Workflow Templates

CHRO Agent with HR Team Description Complete AI-powered HR department with a Chief Human Resources Officer (CHRO) agent orchestrating specialized HR team members for comprehensive people operations. Overview This n8n workflow creates a comprehensive human resources department using AI agents. The CHRO agent analyzes HR requests and delegates tasks to specialized agents for recruitment, policy development, training, performance management, employee engagement, and compensation analysis. Features Strategic CHRO agent using OpenAI O3 for complex HR decision-making Six specialized HR agents powered by GPT-4.1-mini for efficient execution Complete HR lifecycle coverage from hiring to retention Automated policy creation and compliance documentation Performance review and goal-setting systems Employee engagement and culture initiatives Compensation analysis and benchmarking Team Structure CHRO Agent**: Strategic HR oversight and task delegation (O3 model) Recruiter Agent**: Job descriptions, candidate screening, interview questions HR Policy Writer**: Employee handbooks, policies, compliance documentation Training & Development Specialist**: Onboarding programs, learning materials Performance Review Specialist**: Reviews, feedback templates, goal setting Employee Engagement Specialist**: Culture initiatives, team building, communications Compensation & Benefits Analyst**: Salary benchmarking, benefits packages How to Use Import the workflow into your n8n instance Configure OpenAI API credentials for all chat models Deploy the webhook for chat interactions Send HR requests via chat (e.g., "Create a complete onboarding program for software engineers") The CHRO will analyze and delegate to appropriate specialists Receive comprehensive HR deliverables Use Cases Complete Hiring Process**: Job postings → Screening → Interviews → Offers Policy Development**: Employee handbooks, compliance documentation Onboarding Programs**: 30-60-90 day plans with training materials Performance Management**: Review cycles, feedback systems, development plans Culture & Engagement**: Surveys, team building activities, recognition programs Compensation Strategy**: Market analysis, pay equity reviews, benefits design Requirements n8n instance with LangChain nodes OpenAI API access (O3 for CHRO, GPT-4.1-mini for specialists) Webhook capability for chat interactions Optional: Integration with HRIS systems Cost Optimization O3 model used only for strategic CHRO decisions GPT-4.1-mini provides 90% cost reduction for specialist tasks Parallel processing enables simultaneous agent execution Template library reduces redundant content generation Integration Options Connect to HRIS systems (Workday, BambooHR, etc.) Integrate with applicant tracking systems Link to performance management platforms Export to document management systems Contact & Resources Website**: nofluff.online YouTube**: @YaronBeen LinkedIn**: Yaron Been Tags #HRTech #PeopleOperations #TalentAcquisition #EmployeeExperience #HRAutomation #AIRecruitment #PerformanceManagement #CompensationBenefits #OnboardingAutomation #CultureTech #n8n #OpenAI #MultiAgentSystem #FutureOfWork #HRTransformation

This n8n template gives you a chat-style assistant that can search your HubSpot CRM on demand. Ask natural-language questions like “show me leads in Germany” or “what deals close next month,” and the agent translates your request into precise HubSpot searches—then answers in plain English. Great for founders, AEs, and ops folks who want quick answers without clicking through the CRM. How it works Chat trigger** starts a session from your n8n chat UI or embed. AI Agent (Gemini 2.5 Pro)** interprets the message and: Chooses the right HubSpot search (contacts or deals). Fills filter property, operator (EQ, NEQ, GT, GTE, LT, LTE, BETWEEN, IN, NOT\_IN), and value(s). Requests specific properties (email, name, lifecycle stage, owner, activity timestamps, etc.). HubSpot tools** execute live queries: Contacts: flexible property filter + free-text query. Deals: filters by owner and core deal fields (stage, amount, pipeline, close date). Memory buffer** keeps the last turns so you can say “now only show closed won over 10k” and the agent understands context. How to use Connect credentials HubSpot OAuth on both HubSpot Tool nodes. Google Gemini API key on the Gemini Chat Model. Open the chat (the “When chat message received” node). Ask questions like: “Find contacts named Hans created after Sept 1.” “Deals owned by me in Proposal with amount > 10,000.” “Contacts with lead status = New and no email reply in the last 14 days.” Refine with follow-ups: “Sort by most recently contacted.” “Only Germany.” “Show top 5 with emails.” Requirements HubSpot** (OAuth2) Google Gemini** (API key) Notes & customization Property/operator control:** The contact search node lets the agent set both the property (e.g., email, lifecyclestage, hs_lead_status) and the operator (EQ, IN, BETWEEN in epoch ms for dates, etc.). Owner filtering for deals:** Uses hs_all_owner_ids; swap or extend to filter by pipeline/stage ranges. Guardrails:** Add allowlists for searchable properties or cap result counts to avoid noisy answers. Display format:** Have the agent return concise tables (name, email, stage, last activity, CTA). Handoffs:** Add Slack/Email actions—e.g., “post this list to #sales” or “export to CSV.” Telemetry:** Log queries for later dashboards (common searches, coverage gaps). Troubleshooting No results?** Loosen operators (use IN lists, broaden dates) or include a free-text query. Date filters:** Provide epoch ms for GT/GTE/LT/LTE/BETWEEN on time fields (the agent handles this; keep system time in UTC). Too chatty?** Reduce memory window or ask the agent to summarize to bullet points.

