Browse 2,095 Workflows

By Oneclick AI Squad

Quick overview This workflow powers a chat-based shopping assistant using OpenAI for conversation, an HTTP product-catalog search API for live item data, and a checkout/order API to place orders with explicit user approval, then posts the final order status to a Slack channel. How it works Triggers from an n8n Chat Trigger (or a manual test run) when a user submits a shopping request. Uses OpenAI (GPT-4.1-mini) with short-term memory and function calling to query a product-catalog search API for real-time price and availability before recommending up to three items. Parses the agent’s structured JSON response into a reply, an optional product shortlist, and a purchase-intent signal with selected product and quantity. If there is no purchase intent, returns the direct reply message; if there is purchase intent, pauses for the user to confirm the product selection via a resume webhook. Pauses again for an explicit purchase approval via a second resume webhook, then submits the order to the store checkout API with the selected item, quantity, customer, payment method, and shipping details. Waits for an asynchronous order-confirmation callback via a third resume webhook, then formats the order status and posts it to Slack. Setup Add credentials for OpenAI, Slack, and HTTP Header Auth for both the product-catalog search API and the checkout/order API. Update the configuration values for catalog and order base URLs, currency, customer ID, default shipping address, payment method ID, max budget, and the target Slack channel. Copy the resume webhook URLs from the selection, approval, and order-confirmation wait steps and wire them into your chat UI buttons and your store/payment provider’s order-status callback. An n8n automation workflow template by Oneclick AI Squad.

By May Zhan

Quick Overview This workflow manually runs through a list of websites in Google Sheets, maps each site with the Firecrawl Map API to discover project/content URLs, and writes the filtered results back to Google Sheets while marking each source site as Done or Error. How it works Starts when you manually execute the workflow in n8n. Reads the list of sites from the “Sites” sheet in Google Sheets and keeps only rows where the Status field is empty. Processes each unprocessed site one by one and normalizes the site name and domain for downstream steps. Calls the Firecrawl Map endpoint to crawl the site and return a list of discovered links. Filters the returned links to keep only likely project/portfolio pages and saves them to the “Mapped URLs” sheet in Google Sheets. Updates the original site row in the “Sites” sheet to Status = Done, or logs the error to “Mapped URLs” and sets Status = Error, then waits 20 seconds before continuing to the next site. Setup Create a Google Sheet with a “Sites” sheet that includes at least Name, Website, and Status columns, and a “Mapped URLs” sheet with Name, Home Domain, Mapped URL, and Error Message columns. Add Google Sheets credentials in n8n and replace YOUR_GOOGLE_SHEET_ID with your spreadsheet ID in all Google Sheets steps. Add an HTTP Header Auth credential for Firecrawl (API key) and ensure it is selected for the Firecrawl Map request. Review the URL filtering rules (skip fragments/extensions and work/project path fragments) to match the URL patterns you consider valid project pages. Adjust the Firecrawl map settings (for example limit, includeSubdomains, and timeout) and the 20-second wait time to fit your rate limits and crawl volume. An n8n automation workflow template by May Zhan.

By Dahiana

Quick overview This workflow collects a job posting URL via an n8n form, extracts key requirements with OpenRouter, then rewrites your resume and drafts a tailored cover letter and saves both into a new Google Doc (optionally moved to a chosen Google Drive folder). How it works Receives a job posting URL (and optional notes) from an n8n form. Downloads the job posting web page and extracts the page body text. Uses OpenRouter to extract structured job details such as title, company, skills, responsibilities, and ATS keywords from the page text. Uses OpenRouter to rewrite your base resume so it truthfully aligns with the extracted requirements and target keywords. Uses OpenRouter to draft a specific cover letter that references real accomplishments from your base resume and the job’s responsibilities. Creates a new Google Doc titled with the role and company, inserts the tailored resume and cover letter, and moves the file to your selected Google Drive folder. Setup Update the candidate details and paste your full base resume text in the Candidate Profile section. Add an OpenRouter API credential and select it for both OpenRouter model nodes. Add Google Docs OAuth2 credentials for creating and updating documents. Add Google Drive OAuth2 credentials and set the destination folder URL (or remove the move step if you want to keep the doc in My Drive root). Use the form’s production URL to submit a job posting link from your source site. An n8n automation workflow template by Dahiana.

