by Daniel Shashko
AI Customer Support Triage with Gmail, OpenAI, Airtable & Slack How it Works This workflow monitors your Gmail support inbox every minute, automatically sending each unread email to OpenAI for intelligent analysis. The AI evaluates sentiment (Positive/Neutral/Negative/Critical), urgency level (Low/Medium/High/Critical), categorizes requests (Technical/Billing/Feature Request/Bug Report/General), extracts key issues, and generates professional response templates. The system calculates a priority score (0-110) by combining urgency and sentiment weights, then routes tickets accordingly. Critical issues trigger immediate Slack alerts with full context and 30-minute SLA reminders, while routine tickets post to standard monitoring channels. Every ticket logs to Airtable with complete analysis and thread tracking, then updates a Google Sheets dashboard for real-time analytics. A secondary AI pass generates strategic insights (trend identification, risk assessment, actionable recommendations) and stores them back in Airtable. The entire process takes seconds from email arrival to team notification, eliminating manual triage and ensuring critical issues get immediate attention. Who is this for? Customer support teams needing automated prioritization for high email volumes SaaS companies tracking support metrics and response times Startups with lean teams requiring intelligent ticket routing E-commerce businesses managing technical, billing, and return inquiries Support managers needing data-driven insights into customer pain points Setup Steps Setup time:** 20-30 minutes Requirements:** Gmail, OpenAI API key, Airtable account, Google Sheets, Slack workspace Monitor Support Emails: Connect Gmail via OAuth2, configure INBOX monitoring for unread emails AI Analysis Engine: Add OpenAI API key, system prompt pre-configured for support analysis Parse & Enrich Data: JavaScript code automatically calculates priority scores (no changes needed) Route by Urgency: Configure routing rules for critical vs routine tickets Slack Alerts: Create Slack app, get bot token and channel IDs, replace placeholders in nodes Airtable Database: Create base with "tblSupportTickets" table, add API key and Base ID (replace appXXXXXXXXXXXXXX) Google Sheets Dashboard: Create spreadsheet, enable Sheets API, add OAuth2 credentials, replace Sheet ID (1XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX) Generate Insights: Second OpenAI call analyzes patterns, stores insights in Airtable Test: Send test email, verify Slack alerts, check Airtable/Sheets data logging Customization Guidance Priority Scoring:** Adjust urgency weight (25) and sentiment weight (10) in Code node to match your SLA requirements Categories:** Modify AI system prompt to add industry-specific categories (e.g., healthcare: appointments, prescriptions) Routing Rules:** Add paths for High urgency, VIP customers, or specific categories Auto-Responses:** Insert Gmail send node after routine tickets for automatic acknowledgment emails Multi-Language:** Add Google Translate node for non-English support VIP Detection:** Query CRM APIs or match email domains to flag enterprise customers Team Assignment:** Route different categories to dedicated Slack channels by department Cost Optimization:** Use GPT-3.5 (~$0.001/email) instead of GPT-4, self-host n8n for unlimited executions Once configured, this workflow operates as your intelligent support triage layer—analyzing every email instantly, routing urgent issues to the right team, maintaining comprehensive analytics, and generating strategic insights to improve support operations. Built by Daniel Shashko Connect on LinkedIn
by Yanagi Chinatsu
Who's it for? This template is perfect for teams, communities, or anyone who wants a fun, automated way to remember and celebrate birthdays. If you love space and want to make someone's special day a little more cosmic, this is for you. It's a great way to boost morale and ensure no one's birthday is forgotten. How it works / What it does The workflow runs automatically every morning. It reads a list of birthdays from your Google Sheet and checks if any match the current date. If a match is found, it fetches the latest Earth image from NASA's EPIC API and uses an AI model to generate a unique, space-themed birthday greeting. Finally, it sends a personalized HTML email to the birthday person and posts a celebratory message in your designated Slack channel. Requirements A Google Sheet with columns for Name, Email, and Birthday (in a format like YYYY-MM-DD). Credentials for Google Sheets, Gmail, OpenAI, and Slack configured in your n8n instance. How to set up Configure Credentials: Add your API credentials for Google (for both Sheets and Gmail), OpenAI, and Slack in the respective nodes. Set Up Google Sheet: In the "Get Birthday Roster" node, enter your Google Sheet ID and the name of the sheet where the birthday list is stored. Configure Slack: In the "Post Slack Notification" node, select the channel where you want birthday announcements to be posted. Activate Workflow: Save and activate the workflow. It will now run automatically every day! How to customize the workflow Change the schedule: Modify the CRON expression in the "Every Morning at 7:00" node to change when the workflow runs. Adjust the AI prompt: Edit the system message in the "Generate Space Birthday Message" node to alter the tone, length, or style of the AI-generated greetings. Customize the email design: Modify the HTML in the "Send Birthday Email" node to change the look and feel of the birthday message.
by WeblineIndia
Google Sheets + Twelve Data + Groq AI Stock Risk Alert Workflow > Smart Stock Risk Alerts in Minutes This workflow automatically reads your stock portfolio from Google Sheets, fetches real-time prices via API, calculates risk metrics (price drops and volatility) and sends AI-generated email alerts only when risks are detected. It helps you stay informed without being overwhelmed by unnecessary notifications. Quick Implementation Steps Connect your Google Sheets account and prepare your portfolio sheet. Add your Twelve Data API key in the HTTP Request node. Connect your Gmail account for sending alerts. Configure thresholds in the Edit Fields – Config & Thresholds node. Set up a Cron (Schedule Trigger) instead of manual execution. Run the workflow and monitor alerts. What It Does This workflow automates stock portfolio monitoring by combining spreadsheet data, real-time market prices and AI-powered summaries. It reads your portfolio data from Google Sheets and processes each stock by fetching its current market price through an external API. Once the data is enriched, the workflow calculates key risk indicators such as percentage price change and volatility. Based on predefined thresholds, it flags stocks that may require attention. Instead of sending raw data, it uses an AI model to generate a clean, human-readable summary. The workflow ensures efficiency by sending alerts only when necessary, reducing noise and helping you focus on meaningful risks. Who It's For Retail investors tracking personal portfolios Financial analysts monitoring stock risks Traders who want automated alerts Anyone using Google Sheets for stock tracking Users looking to integrate AI into financial workflows Requirements To use this workflow, you need: n8n account (self-hosted or cloud) Google Sheets account** (OAuth2 connection required) Gmail account** (OAuth2 connection required) Twelve Data API key** (mandatory) Groq API access** (for AI summary generation) How It Works & Setup Guide Step 1: Prepare Google Sheets Use a sheet named: Portfolio Range: A:E Required columns (in order): | Column | Field Name | Description | |--------|-------------|-------------| | A | symbol | Stock ticker (e.g., AAPL) | | B | avg_price | Average purchase price | | C | quantity | Number