Search LinkedIn Companies, Score Them with AI, and Add to Google Sheets CRM Who is this for? This template is designed for sales teams, business development reps, and marketers who need a reliable, automated way to build targeted prospect lists. It’s especially useful for agencies, consultants, and B2B companies that want to identify, qualify, and prioritize high-value leads. What problem does this workflow solve? Researching companies on LinkedIn, evaluating whether they fit your ideal customer profile, and manually updating your CRM can be slow, inconsistent, and labor-intensive. This workflow replaces that entire process with a fully automated system that finds, qualifies, and organizes leads for you. What this workflow does The workflow searches LinkedIn for companies based on your chosen filters, gathers in-depth company details, applies qualification rules, uses AI to score how well each company matches your ICP, and then adds them to your Google Sheets CRM while automatically preventing duplicates. Setup Create a Ghost Genius API account and generate your API key Add your API credentials to the HTTP Request nodes Make a copy of the included Google Sheets template Set up Google Sheets and OpenAI credentials as described in the n8n documentation Customize the Set Variables node to define your audience and AI scoring parameters How to customize this workflow Update your search filters to target specific industries, regions, or company sizes Change the follower count threshold to match your qualification rules Modify the AI scoring prompt to better reflect your product or service Add notifications (email, Slack, etc.) to alert you when high-scoring leads are found

Who's it for Digital marketing agencies and Meta Ads managers who need to generate comprehensive performance reports across multiple client accounts automatically. Perfect for agencies handling 5+ Meta Ads accounts who want to save hours on manual reporting while delivering AI-powered insights to their teams. What it does Pulls performance data from multiple Meta Ads accounts for a specified time period (last 7, 14, or 30 days) Uses Claude AI with Pipeboard's Meta Ads MCP to analyze campaign performance, identify trends, and generate actionable insights Generates professional reports with AI-driven recommendations for optimization Automatically delivers formatted reports to your Slack channels Runs on a schedule (weekly/daily) or triggered manually How to set up Set up Claude AI integration (requires Anthropic API key) Configure Pipeboard's Meta Ads MCP connection Connect Slack to n8n via OAuth2 Create a list of client account IDs in the workflow configuration Customize your reporting template and Slack delivery settings Requirements n8n version 1.109.2 or newer. Claude AI API access (Anthropic) Pipeboard account Slack workspace access How to customize the workflow Adjust the date range and metrics to track Modify the AI prompts for different types of insights Configure multiple Slack channels for different clients Set up custom scheduling intervals Add email delivery as an additional output channel