By Salman Mehboob

Quick overview This workflow uses an n8n Chat UI plus OpenRouter (Claude Sonnet) to generate and iteratively edit a single-page local business website, serve a live HTML preview, and publish the approved page to a Hostinger subdomain, while archiving versions to a Data Table, Google Drive, and Google Sheets. How it works Receives a message in the n8n Chat UI and uses OpenRouter (Claude Sonnet) to extract a business brief and decide whether to reply, build a site, or publish. When building, loads the latest saved HTML version for the current chat session and asks OpenRouter (Claude Sonnet) to generate or apply edits to a complete index.html. Cleans the model output into raw HTML, generates a preview URL, and saves a new version (with status) to an n8n Data Table. Archives the generated HTML to Google Drive and appends a run log (including preview URL and Drive link) to Google Sheets. Replies in chat with the preview link and instructions to request edits or approve publishing. Serves GET /preview/:siteId by loading the latest HTML from the Data Table, injecting a fixed “Publish Live/Update Website” bar, and returning the page as text/html. Handles POST /publish/:siteId by creating a Hostinger subdomain via API, uploading the HTML via FTP, updating the Data Table row to “deployed” with the live URL, and returning a JSON confirmation. Setup Add an OpenRouter API credential (or swap to your preferred LLM provider) for both the intake and builder chat model nodes. Create an n8n Data Table for generated sites/versions (siteId, sessionId, businessName, subdomainSlug, html, brief_object, status, version, liveUrl) and select it in all Data Table steps. Add Google Drive OAuth and Google Sheets OAuth credentials, then set the target Drive folder ID and the Google Sheets document ID/sheet name used for logging. Add Hostinger credentials: an HTTP Bearer token for the Hostinger API subdomain endpoint and FTP credentials for uploading to /public_html//index.html. Update the hardcoded PREVIEW_BASE and PUBLISH_BASE URLs inside the code steps to match your Preview and Publish webhook production URLs, and replace the domain used to build live URLs if you are not using dripranks.com. Additional info Read the main sticky it has complete details and setup guide. Contact Email: salmanmehboob1947@gmail.com linkedin: https://www.linkedin.com/in/salman-mehboob-pro/. An n8n automation workflow template by Salman Mehboob.

By Thomas Abraham

Quick Overview This workflow collects n8n Form submissions, uses OpenAI (GPT-4o-mini) to score each lead from 1–10 with reasoning, posts hot leads (score ≥ 7) to Slack, and appends all scored leads to Google Sheets for tracking. How it works Triggers when a new submission is received from an n8n Form. Sends the submitted details to OpenAI (GPT-4o-mini) to generate a 1–10 lead score and brief reasoning. Extracts the numeric score and reasoning from the OpenAI response and structures the lead record. Checks whether the lead score is 7 or higher. Posts a formatted hot-lead alert to a selected Slack channel when the score is 7+. Appends the lead details, score, and reasoning to a Google Sheets spreadsheet for logging. Setup Add an OpenAI credential for the OpenAI Chat Model node. Add a Slack credential and replace the channel selection (e.g., the channel ID) used for hot-lead alerts. Add a Google Sheets OAuth credential and set the target Spreadsheet ID and sheet/tab for logging. Update the lead-scoring prompt text if you want different criteria or a different “hot lead” threshold. An n8n automation workflow template by Thomas Abraham.

By Sundar Raghavan

Quick Overview This workflow receives an n8n Chat message, uses Amazon Bedrock AgentCore to triage it and route it to one of three specialist agents that share customer memory, then posts the specialist’s reply to a Slack channel. How it works Receives a new message in n8n Chat and starts a run for that chat input. Sets customer context values including the agent name, the customer/actor ID derived from the chat session, the question text, and the target Slack channel. Sends the question to an Amazon Bedrock AgentCore triage agent that classifies the request as analysis, advice, or research and provisions a shared harness with managed memory if needed. Parses and validates the triage agent’s JSON output, falls back to the research category when parsing fails, and passes along the shared harness ARN. Routes the request to the matching Amazon Bedrock AgentCore specialist (Analysis with code interpreter, Architecture with AWS skills, or Research) using the same harness ARN and actor ID so the team shares per-customer memory. Cleans up the specialist response and posts a formatted message to Slack indicating which specialist answered and the customer ID. Setup Create an Amazon Bedrock AgentCore API credential and select it on the triage and all three specialist AgentCore nodes. Create a Slack OAuth credential, set the Slack channel name in the customer context (for example, #support), and invite the Slack app/bot to that channel. Open the n8n Chat for this workflow (hosted chat) and send a message to generate a triage decision and a specialist reply. An n8n automation workflow template by Sundar Raghavan.