of shares | | D | sector | Industry sector | | E | notes | Optional notes | Step 2: Connect Google Sheets Open Read Portfolio from Google Sheets node Authenticate using Google OAuth2 Ensure: Sheet ID is correct Range is set to Portfolio!A:E Step 3: Configure API (MANDATORY) ⚠️ This is a required setup step. The workflow will NOT work without it. Open Fetch Stock Prices node Update URL: Replace YOUR_API_KEY with your Twelve Data API key Step 4: Configure Email Alerts (MANDATORY) ⚠️ You must configure the recipient email manually. Open Send Risk Alert Notification node Set: sendTo → your email address Subject is already set: Daily Stock Risk Alert Step 5: Configure Thresholds Open Edit Fields – Config & Thresholds node Default values: drop_threshold = -5 → triggers alert if price drops ≥ 5% volatility_threshold = 3 → triggers alert if volatility ≥ 3% Adjust these based on your risk tolerance. Step 6: Enable Scheduling The workflow is designed for scheduled execution. Replace Manual Trigger with Cron Node Example schedule: Daily at 9 AM Every hour during market hours Step 7: Execute Workflow Run once manually for testing Activate workflow for automation How It Works (Flow Summary) Reads portfolio data from Google Sheets Adds configuration thresholds Loops through each stock Fetches real-time prices (with delay to avoid rate limits) Merges portfolio + price data Computes: Price change % Volatility Flags risky stocks Filters only flagged items Formats data into readable text Uses AI (Groq model) to generate summary Sends email alert How To Customize Nodes Edit Fields – Config & Thresholds** Adjust sensitivity of alerts Wait 8 Seconds Before request** Modify delay based on API rate limits Compute Risk Logic** Add new conditions (e.g., stop-loss, sector-based alerts) Generate Risk Summary** Customize prompt for different tone or format Send Risk Alert Notification** Change subject or email structure Add-ons (Extend This Workflow) Add Slack/Telegram alerts instead of email Store alerts in a database (PostgreSQL / Airtable) Add historical tracking & charts Integrate multiple APIs for redundancy Add portfolio performance analytics dashboard Enable multi-user alerts Use Case Examples Daily Portfolio Monitoring Automatically receive alerts for risky stocks each day Intraday Risk Tracking Run hourly to track sudden market movements High Volatility Detection Identify stocks with unstable price behavior Loss Prevention Alerts Get notified when stocks drop beyond safe thresholds Sector-Based Monitoring Track risk exposure across industries There can be many more use cases depending on how you customize thresholds and logic. Troubleshooting Guide | Issue | Possible Cause | Solution | |------|--------------|----------| | No data fetched from Google Sheets | Incorrect sheet ID or range | Verify Sheet ID and Portfolio!A:E | | API not returning prices | Missing API key | Add apikey in HTTP Request node | | Workflow stops unexpectedly | API rate limit | Increase wait time | | No email received | sendTo field empty | Add recipient email | | No alerts triggered | Thresholds too strict | Adjust drop/volatility values | | AI summary not generated | Groq API issue | Check API credentials | | Incorrect risk calculation | Data format issue | Ensure numeric values in sheet | Need Help? If you need assistance with: Setting up this workflow Customizing risk logic Adding advanced features Integrating additional APIs Building similar automation workflows We’re here to help! 👉 Contact our n8n developes at WeblineIndia for expert support in building scalable, AI-powered automation solutions tailored to your needs.
by Rahul Joshi
Description This workflow intelligently analyzes incoming Gmail emails, classifies intent using GPT-4, and sends real-time Slack notifications while logging structured data into Google Sheets. It provides a smart, AI-assisted communication workflow that saves time and ensures no important email is overlooked. 🤖💌📊 What This Template Does Monitors Gmail for unread or new incoming emails. 📥 Extracts sender, subject, and body content for processing. ✉️ Uses GPT-4 to analyze email intent and determine priority. 🧠 Formats key insights (sender, summary, intent, urgency). 🧾 Posts structured summaries and priority alerts in Slack. 💬 Logs all processed emails with classification results in Google Sheets. 📊 Sends error notifications in case of API or parsing failures. 🚨 Key Benefits ✅ AI-driven email intent classification for smarter response handling. ✅ Seamless Slack notifications for high-priority or urgent emails. ✅ Maintains a centralized record of email insights in Google Sheets. ✅ Reduces response time by surfacing critical messages instantly. ✅ Minimizes manual email triage and improves team productivity. Features Real-time Gmail monitoring for unread emails. AI-based classification using GPT-4. Slack notifications with rich formatting and urgency tagging. Google Sheets logging for tracking and analytics. Built-in error handling with notification alerts. Modular setup for easy credential reuse across projects. Requirements Gmail OAuth2 credentials with inbox read access. Slack Bot token with chat:write and channels:history scopes. Google Sheets OAuth2 credentials for data logging. Azure OpenAI (or OpenAI GPT-4) API credentials. n8n instance (cloud or self-hosted). Target Audience Customer support teams managing shared inboxes. Operations teams tracking email-based requests. Sales or marketing teams prioritizing inbound leads. AI automation enthusiasts optimizing email workflows. Remote teams using Slack for real-time updates. Step-by-Step Setup Instructions Connect your Gmail, Slack, Google Sheets, and GPT-4 credentials in n8n. 🔑 Specify the Gmail search filter (e.g., is:unread) for tracking new emails. 📬 Add your Slack channel ID in the notification node. 💬 Set your Google Sheet ID and tab name for logging results. 📊 Run once manually to verify connection and output structure. ✅ Enable the workflow for continuous, real-time execution. 🚀
by Khairul Muhtadin
Promo Seeker automatically finds, verifies, and delivers active promo codes to users via Telegram or email using SerpAPI + Gemini (OpenRouter). Saves hours of manual searching and deduplicates results into an n8n Data Table for fast reuse. Why Use This Workflow? Time Savings: Reduces manual promo hunting from 2 hours to 5 minutes per query. Cost Reduction: Cuts reliance on paid scraping tools or manual services — potential savings of $50–$200/month. Error Prevention: Cross-references sources and enforces a 30‑day recency filter to reduce expired-code hits by ~60% vs single-source checks. Scalability: Handles hundreds of queries per day with Data Table upserts and optional scheduling for continuous discovery. Ideal For Marketing / Growth Managers:** Quickly discover competitor or partner discounts to promote in campaigns. Customer Support / Operations:** Respond to user requests with verified promo codes via Telegram or email. Affiliate / Content Teams:** Aggregate and maintain a clean promo feed for newsletters or site widgets. How It Works Trigger: Incoming request via Webhook, Telegram message, Google Form submission, or scheduled run. Data Collection: The LangChain agent uses SerpAPI search results and Gemini (OpenRouter) to locate recent promo codes. Processing: Filter for recency (last 30 days), extract code, value, terms, and expiry. Intelligence Layer: Gemini 2.5 Pro (OpenRouter) + LangChain agent structure and verify results, outputting a standardized JSON. Output & Delivery: If a code exists in the Data Table, notify the requester via Telegram and Gmail; otherwise, return results and upsert them into the Data Table. Storage & Logging: Results stored/upserted in an n8n Data Table to prevent duplicates and enable fast lookups. Setup Guide Prerequisites | Requirement | Type | Purpose | |-------------|------|---------| | n8n instance | Essential | Execute the workflow — import JSON to your n8n instance | | SerpAPI account | Essential | Web search results for promo code discovery | | OpenRouter (Gemini) account | Essential | Language model (Gemini 2.5 Pro) for extraction and verification | | Telegram Bot (BotFather) | Essential | Receive queries and send promo notifications | | Gmail OAuth2 | Essential | Send rich email notifications | | n8n Data Tables | Essential | Store and deduplicate promo code records | Get your n8n instance here: n8n instance — import the JSON and begin configuration. (Repeat link for convenience) n8n instance Installation Steps Import the JSON workflow into your n8n instance. Configure credentials (use n8n's Credentials UI — do NOT paste keys into nodes): SerpAPI: paste your SerpAPI API Key from your SerpAPI dashboard. OpenRouter API: paste your OpenRouter API Key (for Gemini 2.5 Pro). Telegram API: create bot via @BotFather, then add Bot Token to Telegram credentials. Gmail OAuth2: use n8n's Gmail OAuth2 credential flow and authorize the account. Update environment-specific values: Webhook path: /v1/promo-seeker (configured in the Webhook node) or replace with your preferred path. Data Table ID: point to your own Data Table Form/webhook recipient fields (email/chatId mappings). Customize settings: Adjust the LangChain agent prompt (Promo Seeker Agent) for different recency windows or regional focus. Change max results/limit on the Data Table node (default limit = 3). Test execution: Trigger via Telegram or a POST to the webhook with sample payload: { "platform":"example.com", "email":"you@domain.com" } Confirm notifications arrive and Data Table rows are upserted. Technical Details Core Nodes | Node | Purpose | Key Configuration | |------|---------|-------------------| | SerpAPI | Fetch web search results | Provide credential; adjust search params in agent prompt | | Gemini 2.5Pro (OpenRouter) | Extract & verify promo details | Use OpenRouter credential; model google/gemini-2.5-pro | | Promo Seeker Agent (LangChain) | Orchestrates search + parsing | System prompt enforces 30‑day recency & result format | | Structured Output Parser | Validates agent output | JSON schema example for platform/code/value/terms/validUntil | | Data Table (Get row(s)) | Lookup existing promos | Filters by platform; limit = 3 | | If (Code Exist?) | Branching logic | Checks existence of platform field | | Data Table (Upsert row(s)) | Insert or update promo | Mapping from agent output to Data Table columns | | Telegram Trigger / Telegram | Receive queries & notify users | Webhook-based trigger; parse_mode = HTML for messages | | Gmail | Send rich HTML emails | Uses Gmail OAuth2 credential | | Webhook / Form Trigger | Alternate inputs | Webhook path /v1/promo-seeker and Form trigger for manual submissions | Workflow Logic On trigger, the Platform Set node normalizes the incoming query and receiver. Get row(s) checks Data Table for existing promos. If found: notify via Telegram and send Gmail (email template included). If not found: the Promo Seeker Agent runs SerpAPI searches, parses structured output, then Upsert row(s) saves results and notifications are sent. Structured Output Parser enforces correct JSON to avoid bad upserts. Customization Options Basic Adjustments Recency window: change the agent prompt to 7/14/30 days. Result limit: increase Data Table Get limit or change Upsert batch size. Advanced Enhancements Add Slack or Microsoft Teams notifications (moderate complexity). Add caching layer (Redis) to reduce repeated SerpAPI calls (advanced). Parallelize searches across multiple search engines (higher API usage & complexity). Performance & Optimization | Metric | Expected Performance | Optimization Tips | |--------|----------------------|-------------------| | Execution time | 8–30s per new search (depends on SerpAPI + LM response) | Reduce SerpAPI page depth; cache recent results | | API calls | 3–10 SerpAPI calls per complex query | Batch queries; use higher-quality search params | | Error handling | Agent retries on malformed output | Use retry nodes and set onError strategy for downstream nodes | Troubleshooting | Problem | Cause | Solution | |---------|-------|----------| | No results returned | Query too vague or rate-limited API | Improve query specificity; check SerpAPI quota | | Gmail send fails | OAuth scope not granted or token expired | Reconnect Gmail OAuth2 credential in n8n | | Telegram webhook not firing | Incorrect bot token or webhook setup | Recreate Telegram credential and check bot permissions | | Duplicate rows | Upsert mapping mismatch | Ensure promoCode mapping in Upsert matches structured output | | Agent returns malformed JSON | LM prompt too permissive | Tighten the agent system prompt and validate with Structured Output Parser | Created by: khaisa Studio Category: Marketing Automation Tags: promo-codes, coupons, serpapi, telegram, gmail, openrouter, data-tables Need custom workflows or help adapting this template? 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by isaWOW
Description Paste any webinar, training, or lecture recording URL into a simple form along with the title, speaker name, topic category, and date and the workflow builds your knowledge base automatically. WayinVideo transcribes the full session with speaker labels and timestamps, then GPT-4o-mini identifies 3 to 8 distinct topics covered and writes a complete structured page for each one — summary, key insights, action items, notable quotes, timestamps, and tags. One Notion page is created per topic and every page is logged to Google Sheets with its Notion URL for easy team access. Built for teams, educators, consultants, and agencies who want a searchable knowledge base from every webinar without watching recordings or taking notes manually. What This Workflow Does Transcribes webinars with speaker labels** — WayinVideo processes the full session and returns every segment attributed to the correct speaker with timestamps, giving GPT full context Identifies 3 to 8 distinct topics automatically** — GPT-4o-mini reads the transcript and determines how many meaningful topics were covered — no manual segmentation needed Writes a complete knowledge page per topic** — Each topic gets a summary, up to five key insights, action items with checkboxes, notable quotes, timestamp range, and relevant tags Creates one Notion page per topic** — Each knowledge page is published directly to your Notion database with the webinar title and topic title as the page name Polls automatically until transcription is ready** — Waits 90 seconds then checks every 30 seconds until the transcript is available, with no manual monitoring required Logs every created page to Google Sheets** — Appends a row with the Notion page ID, Notion page URL, topic title, speaker, tags, and Status set to Published Saves all webinar metadata to every page** — Speaker name, webinar date, duration, target team, and recording URL are embedded in every Notion page for full context Setup Requirements Tools Needed n8n instance (self-hosted or cloud) WayinVideo account with API access OpenAI account with GPT-4o-mini API access Notion account with a connected database Google Sheets (one sheet with a tab named Knowledge Base Log) Credentials Required WayinVideo API key (pasted into 2. WayinVideo — Submit Transcription and 4. WayinVideo — Get Transcript Results) OpenAI API key Notion OAuth credential Google Sheets OAuth2 > ⚠️ WayinVideo API key appears in 2 steps — replace YOUR_WAYINVIDEO_API_KEY in both 2. WayinVideo — Submit Transcription and 4. WayinVideo — Get Transcript Results. Missing either one will cause the workflow to fail. Estimated Setup Time: 20–25 minutes Step-by-Step Setup Import the workflow — Open n8n → Workflows → Import from JSON → paste the workflow JSON → click Import