Description: Stay on top of your support pipeline with this Ticket Status Digest automation for Zendesk. Built in n8n, this workflow automatically fetches tickets from Zendesk, filters only open ones, enriches them with requester details, and saves them into Google Sheets. 📊 Instead of manually checking Zendesk, you get a real-time digest of pending tickets with full customer details—perfect for support leads who need a quick snapshot of unresolved cases. Whether you’re tracking team workload, prioritizing open issues, or preparing daily status reports, this automation ensures your support data is always structured, centralized, and up to date. 🚀 What This Template Does (Step-by-Step) 🔔 Trigger – Manual Start (or Schedule) Begin workflow with a manual trigger (ideal for testing). Can be switched to scheduled runs (daily, hourly) for automated digests. 🎫 Fetch All Tickets (Zendesk) Pulls all tickets from Zendesk API. Captures ticket ID, subject, description, status, priority, tags, and timestamps. 🔍 Filter Open Tickets Only Includes only tickets where status = open. Skips closed, solved, or pending tickets. 👤 User Information Enrichment Looks up requester details (name, email, organization). Converts raw IDs into human-readable contact info. 📊 Save to Google Sheets Appends/updates ticket rows in “Ticket status dummy → Sheet1”. Columns: Ticket No. | Description | Status | Owner | Email | Tag. Required Integrations: Zendesk API (OAuth or API Key) Google Sheets (OAuth2 credentials) Best For: 🧑‍💼 Support leads monitoring unresolved tickets 📈 Managers building daily ticket status dashboards 🤝 Teams that need centralized visibility of customer issues ⏱️ Anyone tired of manual Zendesk data exports Key Benefits: ✅ Automated ticket sync to Google Sheets ✅ Real-time visibility of open issues ✅ Centralized view with enriched requester details ✅ Reduces manual tracking and reporting ✅ Scalable for daily, weekly, or custom digest runs

✅ What problem does this workflow solve? Accounting teams spend hours manually entering purchase bills into accounting systems—copying vendor details, creating items, checking duplicates, and reconciling totals. This workflow removes that manual effort entirely. With OCR + AI + QuickBooks integration, this automation converts uploaded purchase bills into fully reconciled QuickBooks bills—accurately, consistently, and without human intervention. ⚙️ What does this workflow do? Accepts multiple purchase bills in a single upload Extracts structured invoice data using OCR + AI Automatically syncs vendors and items with :contentReference[oaicite:0]{index=0} Creates missing vendors or items when needed Generates clean, validated bills inside QuickBooks Prevents duplicate vendors or line items 🧠 How It Works – Step-by-Step 1. 📤 Upload Purchase Bills Users upload one or multiple PDF bills using an n8n form Each bill is automatically split and processed individually 2. 🔍 OCR & Invoice Data Extraction The workflow extracts text from each PDF An AI extraction engine powered by :contentReference[oaicite:2]{index=2} identifies: Invoice number & dates Vendor details Line items (name, quantity, price, amount) Subtotal, tax, and total 3. 🔄 Item & Vendor Reconciliation (QuickBooks) Fetches existing items from QuickBooks If an item does not exist: Automatically creates it Checks if the vendor exists: Creates a new vendor if missing Ensures zero duplicates in QuickBooks 4. 🧾 Bill Payload Creation Builds a clean QuickBooks-compatible bill payload Maps: Items Vendor Dates Taxes Totals Handles edge cases like missing quantities or unit prices 5. 💰 Bill Creation in QuickBooks Creates a finalized bill inside QuickBooks Each bill is immediately ready for reconciliation and reporting 🛠 Tools & Integrations Used n8n Form Trigger** – Bill upload PDF Extractor** – Text extraction AI Invoice Parser** – Structured data extraction QuickBooks API** – Vendor, item, and bill creation OpenAI / OpenRouter** – Intelligent field mapping 💡 Key Benefits ⏱ Eliminates hours of manual bill entry 🧠 Intelligent OCR with structured extraction 🚫 No duplicate vendors or items ⚡ Instant QuickBooks synchronization 📊 Accurate accounting data every time 👤 Who can use this? Perfect for: 🧾 Accounting teams 🏢 Finance departments 📈 SMBs using QuickBooks 🚀 SaaS platforms automating bookkeeping If you're processing large volumes of purchase bills, this workflow turns documents into structured accounting data—automatically.