By Dr. Firas

Quick overview This workflow manually scrapes Facebook Ad Library results via apify, filters for high-like advertisers, analyzes video/image/text ads with OpenAI (vision + text), and appends a strategic summary plus rewritten ad copy for each ad to Google Sheets. How it works Starts when you run the workflow manually. Sends your keyword, country, status, and limit settings to an apify Facebook Ad Library scraper API to fetch recent ads and their details. Filters out ads from advertisers whose Facebook page likes are below the configured minimum. Routes each remaining ad into video, image, or text-only processing based on which creative fields are present. For video and image ads, uses OpenAI Vision to describe the ad creative (video cover frame or image) and then uses OpenAI to generate a structured strategic analysis and a rewritten version of the ad copy. For text-only ads, uses OpenAI to generate the same structured strategic analysis and rewritten ad copy from the scraped ad data. Appends each analysis result to a Google Sheets spreadsheet for tracking and review. Setup Add an apify API token as an HTTP Header Auth credential and ensure you have access to the Apify actor used by the Facebook Ad Library scraper request. Add an OpenAI API credential with access to the configured vision and chat models, and update the model IDs in the configuration if needed. Connect Google Sheets OAuth2 credentials and select the target spreadsheet and sheet in each of the three Google Sheets append steps. Adjust the configuration values (search keywords, country, active status, minimum page likes, and max ads) to match the competitors and markets you want to monitor. Additional info Analyze competitor Facebook ads with Apify and OpenAI 📥 Open full documentation on Notion Need help customizing? Contact me for consulting and support : Linkedin MY NEW YOUTUBE CHANNEL 👉 Subscribe to my new YouTube channel. Here I'll share videos and Shorts with practical tutorials and FREE templates for n8n. An n8n automation workflow template by Dr. Firas.

By Dr. Firas

Quick overview This workflow collects public Instagram usernames through an n8n form, scrapes profile and recent post metrics using Apify’s Instagram Profile Scraper, then upserts the results (including engagement rate and a high-profile flag) into a Google Sheets table. How it works Receives Instagram usernames submitted through an n8n form (comma- or newline-separated). Normalizes the input into a clean username list and sets run parameters like the Apify actor and how many recent posts to analyze. Sends a single batched request to the Apify Instagram Profile Scraper API to retrieve profile details and latest post stats. Detects whether each returned item contains valid profile data and formats records into a consistent schema for scraped vs. private/not-found outcomes. Captures Apify request failures and formats an error record with a clear status and timestamp. Merges all outcomes and appends or updates rows in Google Sheets so reruns update existing usernames instead of creating duplicates. Setup Add an Apify API token as an HTTP Header Auth credential (Authorization: Bearer ) and select it in the Apify request step. Connect a Google Sheets OAuth2 credential, then select the target spreadsheet and the “Profiles” sheet (or create them). Ensure the sheet has columns matching the logged fields (for example: username, fullName, followersCount, followsCount, biography, profilePicUrl, externalUrl, isPrivate, isVerified, postsCount, latestPostCaption, latestPostLikes, latestPostComments, engagementRatePercent, isHighProfile, status, scrapedAt). Review the configuration values (Apify actor slug, resultsLimit/max posts, and the follower threshold used to flag high-profile accounts) to match your needs. Additional info Scrape Instagram profiles and log them to Google Sheets 📥 Open full documentation on Notion Need help customizing? Contact me for consulting and support : Linkedin MY NEW YOUTUBE CHANNEL 👉 Subscribe to my new YouTube channel. Here I'll share videos and Shorts with practical tutorials and FREE templates for n8n. An n8n automation workflow template by Dr. Firas.

By Dr. Firas

Quick overview This workflow receives inbound WhatsApp messages via Whapi, screens them with OpenAI-powered guardrails, and replies using an OpenAI support agent that can search a Notion knowledge base, look up live WooCommerce orders/products/customers, and escalate complex cases to a human via Gmail. How it works Receives an incoming WhatsApp message via a webhook endpoint configured in Whapi. Extracts key settings and message fields (sender phone, type, text, thresholds, and escalation email) and stops non-text requests by replying with a “text only” message. Uses OpenAI guardrails to detect jailbreak attempts, NSFW content, and off-topic requests, and sends a policy-violation reply when the message is unsafe. Passes safe customer messages to an OpenAI agent with conversation memory keyed to the customer phone number. The agent answers by searching policies and FAQs in Notion and fetching real-time order, product, and customer data from WooCommerce when needed. If the agent decides the issue needs a human, it emails the escalation details to the support manager through Gmail. Sends the agent’s final response back to the customer on WhatsApp via the Whapi API. Setup Create a Whapi account, connect your WhatsApp number, and configure Whapi to POST incoming messages to this workflow’s webhook URL. Add OpenAI API credentials and choose the model to use in the workflow’s configuration values. Add WooCommerce REST API credentials (consumer key/secret) and ensure your store API access is enabled. Add a Notion API connection and ensure your support knowledge base exists as searchable Notion pages. Add a Gmail OAuth2 connection and set the support manager email address in the Configuration values for escalations. Additional info Handle e-commerce customer support on WhatsApp with AI, WooCommerce and Notion 📥 Open full documentation on Notion Need help customizing? Contact me for consulting and support : Linkedin MY NEW YOUTUBE CHANNEL 👉 Subscribe to my new YouTube channel. Here I'll share videos and Shorts with practical tutorials and FREE templates for n8n. An n8n automation workflow template by Dr. Firas.