Get your WayinVideo API key — Log in to your WayinVideo account → go to Account Settings → copy your API key Add your WayinVideo API key to node 2 — Open node 2. WayinVideo — Submit Transcription → find the Authorization header value Bearer YOUR_WAYINVIDEO_API_KEY → replace YOUR_WAYINVIDEO_API_KEY with your actual key Add your WayinVideo API key to node 4 — Open node 4. WayinVideo — Get Transcript Results → find the same Authorization header → replace YOUR_WAYINVIDEO_API_KEY with the same key Connect OpenAI — Open node 9. OpenAI — GPT-4o-mini Model → click the credential dropdown → add your OpenAI API key → test the connection Set up your Notion database — In Notion, create a database (or use an existing one) where the knowledge pages will be created → open the database in a browser → copy the database ID from the URL (the 32-character string after your workspace name and before the ?) Connect Notion — Open node 11. Notion — Create Topic Page → click the credential dropdown → add Notion OAuth → complete the OAuth flow to authorize n8n access → in the pageId field, paste your Notion database URL or ID Create your Google Sheet tab — Open your Google Sheet → add a tab named exactly Knowledge Base Log → add these 10 column headers in row 1: Webinar Title, Topic Title, Speaker, Topic Category, Webinar Date, Notion Page ID, Notion Page URL, Tags, Created On, Status Connect Google Sheets — Open node 12. Google Sheets — Log Created Pages → click the document field → replace YOUR_GOOGLE_SHEET_LOG_ID by selecting your spreadsheet or entering the Sheet ID (the string between /d/ and /edit in your Sheet URL) → click the credential dropdown → add Google Sheets OAuth2 → authorize access Activate the workflow — Toggle the workflow to Active → copy the Form URL from node 1. Form — Webinar URL + Details → open it in a browser to submit your first webinar How It Works (Step by Step) Step 1 — Form: Webinar URL + Details You open the form URL in a browser and fill in six fields: the webinar or recording URL (Zoom, YouTube, Vimeo, or any direct link), the webinar title, the speaker or presenter name, the topic category (e.g. SEO, Marketing, AI), the webinar date, and optionally the target team or department. Submitting the form starts the workflow. Step 2 — HTTP: WayinVideo — Submit Transcription The webinar URL is sent to the WayinVideo transcription API with the target language set to English. WayinVideo accepts the job and returns a task ID confirming transcription has started. Step 3 — Wait: 90 Seconds The workflow pauses for 90 seconds before the first status check. This is longer than shorter video workflows because webinar recordings are typically 45–90 minutes and need more initial processing time. Step 4 — HTTP: WayinVideo — Get Transcript Results A GET request checks the WayinVideo results endpoint using the task ID from step 2. It returns the current processing status and, once complete, the full speaker-labeled transcript. Step 5 — IF: Transcription Complete? This is the polling gate. If the status equals SUCCEEDED (YES path), the transcript is ready and the workflow moves forward to formatting. If still processing (NO path), the workflow routes to 6. Wait — 30 Seconds Retry which pauses 30 seconds then loops back to step 4 to check again. This repeats until SUCCEEDED. Step 6 — Wait: 30 Seconds Retry When the transcript is not yet ready, the workflow waits 30 seconds then returns to step 4 for another check. The loop continues automatically. Step 7 — Code: Format Transcript Each segment is formatted as [Speaker Name | MM:SS] text. Total duration in minutes, word count, and unique speaker names are calculated. All form inputs — webinar title, speaker name, topic category, webinar date, target team, and recording URL — are packaged here for the AI prompt. Step 8 — AI Agent: Extract Knowledge Topics GPT-4o-mini receives the formatted transcript and a detailed system prompt. It identifies between 3 and 8 distinct topics from the webinar and for each topic returns a structured JSON object with: a 5–8 word topic title, a 2–3 sentence summary, up to five key insights, action items, notable quotes, an approximate timestamp range, and 2–4 tags. The output is a clean JSON array. GPT is instructed to write only from what was actually said in the transcript. Step 9 — OpenAI: GPT-4o-mini Model This is the language model powering the knowledge extraction. It runs with default settings for consistent, structured output. Step 10 — Code: Parse Topics and Build Notion Content The AI output JSON is cleaned (any accidental markdown backticks removed) and parsed. If parsing fails, the step throws a clear error. Each topic in the array is returned as an individual row. For each topic, a full Notion-ready markdown page is assembled with sections for Summary, Key Insights, Action Items (with checkbox syntax), Notable Quotes (in blockquote format), and Webinar Details. All webinar metadata is embedded in every page. Step 11 — Notion: Create Topic Page One Notion page is created per topic. The page title is formatted as "Webinar Title — Topic Title". The full markdown content built in step 10 is written into the page body. Notion returns the new page's ID and URL. Step 12 — Google Sheets: Log Created Pages After each Notion page is created, one row is appended to your Knowledge Base Log tab. The row includes webinar title, topic title, speaker, topic category, webinar date, the Notion page ID, the Notion page URL, the tags as a comma-separated string, the creation timestamp, and Status set to Published. Your team now has a direct link to every knowledge page from one sheet. Key Features ✅ 90-second initial wait for long recordings — The workflow uses a longer first pause suited to webinar-length content rather than short video clips ✅ 3 to 8 topics per webinar — auto-detected — GPT decides how many meaningful topics are present based on the actual content, not a fixed number ✅ Action items formatted as Notion checkboxes — Every action item is written with - [ ] syntax so they render as real checkboxes in Notion — ready to assign and complete ✅ Notable quotes in blockquote format — Speaker quotes are wrapped in Notion blockquote syntax so they visually stand out on the page ✅ Webinar metadata embedded in every page — Speaker, date, duration, target team, and recording URL are written into each page so the context is always visible without referencing a separate document ✅ Notion page URL logged immediately — Every page URL is saved to Google Sheets the moment it is created so your team can access any page directly without opening Notion ✅ JSON parsing with fallback protection — The code step strips any accidental markdown formatting from GPT output before parsing, reducing the chance of a JSON parse failure on well-formed responses Customisation Options Increase the maximum number of topics — In node 8. AI Agent — Extract Knowledge Topics, change "maximum 8 topics" in the system prompt to a higher number — useful for long full-day workshop recordings that cover more than 8 distinct areas. Add a Slack notification after all pages are created — After node 12. Google Sheets — Log Created Pages (on the last topic row), add a Slack step that posts the webinar title, number of pages created, and a link to your Knowledge Base Log sheet so your team is notified without checking Sheets. Filter which topics get a Notion page — After node 10. Code — Parse Topics and Build Notion Content, add an IF check that only proceeds to Notion creation if the number of key insights is 3 or more — skipping thin topics that GPT extracted with limited content. Add a Notion tag property — In node 11. Notion — Create Topic Page, add a multi-select property mapping that sends the tags array to a Tags property in your Notion database — making pages filterable and searchable by tag directly in Notion. Send a