Showcase your n8n creator profile with a dynamically generated SVG stats badge, automatically pushed to any GitHub repository on a schedule — ready to embed in your README in seconds. What this workflow does On a configurable schedule, this workflow fetches your public creator profile from the n8n community, builds a fully styled SVG card displaying your name, avatar, total workflows, and community username, then pushes it directly to a GitHub repository. If the file already exists it updates it; if not, it creates it automatically. The final node outputs both the raw GitHub URL and a CDN-cached URL for embedding. What you'll see in your README A clean, animated 495×190px badge showing: Your avatar (circular, pulled live from your n8n profile) Display name and "n8n Creator" label Total workflow count Approved workflow count Community username Direct link to your n8n creator page Setup Open the ⚙️ Config node and fill in your n8n community username, GitHub username, target repository, and your preferred card colors Add your GitHub credentials to both GitHub nodes Adjust the Schedule Trigger to your preferred refresh interval (daily recommended) Activate — the badge will be created on first run and kept up to date automatically Embed in your README Nodes used: Schedule Trigger, Set, HTTP Request, Code, Extract From File, GitHub, Aggregate

How it works A daily schedule pulls your existing contacts from HubSpot All contacts are bulk-enriched with Lusha in a single API call for efficiency A code node compares current Lusha data against CRM records to detect job title or company changes Changed contacts trigger a CRM update and a Slack alert to the assigned rep Set up steps Install the Lusha community node Add your Lusha API, HubSpot, and Slack credentials Adjust the CRM fetch limit based on your contact volume Activate the workflow to run daily

How it works A daily schedule pulls your target accounts from HubSpot All companies are bulk-enriched with Lusha in a single API call A code node detects growth signals: headcount increase, revenue growth, and funding activity For accounts showing signals, Lusha searches for key contacts and alerts your sales team via Slack Set up steps Install the Lusha community node Add your Lusha API, HubSpot, and Slack credentials Define your target account list or ICP filters in HubSpot Set the Slack channel for signal alerts and activate

This n8n template generates a dynamic weekly sales report from Airtable and sends it to Slack. It calculates key sales metrics like total pipeline value, weighted pipeline (based on deal stage), top deal, closed revenue, and win rate.. all formatted in a clean Slack message. How it works A schedule trigger starts the workflow (e.g., every Monday). It fetches deal data from Airtable, splits open vs closed deals, calculates all metrics with JavaScript, and formats the output. The message is then sent to Slack using Markdown for readability. How to use Update the Airtable credentials and select your base and table with fields: Deal Name, Value, Status, etc. Set the Slack channel in the final node to your preferred sales or ops channel. Requirements Airtable base with relevant deal data (see field structure) Slack webhook or token for sending messages Customising this workflow You can adapt the logic to other CRMs like Salesforce or HubSpot, add charts, or tweak stage weights. You can also change the schedule or add filters (e.g., by rep or region).

Maximize your conversion rates with this end-to-end automated outreach and lead nurturing system. This workflow manages the entire sales lifecycle—from instant contact enrollment via WhatsApp to AI-personalized follow-ups and comprehensive A/B performance tracking—all integrated through WATI, Airtable, and OpenAI. 🎯 What This Workflow Does This template operates across four specialized pipelines to ensure no lead is left behind: 📥 Pipeline A: Instant Enrollment Sales reps can enroll a new lead directly from WhatsApp by typing a simple command (e.g., enroll <phone> <name> <company> <campaignId>). The system automatically assigns an A/B testing variant and saves the record to Airtable. ⏰ Pipeline B: Intelligent Follow-up Scheduler Every morning at 9 AM, the bot identifies leads due for a touchpoint. OpenAI generates a unique, personalized message based on the lead's profile and assigned tone (Formal vs. Casual), which is then delivered via WATI. 💬 Pipeline C: Engagement & Intent Tracker Every inbound reply is analyzed by AI to detect the lead's intent (e.g., "Interested", "Question", or "Unsubscribe"). The system automatically updates the CRM status and, if a lead unsubscribes or converts, instantly pauses future automated follow-ups. 📊 Pipeline D: Real-time Analytics By sending the command report, you receive an instant performance dashboard showing conversion rates, total engagement, and a clear comparison of which A/B variant is winning. ✨ Key Features Command-Based Control:** Manage your entire CRM database using simple WhatsApp keywords like enroll, report, and pause. Dynamic Personalization:** OpenAI crafts context-aware messages that mention the lead’s specific company and name, avoiding the "bot feel" of standard templates. Built-in A/B Testing:** Automatically splits leads into two groups to test different messaging strategies and find what converts best. Reputation Protection:** Immediate status updates for "Unsubscribe" or "Not Interested" intents ensure you remain compliant and professional. Rich CRM Integration:** Uses Airtable to store detailed logs of every sent message and received reply for a complete audit trail. 💼 Perfect For SDR & Sales Teams:** Automating the first 5–7 touchpoints so reps can focus only on "Interested" leads. Event Organizers:** Following up with attendees post-webinar or conference. Recruiters:** Managing candidate outreach and tracking initial screening responses. Agencies:** Running outreach campaigns for multiple clients from a single dashboard. 🔧 What You'll Need Required Integrations WATI:** For WhatsApp triggering and message dispatch. Airtable:** To act as your central campaign database. OpenAI API:** For intelligent message generation and intent detection. Configuration Steps Airtable: Create a base with four tables: Contacts Campaigns FollowUps Engagement Airtable IDs: Replace the placeholder Base and Table IDs in all Airtable nodes. WATI: Set up your WATI API credentials. Ready to scale your outreach? Import this template and connect your Airtable to start automating your follow-up campaigns today!

