware), then saves the draft to Google Sheets and sends the email to subscribers via Gmail. The flow is optimized for batch sending and brand-consistent HTML output. How it works (step-by-step) Trigger — On form submission accepts Brand Name, Brand Website, and YouTube video link. Site scrape & colour study — HTTP requests + Information Extractor → AI agent derives brand color theme (primary/secondary/accent/background). Transcript retrieval — Two YouTube transcript scrapers (Apify acts) fetch the video transcript and thumbnail; a small Code node merges transcript chunks. Summarization & journalism — AI Agent2 (LangChain/Gemini) cleans the transcript, extracts thesis + key points, and writes 3 newsletter sections in a journalistic tone. HTML conversion — Convert Newsletter to HTML (AI) agent applies the fixed layout and injects only text color variables (keeps layout intact) and outputs Subject + HTML body (≤1000 words). Aggregate & merge — Merge + Aggregate assemble files, assets, and parsed outputs. Save & send — Save the email draft to Google Sheets (Save Newsletter Draft in Google Sheet) and loop through subscribers from a subscribers sheet; Sending Emails to all the Subscribers (Gmail node) sends the HTML to each address in batches. Batching & looping — Split In Batches handles large subscriber lists; Loop Over Items triggers the HTML-conversion per recipient batch. Quick Setup Guide 👉 Demo & Setup Video 👉 Sheet Template 👉 Course Nodes of interest On form submission (formTrigger) — entry point for video + brand inputs. You Tube Transcript Scraper, You Tube Transcript Scraper1 (HTTP Request → Apify) — transcript + thumbnail fetching. Information Extractor & AI Agent1 — website color/theme extraction. Code in JavaScript — merges transcript pieces into a single text payload. AI Agent2 (LangChain agent + Gemini Chat Model) — transcript → journalist-style newsletter sections. Convert Newsletter to HTML (AI) (LangChain agent + Structured Output Parser) — builds constrained, brand-aware HTML email and subject. Structured Output Parser1/2 — enforce schemas for color theme / structured outputs. Get row(s) in sheet & Save Newsletter Draft in Google Sheet (Google Sheets) — subscriber list + draft storage. Loop Over Items / Split In Batches — batch processing for sends. Sending Emails to all the Subscribers (Gmail) — SMTP/OAuth send. OpenRouter Chat Model — LM compute provider configured in the workflow. What you’ll need (credentials & resources) Google Sheets OAuth2 (for reading subscribers & saving drafts). Gmail OAuth2 (for sending HTML emails). Gemini / LLM provider credentials (Gemini API key or equivalent) for the LangChain agents. Apify API key (for the YouTube transcript scrapers). ConvertAPI (or similar) key if you convert logos (SVG→PNG) server-side. Host storage / publicly accessible URLs for images (thumbnails, logos) or a file-store (S3). Optional: SendGrid / Mailgun credentials if you swap Gmail for a transactional email provider. Security note: do NOT hardcode credentials in node parameters; use n8n credentials manager or environment variables. Recommended settings & best practices Batch size & rate-limits:** set Split In Batches to a conservative batch size (e.g., 50–200) and add delays between batches to avoid provider rate limits and Gmail throttling. Retries & timeouts:** enable retries for HTTP Request nodes and set sensible timeouts (e.g., 30–60s). Use exponential backoff. LM controls:** set token/response length limits and max_output_tokens (or equivalent) to avoid runaway costs; enforce the 1000-word HTML hard limit in the prompt. Validation:** validate the YouTube URL and that transcript content exists before invoking AI summarization (fail fast with a clear error). Schema enforcement:** use Structured Output Parser nodes with strict JSON schemas to prevent malformed outputs. Testing:** run with a small subscriber test sheet and use a safety test Gmail account before sending to production lists. Logging & monitoring:** log each run (video URL, subject, send count, errors) to a monitoring sheet or external logging service. Privacy & compliance:** ensure recipients have consent to receive emails (store opt-ins); include unsubscribe handling if you move beyond one-off sends. Comply with CAN-SPAM / local laws. Credential rotation:** rotate API keys periodically and revoke compromised tokens. Content safety:** instruct the LM agents to avoid hallucinated citations — only include links you can verify. Customization ideas Multi-language support: auto-detect video language and run summarizer in that language. A/B subject testing: generate 2–3 subject lines and send variations to subsets. Scheduling: add a scheduler node to delay sends or publish at optimal send-times per recipient timezone. Integrate with SendGrid/Mailgun for higher throughput and analytics (opens/clicks). Add personalization tokens (first name, company) from subscribers sheet to the HTML (merge fields). Auto-attach transcript as plain-text footer or include “Read more” link to a hosted full article. Add analytics: record opens, clicks, and engagement back into Google Sheets or a database. Support other platforms: ingest videos from Vimeo, Loom, or uploaded MP4s. Use a templating engine to allow multiple newsletter layouts and style variants. Auto-generate social posts (Twitter/X, LinkedIn) from the newsletter summary. Tags n8n newsletter youtube transcript langchain gemini apify gmail google-sheets html-email automation batching ai content-ops