summary email after all pages are created — After node 12. Google Sheets — Log Created Pages (last row only), add a Gmail step that sends an email with the webinar title, number of pages created, and a direct link to the Knowledge Base Log sheet so the submitter gets a confirmation. Troubleshooting WayinVideo returning an error on submission: Confirm YOUR_WAYINVIDEO_API_KEY in node 2. WayinVideo — Submit Transcription is replaced with your actual API key — not the placeholder text Confirm the same replacement was made in node 4. WayinVideo — Get Transcript Results — both steps require the key Check the execution log of node 2 for the raw error — a 401 means wrong key, a 422 means the URL format is not supported by WayinVideo Workflow stuck in the polling loop: Check that the webinar URL is publicly accessible — Zoom recordings with password protection, private YouTube videos, or expired Zoom links will not be processed Open the execution log of node 4. WayinVideo — Get Transcript Results and check the raw response — WayinVideo may have returned a FAILED status with a specific error message Very long recordings (over 2 hours) may take longer than the polling loop can handle — consider increasing the retry wait from 30 to 60 seconds in node 6. Wait — 30 Seconds Retry GPT not returning valid JSON or extracting zero topics: Confirm the API key is connected in node 9. OpenAI — GPT-4o-mini Model and your account has available credits Check the execution log of node 8. AI Agent — Extract Knowledge Topics for the raw GPT output — the code step in node 10 will show a parse error with the first 200 characters of the bad output If GPT is consistently returning markdown-wrapped JSON (with backticks), node 10 strips these automatically — but if the output has additional explanation text before the array, the JSON extraction regex should still find it Notion pages not being created: Confirm the Notion OAuth credential in node 11. Notion — Create Topic Page is connected and that the integration has been added to the target database in Notion — go to your Notion database → three-dot menu → Add connections → find your n8n integration Confirm the pageId field in node 11 points to a valid Notion database URL — this must be a database, not a regular page Check the execution log of node 11 for the Notion API error — a 404 means the database ID is incorrect Google Sheets not logging rows: Confirm YOUR_GOOGLE_SHEET_LOG_ID in node 12. Google Sheets — Log Created Pages is replaced with your actual sheet ID from the URL Confirm the tab is named Knowledge Base Log exactly and all 10 column headers in row 1 match exactly Check that the Google Sheets OAuth2 credential is connected and not expired — re-authorize if needed Support Need help setting this up or want a custom version built for your team or agency? 📧 Email: info@isawow.com 🌐 Website: https://isawow.com/
by Avkash Kakdiya
How it works This workflow monitors customer health by combining payment behavior, complaint signals, and AI-driven feedback analysis. It runs on daily and weekly schedules to evaluate risk levels, escalate high-risk customers, and generate structured product insights. High-risk cases are notified instantly, while detailed feedback and audit logs are stored for long-term analysis. Step-by-step Step 1: Triggers & mode selection** Daily Risk Check Trigger – Starts the workflow on a daily schedule. Weekly schedule1 – Triggers the workflow for weekly summary runs. Edit Fields3 – Sets flags for daily execution. Edit Fields2 – Sets flags for weekly execution. Switch1 – Routes execution based on daily or weekly mode. Step 2: Risk evaluation & escalation** Fetch Customer Risk Data – Pulls customer, payment, product, and complaint data from PostgreSQL. Is High Risk Customer? – Evaluates payment status and complaint count. Prepare Escalation Summary For Low Risk User – Assigns low-risk status and no-action details. Prepare Escalation Summary For High Risk User – Assigns high-risk status and escalation actions. Merge Risk Result – Combines low-risk and high-risk customer records. Send a message4 – Sends the customer risk summary via Gmail. Send a message5 – Sends the same risk summary to Discord. Code in JavaScript3 – Appends notification status and timestamps. Append or update row in sheet3 – Logs risk evaluations and notification status in Google Sheets. Step 3: AI feedback & reporting** Get row(s) in sheet1 – Fetches customer records for feedback analysis. Loop Over Items1 – Processes customers one by one. Prompt For Model1 – Builds a structured prompt for product feedback analysis. HTTP Request1 – Sends data to the AI model for insight generation. Code in JavaScript – Merges AI feedback with original customer data. Append or update row in sheet – Stores AI-generated feedback in Google Sheets. Wait1 – Controls execution pacing between records. Merge1 – Prepares consolidated feedback data. Send a message1 – Emails the final AI-powered feedback report. Why use this? Detect customer churn risk early using payment and complaint signals Automatically escalate high-risk customers without manual monitoring Convert raw customer issues into executive-ready product insights Keep a complete audit trail of risk, feedback, and notifications Align support, product, and leadership teams with shared visibility
by Țugui Dragoș
This workflow automatically collects customer reviews from Google, Facebook, Trustpilot, and Yelp, analyzes their sentiment using AI, sends real-time alerts for negative feedback, and generates a weekly summary report. It is ideal for businesses that want to monitor their online reputation across multiple platforms and respond quickly to customer concerns. How It Works Daily Schedule**: Triggers the workflow every day at 09:00. Review Collection**: Fetches new reviews from Google, Facebook, Trustpilot, and Yelp using their official APIs. Data Normalization**: Merges and standardizes all reviews into a unified format. AI Sentiment Analysis**: Uses GPT-4 to analyze the sentiment and extract key insights from each review. Negative Review Alerts**: Sends a Slack notification to managers if a negative review is detected. Logging**: Saves all reviews and their analysis to a Google Sheet for record-keeping. Weekly Reporting**: Every Monday, aggregates the past week’s reviews, generates an AI-powered summary, and emails it to management. Configuration API Credentials: Google My Business API: Create a project in Google Cloud, enable the My Business API, and generate OAuth credentials. Facebook Graph API: Create a Facebook App, request the necessary permissions, and obtain a Page Access Token. Trustpilot API: Register for a Trustpilot Business account and generate an API key. Yelp Fusion API: Sign up for Yelp Fusion, create an app, and get your API key. OpenAI API: Create an account at OpenAI, generate an API key for GPT-4 access. Slack API: Create a Slack App, enable Incoming Webhooks, and get the webhook URL. Google Sheets API: Enable the Google Sheets API in Google Cloud and create OAuth credentials. Set Up Environment Variables: Add all API keys, tokens, and configuration values in the Workflow Configuration node or as n8n credentials. Google Sheet Setup: Create a Google Sheet with columns for review data and share it with your service account email. Slack Channel: Set up a Slack channel for alerts and add the webhook URL in the configuration. Email Settings: Configure the recipient email address for weekly reports in the workflow. Usage Activate the workflow after configuration. Reviews will be collected and analyzed daily. Negative reviews trigger instant Slack alerts. Every Monday, a summary report is sent via email. Use Case: Monitor and respond to customer feedback across Google, Facebook, Trustpilot, and Yelp, automate sentiment analysis, and keep management informed with actionable weekly insights.