Youtube Video For Workflow Explanation: https://youtu.be/3VTYQU7N6uU This workflow operates as an automated WhatsApp customer service and booking chatbot for an HVAC company (Blankarray HVAC Solutions). It connects WhatsApp, GoHighLevel (for CRM and calendar), and a Gemini AI model to handle customer inquiries, capture contact details, and schedule service appointments. 1. Core Flow (The Main Logic) WhatsApp Trigger** Purpose:** This is the starting point of the workflow. It actively listens for incoming WhatsApp messages and triggers the sequence whenever a new message is received. If Valid Sender Exists** Purpose:** A conditional check to ensure the incoming message has a valid sender phone number (messages[0].from is not empty). This prevents the workflow from failing on empty or malformed requests. Fetch GHL Contacts** Purpose:** Connects to GoHighLevel to search for an existing contact record using the sender's WhatsApp phone number. It always outputs data, which tells the AI later if this is a known customer or a new lead. Customer Service AI Agent1** Purpose:** The central "brain" of the operation. This node orchestrates the conversational logic based on a detailed system prompt. It adopts the persona of "Alex," an HVAC service coordinator. Functionality:** It decides whether to ask for missing user information (Name and Email), when to look up calendar slots, when to book the appointment, and how to format the responses (using WhatsApp-friendly styling). Send WhatsApp Response** Purpose:** The final step in the main execution path. It takes the text output generated by the AI Agent and sends it back to the customer's WhatsApp number. 2. AI Sub-Nodes (The Agent's Toolkit & Brain) These nodes are connected directly to the Customer Service AI Agent1 to give it memory, intelligence, and the ability to take actions. The Brain & Memory Gemini Chat Model** Purpose:** The Large Language Model (LLM) powering the AI Agent. It processes the user's text, understands the context based on your prompt, and generates the natural language response. Redis Chat History Memory** Purpose:** Maintains the context of the conversation. It uses the user's phone number as a unique session key, allowing the AI to remember what was said earlier in the chat rather than treating every message as a brand new interaction. The Action Tools (GoHighLevel Integrations) The AI Agent intelligently decides when to trigger these tools based on the conversation flow. Save user issue in notes** Purpose:** When a customer describes their HVAC problem, the AI uses this tool to immediately log a summary of the issue directly into the customer's GoHighLevel contact profile notes. Create or update a contact in HighLevel** Purpose:** If the "Fetch GHL Contacts" node found no existing record, the AI asks the user for their name and email. Once provided, the AI uses this tool to create a brand new contact profile in GoHighLevel before proceeding to book an appointment. Fetch Available Calendar Slots** Purpose:** When the user wants to book a service, the AI uses this tool to query the GoHighLevel calendar for available 30-minute time slots on the requested date. Book Calendar Appointment** Purpose:** Once the customer agrees to a specific time, the AI uses this tool to officially book the appointment in the GoHighLevel calendar using the Contact ID and the agreed-upon timestamp.