By Dr. Firas

Quick overview This workflow indexes a product brochure PDF into an in-memory vector store and then responds to incoming WhatsApp text, voice, image, and video messages using OpenAI and Google Gemini, with per-customer chat memory and retrieval-augmented answers from the catalogue. How it works Runs manually to download a product brochure PDF, extract its text, split it into chunks, generate OpenAI embeddings, and index everything into an in-memory vector store. Triggers when a new WhatsApp message arrives and loads the workflow configuration (models, prompts, phone number ID, and vector store key). Routes the message by type and converts non-text inputs into text by transcribing audio with OpenAI, describing images with OpenAI Vision, or describing videos with Google Gemini. Normalizes the customer input (message text, captions, and sender number) into a single prompt for the sales agent. Uses an OpenAI chat model with per-customer memory and a vector-store retrieval tool to answer questions grounded in the indexed product catalogue. Sends the agent’s reply back to the customer via WhatsApp, or returns a predefined message for unsupported WhatsApp message types. Setup Create and connect credentials for WhatsApp Business Cloud (trigger + send/media access), OpenAI (chat, embeddings, transcription, and vision), and Google Gemini (video analysis). Set a public direct URL to your product brochure/catalogue PDF in the knowledge base settings and run the manual indexing branch whenever the catalogue changes. Fill in your WhatsApp Business phone number ID, choose your OpenAI/Gemini model IDs, and adjust the system prompt and limits in the configuration fields before activating the workflow. Additional info Build a WhatsApp Sales Agent that understands text, voice, photos and videos with RAG 📥 Open full documentation on Notion Need help customizing? Contact me for consulting and support : Linkedin MY NEW YOUTUBE CHANNEL 👉 Subscribe to my new YouTube channel. Here I'll share videos and Shorts with practical tutorials and FREE templates for n8n. An n8n automation workflow template by Dr. Firas.

By Youssef

Quick overview This workflow collects a CSV/XLSX/XLS campaign file via an n8n form, validates each row, then uploads images to PinFlow and schedules posts for Pinterest, Instagram, and Facebook at a defined interval (default 5 hours). How it works Receives a file upload through an authenticated n8n form along with the file format, posting interval in hours, and an optional first publish timestamp. Parses the uploaded file as CSV, XLSX, or XLS based on the selected format and converts each row into an item. Validates required fields (HTTPS image URL and either title or description) and assigns a scheduled time per row using either scheduled_at or an interval-based schedule starting from the provided first publish time. Processes the campaign one row at a time, downloading the row’s image from the provided URL. Uploads the downloaded image to PinFlow media storage and uses the returned media URL. Schedules a Pinterest pin, then an Instagram post, then a Facebook post in PinFlow using the row’s text, link, and computed scheduled time. Setup Create and assign a PinFlow credential for the PinFlow nodes. Fill in your PinFlow targets: Pinterest profile ID and board ID, Instagram profile ID, and Facebook page ID. Prepare a spreadsheet with required columns (image_url and at least one of title or description) and optional columns (destination_url, instagram_caption, facebook_message, scheduled_at). Enable basic authentication on the form and share the form URL with anyone who should upload campaign files. Requirements Pinflow node. An n8n automation workflow template by Youssef.

By Salim BRAHMI

Quick Overview This workflow indexes a product backlog PDF into a Supabase vector store and lets users query it from Slack using a slash command, with Google Gemini embeddings for retrieval and an OpenRouter chat model to generate answers. How it works Receives a form submission with a product backlog PDF upload. Extracts text from the PDF and generates embeddings with Google Gemini before inserting the content into a Supabase vector store table. Loads default documents and embeddings to initialize the same Supabase knowledge base. Receives a Slack slash command request and immediately returns an in-channel “search in progress” acknowledgment. Sends the Slack question to an OpenRouter chat model–powered RAG agent, which uses Google Gemini embeddings to retrieve relevant backlog passages from Supabase. Posts the final, Slack-formatted answer back to the originating channel using Slack’s response_url. Setup Configure the n8n form trigger (or share it) so users can upload a PDF file for indexing. Add a Supabase API credential and ensure a vector store table named backlog_documents exists (or update the table name in both Supabase nodes). Add a Google Gemini (PaLM) API credential for the embeddings nodes. Add an OpenRouter API credential and select the target model in the chat model node. Create a Slack slash command that sends POST requests to the workflow webhook path /backlog-query and use the generated webhook URL in Slack. An n8n automation workflow template by Salim BRAHMI.