by Jitesh Dugar
Transform procurement from manual chaos to intelligent automation - AI-powered supplier selection analyzes urgency, cost, and delivery requirements to recommend optimal vendors, then automatically generates professional POs, manages approval workflows, and tracks delivery while maintaining complete audit trails. What This Workflow Does Revolutionizes purchase order management with AI-driven supplier optimization and automated procurement workflows: Webhook-Triggered Generation** - Automatically creates POs from inventory systems, manual requests, or threshold alerts Smart Data Validation** - Verifies item details, quantities, pricing, and calculates totals with tax and shipping AI Supplier Selection** - OpenAI agent analyzes order requirements and recommends optimal supplier based on multiple factors Intelligent Analysis** - AI considers urgency level, total value, item categories, delivery requirements, and cost optimization Multi-Supplier Database** - Maintains supplier profiles with contact details, payment terms, delivery times, and specializations Approval Workflow** - Routes high-value orders (>$5000) for management approval before supplier notification Professional PO Generation** - Creates beautifully formatted purchase orders with company branding and complete details AI Insights Display** - Shows supplier selection reasoning, cost optimization notes, and alternative supplier recommendations PDF Conversion** - Transforms HTML into print-ready, professional-quality purchase order documents Automated Email Distribution** - Sends POs directly to selected suppliers with all necessary attachments Google Drive Archival** - Automatically saves POs to organized folders with searchable filenames Procurement System Logging** - Records complete PO details, supplier info, and status in centralized system Delivery Tracking** - Monitors order status from placement through delivery confirmation Slack Team Notifications** - Real-time alerts to procurement team with PO details and AI recommendations Urgency Classification** - Prioritizes orders based on urgency (urgent, normal) affecting supplier selection Cost Optimization** - AI identifies opportunities for savings or faster delivery based on requirements Key Features AI-Powered Supplier Matching**: Machine learning analyzes order characteristics and recommends best supplier from database based on delivery speed, cost, and specialization Intelligent Trade-Off Analysis**: AI balances cost vs delivery time vs supplier capabilities to find optimal choice for specific order requirements Automatic PO Numbering**: Generates unique sequential purchase order numbers with format PO-YYYYMM-#### for tracking and reference Approval Threshold Management**: Configurable dollar thresholds trigger approval workflows for high-value purchases requiring management authorization Multi-Criteria Supplier Selection**: Considers urgency level, order value, item categories, delivery requirements, and historical performance Supplier Specialization Matching**: Routes technology orders to tech suppliers, construction materials to building suppliers, etc. Cost vs Speed Optimization**: AI recommends premium suppliers for urgent orders and budget suppliers for standard delivery timelines Alternative Supplier Suggestions**: Provides backup supplier recommendations in case primary choice is unavailable Real-Time Pricing Calculations**: Automatically computes line items, subtotals, taxes, shipping, and grand totals Payment Terms Automation**: Pulls supplier-specific payment terms (Net 30, Net 45, etc.) from supplier database Shipping Address Management**: Maintains multiple delivery locations with automatic address population Special Instructions Field**: Captures custom requirements, delivery notes, or handling instructions for suppliers Item Catalog Integration**: Supports product codes, descriptions, quantities, and unit pricing for accurate ordering Audit Trail Generation**: Complete activity log tracking PO creation, approvals, supplier notification, and delivery Status Tracking System**: Monitors PO lifecycle from creation through delivery confirmation with real-time updates Multi-Department Support**: Tracks requesting department for budget allocation and accountability Perfect For Retail Stores** - Automated inventory reordering when stock reaches threshold levels Manufacturing Companies** - Raw material procurement with delivery scheduling for production planning Restaurant Chains** - Food and supplies ordering with vendor rotation and cost optimization IT Departments** - Equipment purchasing with approval workflows for technology investments Construction Companies** - Materials procurement with urgency-based supplier selection for project timelines Healthcare Facilities** - Medical supplies ordering with compliance tracking and vendor management Educational Institutions** - Procurement for facilities, supplies, and equipment across departments E-commerce Businesses** - Inventory replenishment with AI-optimized supplier selection for margins Hospitality Industry** - Supplies procurement for hotels and resorts with cost control Government Agencies** - Compliant procurement workflows with approval chains and audit trails What You Will Need Required Integrations OpenAI API** - AI agent for intelligent supplier selection and optimization (API key required) HTML to PDF API** - PDF conversion service for professional PO documents (approximately 1-5 cents per PO) Gmail or SMTP** - Email delivery for sending POs to suppliers and approval requests Google Drive** - Cloud storage for PO archival and compliance documentation Optional Integrations Slack Webhook** - Procurement team notifications with PO details and AI insights Procurement Software** - ERP/procurement system API for automatic logging and tracking Inventory Management** - Connect to inventory systems for automated reorder triggers Accounting Software** - QuickBooks, Xero integration for expense tracking and reconciliation Supplier Portal** - Direct integration with supplier order management systems Approval Software** - Connect to approval management platforms for workflow automation Quick Start Import Template - Copy JSON workflow and import into your n8n instance Configure OpenAI - Add OpenAI API credentials for AI supplier selection agent Setup PDF Service - Add HTML to PDF API credentials in the HTML to PDF node Configure Gmail - Connect Gmail OAuth2 credentials and update sender email Connect Google Drive - Add Google Drive OAuth2 credentials and set folder ID for PO archival Customize Company Info - Edit company data with your company name, address, contact details Update Supplier Database - Modify supplier information in enrichment node with actual vendor details Set Approval Threshold - Adjust dollar amount requiring management approval ($5000 default) Configure Email Templates - Customize supplier email and approval request messages Add Slack Webhook - Configure Slack notification URL for procurement team alerts Test AI Agent - Submit sample order to verify AI supplier selection logic Test Complete Workflow - Run end-to-end test with real PO data to verify all integrations Customization Options Supplier Scoring Algorithm** - Adjust AI weighting for cost vs delivery speed vs quality factors Multi-Location Support** - Add multiple shipping addresses for different facilities or warehouses Budget Tracking** - Integrate departmental budgets with automatic budget consumption tracking Volume Discounts** - Configure automatic discount calculations based on order quantities Contract Compliance** - Enforce existing vendor contracts and preferred supplier agreements Multi-Currency Support** - Handle international suppliers with currency conversion and forex rates RFQ Generation** - Extend workflow to generate requests for quotes for new items Delivery Scheduling** - Integrate calendar for scheduled deliveries and receiving coordination Quality Tracking** - Add supplier performance scoring based on delivery time and quality Return Management** - Create return authorization workflows for defective items Recurring Orders** - Automate standing orders with scheduled generation Inventory Forecasting** - AI predicts reorder points based on historical consumption patterns Supplier Negotiation** - Track pricing history and flag opportunities for renegotiation Compliance Documentation** - Attach required certifications, insurance, or regulatory documents Multi-Approver Chains** - Configure complex approval hierarchies for different dollar thresholds Expected Results 90% time savings** - Reduce PO creation from 30 minutes to 3 minutes per order 50% faster supplier selection** - AI recommends optimal vendor instantly vs manual research Elimination of stockouts** - Automated reordering prevents inventory shortages 20-30% cost savings** - AI optimization identifies better pricing and supplier options 100% approval compliance** - No high-value orders bypass required approvals Zero lost POs** - Complete digital trail with automatic archival Improved supplier relationships** - Professional, consistent POs with clear requirements Faster order processing** - Suppliers receive clear POs immediately enabling faster fulfillment Better delivery predictability** - AI matches urgency to supplier capabilities reducing delays Reduced procurement overhead** - Automation eliminates manual data entry and follow-up Pro Tips Train AI with Historical Data** - Feed past successful orders to improve AI supplier recommendations Maintain Supplier Performance Scores** - Track delivery times and quality to enhance AI selection accuracy Set Smart Thresholds** - Adjust approval amounts based on department budgets and risk tolerance Use Urgency Levels Strategically** - Reserve "urgent" classification for true emergencies to optimize costs Monitor AI Recommendations** - Review AI reasoning regularly to validate supplier selection logic Integrate Inventory Triggers** - Connect to inventory systems for automatic PO generation at reorder points Establish Preferred Vendors** - Flag preferred suppliers in database for AI to prioritize when suitable Document Special Requirements** - Use special instructions field consistently for better supplier compliance Track Cost Trends** - Export PO data to analyze spending patterns and negotiation opportunities Review Alternative Suppliers** - Keep AI's alternative recommendations for backup when primary unavailable Schedule Recurring Orders** - Set up automated triggers for regular supply needs Centralize Receiving** - Use consistent ship-to addresses to simplify delivery coordination Archive Systematically** - Organize Drive folders by fiscal year, department, or supplier Test Approval Workflow** - Verify approval routing works before deploying to production Communicate AI Benefits** - Help procurement team understand AI recommendations build trust Business Impact Metrics Track these key metrics to measure workflow success: PO Generation Time** - Average minutes from request to supplier notification (target: under 5 minutes) Supplier Selection Accuracy** - Percentage of AI recommendations that meet delivery and cost expectations (target: 90%+) Approval Workflow Speed** - Average hours for high-value PO approvals (target: under 4 hours) Stockout Prevention** - Reduction in inventory shortages due to faster PO processing Cost Savings** - Percentage reduction in procurement costs from AI optimization (typical: 15-25%) Order Accuracy** - Reduction in PO errors requiring correction or cancellation Supplier On-Time Delivery** - Improvement in delivery performance from better supplier matching Procurement Productivity** - Number of POs processed per procurement staff member Budget Compliance** - Percentage of POs staying within approved departmental budgets Audit Readiness** - Time required to produce PO documentation for audits (target: under 5 minutes) Template Compatibility Compatible with n8n version 1.0 and above Requires OpenAI API access for AI agent functionality Works with n8n Cloud and Self-Hosted instances Requires HTML to PDF API service subscription No coding required for basic setup Fully customizable supplier database and selection criteria Integrates with major procurement and ERP systems via API Supports unlimited suppliers and product categories Scales to handle thousands of POs monthly Ready to transform your procurement process? Import this template and start generating intelligent purchase orders with AI-powered supplier selection, automated approval workflows, and complete procurement tracking - eliminating manual processes, preventing stockouts, and optimizing costs across your entire supply chain!
by explorium
Outbound Agent - AI-Powered Lead Generation with Natural Language Prospecting This n8n workflow transforms natural language queries into targeted B2B prospecting campaigns by combining Explorium's data intelligence with AI-powered research and personalized email generation. Simply describe your ideal customer profile in plain English, and the workflow automatically finds prospects, enriches their data, researches them, and creates personalized email drafts. DEMO Template Demo Credentials Required To use this workflow, set up the following credentials in your n8n environment: Anthropic API Type:** API Key Used for:** AI Agent query interpretation, email research, and email writing Get your API key at Anthropic Console Explorium API Type:** Generic Header Auth Header:** Authorization Value:** Bearer YOUR_API_KEY Used for:** Prospect matching, contact enrichment, professional profiles, and MCP research Get your API key at Explorium Dashboard Explorium MCP Type:** HTTP Header Auth Used for:** Real-time company and prospect intelligence research Connect to: https://mcp.explorium.ai/mcp Gmail Type:** OAuth2 Used for:** Creating email drafts Alternative options: Outlook, Mailchimp, SendGrid, Lemlist Go to Settings → Credentials, create these credentials, and assign them in the respective nodes before running the workflow. Workflow Overview Node 1: When chat message received This node creates an interactive chat interface where users can describe their prospecting criteria in natural language. Type:** Chat Trigger Purpose:** Accept natural language queries like "Get 5 marketing leaders at fintech startups who joined in the past year and have valid contact information" Example Prompts:** "Find SaaS executives in New York with 50-200 employees" "Get marketing directors at healthcare companies" "Show me VPs at fintech startups with recent funding" Node 2: Chat or Refinement This code node manages the conversation flow, handling both initial user queries and validation error feedback. Function:** Routes either the original chat input or validation error messages to the AI Agent Dynamic Input:** Combines chatInput and errorInput fields Purpose:** Creates a feedback loop for validation error correction Node 3: AI Agent The core intelligence node that interprets natural language and generates structured API calls. Functionality: Interprets user intent from natural language queries Maps concepts to Explorium API filters (job levels, departments, company size, revenue, location, etc.) Generates valid JSON requests with precise filter criteria Handles off-topic queries with helpful guidance Connected to MCP Client for real-time filter specifications AI Components: Anthropic Chat Model:** Claude Sonnet 4 for query interpretation Simple Memory:** Maintains conversation context (100 message window) Output Parser:** Structured JSON output with schema validation MCP Client:** Connected to https://mcp.explorium.ai/mcp for Explorium specifications System Instructions: Expert in converting natural language to Explorium API filters Can revise previous responses based on validation errors Strict adherence to allowed filter values and formats Default settings: mode: "full", size: 10000, page_size: 100, has_email: true Node 4: API Call Validation This code node validates the AI-generated API request against Explorium's filter specifications. Validation Checks: Filter key validity (only allowed filters from approved list) Value format correctness (enums, ranges, country codes) No duplicate values in arrays Proper range structure for experience fields (total_experience_months, current_role_months) Required field presence Allowed Filters: country_code, region_country_code, company_country_code, company_region_country_code company_size, company_revenue, company_age, number_of_locations google_category, naics_category, linkedin_category, company_name city_region_country, website_keywords has_email, has_phone_number job_level, job_department, job_title business_id, total_experience_months, current_role_months Output: isValid: Boolean validation status validationErrors: Array of specific error messages Node 5: Is API Call Valid? Conditional routing node that determines the next step based on validation results. If Valid:** Proceed to Explorium API: Fetch Prospects If Invalid:** Route to Validation Prompter for correction Node 6: Validation Prompter Generates detailed error feedback for the AI Agent when validation fails. This creates a self-correcting loop where the AI learns from validation errors and regenerates compliant requests by routing back to Node 2 (Chat or Refinement). Node 7: Explorium API: Fetch Prospects Makes the validated API call to Explorium's prospect database. Method:** POST Endpoint:** /v1/prospects/fetch Authentication:** Header Auth (Bearer token) Input:** JSON with filters, mode, size, page_size, page Returns:** Array of matched prospects with prospect IDs based on filter criteria Node 8: Pull Prospect IDs Extracts prospect IDs from the fetch response for bulk enrichment. Input:** Full fetch response with prospect data Output:** Array of prospect_id values formatted for enrichment API Node 9: Explorium API: Contact Enrichment Single enrichment node that enhances prospect data with both contact and profile information. Method:** POST Endpoint:** /v1/prospects/enrich Enrichment Types:** contacts, profiles Authentication:** Header Auth (Bearer token) Input:** Array of prospect IDs from Node 8 Returns: Contacts:** Professional emails (current, verified), phone numbers (mobile, work), email validation status, all available email addresses Profiles:** Full professional history, current role details, company information, skills and expertise, education background, experience timeline, job titles and seniority levels Node 10: Clean Output Data Transforms and structures the enriched data for downstream processing. Node 11: Loop Over Items Iterates through each prospect to generate individualized research and emails. Batch Size:** 1 (processes prospects one at a time) Purpose:** Enable personalized research and email generation for each prospect Loop Control:** Processes until all prospects are complete Node 12: Research Email AI-powered research agent that investigates each prospect using Explorium MCP. Input Data: Prospect name, job title, company name, company website LinkedIn URL, job department, skills Research Focus: Company automation tool usage (n8n, Zapier, Make, HubSpot, Salesforce) Data enrichment practices Tech stack and infrastructure (Snowflake, Segment, etc.) Recent company activity and initiatives Pain points related to B2B data (outdated CRM data, manual enrichment, static workflows) Public content (speaking engagements, blog posts, thought leadership) AI Components: Anthropic Chat Model1:** Claude Sonnet 4 for research Simple Memory1:** Maintains research context Explorium MCP1:** Connected to https://mcp.explorium.ai/mcp for real-time intelligence Output: Structured JSON with research findings including automation tools, pain points, personalization notes Node 13: Email Writer Generates personalized cold email drafts based on research findings. Input Data: Contact info from Loop Over Items Current experience and skills Research findings from Research Email agent Company data (name, website) AI Components: Anthropic Chat Model3:** Claude Sonnet 4 for email writing Structured Output Parser:** Enforces JSON schema with email, subject, message fields Output Schema: email: Selected prospect email address (professional preferred) subject: Compelling, personalized subject line message: HTML formatted email body Node 14: Create a draft (Gmail) Creates email drafts in Gmail for review before sending. Resource:** Draft Subject:** From Email Writer output Message:** HTML formatted email body Send To:** Selected prospect email address Authentication:** Gmail OAuth2 After Creation: Loops back to Node 11 (Loop Over Items) to process next prospect Alternative Output Options: Outlook:** Create drafts in Microsoft Outlook Mailchimp:** Add to email campaign SendGrid:** Queue for sending Lemlist:** Add to cold email sequence Workflow Flow Summary Input: User describes target prospects in natural language via chat interface Interpret: AI Agent converts query to structured Explorium API filters using MCP Validate: API call validation ensures filter compliance Refine: If invalid, error feedback loop helps AI correct the request Fetch: Retrieve matching prospect IDs from Explorium database Enrich: Parallel bulk enrichment of contact details and professional profiles Clean: Transform and structure enriched data Loop: Process each prospect individually Research: AI agent uses Explorium MCP to gather company and prospect intelligence Write: Generate personalized email based on research Draft: Create reviewable email drafts in preferred platform This workflow eliminates manual prospecting work by combining natural language processing, intelligent data enrichment, automated research, and personalized email generation—taking you from "I need marketing leaders at fintech companies" to personalized, research-backed email drafts in minutes. Customization Options Flexible Triggers The chat interface can be replaced with: Scheduled runs for recurring prospecting Webhook triggers from CRM updates Manual execution for ad-hoc campaigns Scalable Enrichment Adjust enrichment depth by: Adding more Explorium API endpoints (technographics, funding, news) Configuring prospect batch sizes Customizing data cleaning logic Output Destinations Route emails to your preferred platform: Email Platforms:** Gmail, Outlook, SendGrid, Mailchimp Sales Tools:** Lemlist, Outreach, SalesLoft CRM Integration:** Salesforce, HubSpot (create leads with research) Collaboration:** Slack notifications, Google Docs reports AI Model Flexibility Swap AI providers based on your needs: Default: Anthropic Claude (Sonnet 4) Alternatives: OpenAI GPT-4, Google Gemini Setup Notes Domain Filtering: The workflow prioritizes professional emails—customize email selection logic in the Clean Output Data node MCP Configuration: Explorium MCP requires Header Auth setup—ensure credentials are properly configured Rate Limits: Adjust Loop Over Items batch size if hitting API rate limits Memory Context: Simple Memory maintains conversation history—increase window length for longer sessions Validation: The AI self-corrects through validation loops—monitor early runs to ensure filter accuracy This workflow represents a complete AI-powered sales development representative (SDR) that handles prospecting, research, and personalized outreach with minimal human intervention.
by Cheng Siong Chin
How It Works This workflow automates end-to-end AI-driven content moderation for platforms managing user-generated content, including marketplaces, communities, and enterprise systems. It is designed for product, trust & safety, and governance teams seeking scalable, policy-aligned enforcement without subjective scoring. The workflow validates structured review, goal, and feedback data using a Performance Signal Agent that standardizes moderation signals and removes ambiguity. A Governance Agent then orchestrates policy enforcement, eligibility checks, escalation logic, and audit preparation. Content enters via webhook, is classified, validated, and routed by action type (approve, flag, escalate). Enforcement logic determines whether to store clean content, flag violations, or trigger escalation emails and team notifications. All actions are logged for traceability and compliance. This template solves inconsistent moderation decisions, lack of structured governance controls, and manual escalation overhead by embedding deterministic checkpoints, structured outputs, and audit-ready logging into a single automated pipeline. Setup Steps Connect OpenAI API credentials for AI agents. Configure Google Sheets or database for logging. Connect Gmail for escalation emails. Define moderation policies and routing rules. Activate webhook and test sample content. Prerequisites n8n account, OpenAI API key, Google Sheets or DB access, Gmail credentials, defined moderation policies. Use Cases Marketplace listing moderation, enterprise HR review screening Customization Adjust policy rules, add risk scoring, integrate Slack instead of Gmail Benefits Improves moderation accuracy, reduces manual review, enforces governance consistency
by Cheng Siong Chin
How It Works This workflow automates student academic advising by deploying a multi-agent AI system that triages student queries, routes them intelligently, and escalates when human intervention is needed. Designed for academic institutions, it eliminates manual triage bottlenecks and ensures timely, context-aware responses. A student event triggers the webhook, which feeds into a Status Agent to classify the student's situation. A routing node directs the request to an Academic Orchestration Agent, which delegates to specialized sub-agents—Advising, Notification, or Escalation—based on query type. Results are routed by action type, checked for escalation, then dispatched via student email, faculty email, or Slack advisor alert before logging completion. Setup Steps Import workflow and configure Student Event Webhook URL. Add OpenAI API credentials to all OpenAI Model nodes. Configure Gmail credentials for student and faculty email nodes. Add Slack credentials and set target advisor channel for Slack alert. Set escalation thresholds in the "Check if Escalation Required" node. Test with sample student event payload via webhook. Prerequisites OpenAI API key Gmail account with OAuth2 Slack workspace with bot token Use Cases Automated academic query triage for universities Customization Add new sub-agents for career or financial advising Benefits Reduces advisor workload through intelligent auto-triage Ensures urgent cases are escalated instantly