Billy Christi
I build scalable automation systems with n8n to help businesses save time and cut costs. 💼 n8n expert available for new projects 📩 billychartanto@gmail.com
Templates by Billy Christi
Automate blog content creation with OpenAI, Google Sheets & email approval flow
Who is this for? This workflow is perfect for: Digital marketers who need to scale SEO-optimized content production Bloggers and content creators who want to maintain consistent publishing schedules Small business owners who need regular blog content but lack writing resources What problem is this workflow solving? Creating high-quality, SEO-optimized blog content consistently is time-consuming and resource-intensive. This workflow solves that by: Automating the content generation process from topic to final draft Ensuring quality control through human-in-the-loop approval Managing topic queues and preventing duplicate content creation Streamlining the revision process based on human feedback Organizing and archiving all generated content for future reference What this workflow does From topics stored in Google Sheets, this workflow: Automatically retrieves pending topics from your Google Sheets tracking document Generates SEO-optimized blog posts (800-1200 words) using OpenAI GPT-4 with structured prompts Sends content for human approval via email with custom approval forms Handles revision requests by incorporating feedback while maintaining SEO best practices Updates topic status to prevent duplicate processing Add approved generated content in Google Sheets for easy access and management Routes workflow based on approval decisions (approve, revise, or cancel) Setup Copy the Google Sheet template here: 👉 Automate Blog Content Creation – Google Sheet Template Connect Google Sheets with your topic tracking document (requires "Topic List" and "Generated Content" sheets) Add your OpenAI API key to the AI agent nodes for content generation Configure Gmail for the approval notification system Set up your topic list in Google Sheets with "Topic" and "Status" columns Customize the schedule trigger to run at your preferred intervals Update email recipient in the approval node to your email address Test with a sample topic marked as "Pending" in your Google Sheet How to customize this workflow to your needs Adjust content length: modify the word count requirements in the AI agent prompts Change writing style: customize the copywriter prompts for different tones (formal, casual, technical) Add multiple reviewers: extend the approval system to include additional stakeholders Integrate with CMS: add nodes to automatically publish approved content to WordPress, Webflow, or other platforms Include keyword research: add Ahrefs or SEMrush nodes to incorporate keyword data Add image generation: integrate DALL-E or Midjourney for automatic featured image creation Customize approval criteria: modify the approval form to include specific feedback categories Add content scoring: integrate readability checkers or SEO analysis tools before approval Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiAI-powered candidate screening and evaluation workflow using OpenAI and Airtable
Who is this for? This workflow is ideal for: HR professionals and recruiters who want to automate and enhance the hiring process Organizations seeking AI-driven, consistent, and data-backed candidate evaluations Hiring managers using Airtable as their recruitment database --- What problem is this workflow solving? Screening candidates manually is time-consuming, inconsistent, and difficult to scale. This workflow solves that by: Automating resume intake and AI evaluation Matching candidates to job postings dynamically Generating standardized suitability reports Notifying HR only when candidates meet the criteria Storing all applications in a structured Airtable database --- What this workflow does This workflow builds an end-to-end AI-powered hiring pipeline using Airtable, OpenAI, and Google Drive. Here's how it works: Accept candidate applications via a public web form, including resume upload (PDF only) Extract text from uploaded resumes for processing Store resumes in Google Drive and generate shareable links Match the application to a job posting stored in Airtable Use AI to evaluate candidates (via OpenAI GPT-4) against job descriptions and requirements Generate suitability results including: Match percentage Screening status: Suitable, Not Suitable, Under Review Detailed notes Combine AI output and files into one data object Create a new candidate record in Airtable with all application data Automatically notify HR via Gmail if a candidate is marked “Suitable” --- Setup View & Copy the Airtable base here: 👉 Candidate Screening – Airtable Base Template Set up Google Drive folder Connect your OpenAI API key for the AI agent model Connect your Gmail account for email notifications Deploy the public-facing form to start receiving applications Test the workflow using a sample job and resume --- How to customize this workflow to your needs Expand file support: Allow DOC or DOCX uploads by adding format conversion nodes Add multi-recipient email alerts: Extend Gmail node for multiple HR recipients Handle “Under Review” differently: Add additional logic to notify or flag these candidates Send rejection emails automatically: Extend the IF branch for “Not Suitable” candidates Schedule interviews: Integrate with Google Calendar or Calendly APIs Add Slack notifications: Send alerts to team channels for real-time updates Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiAI-Powered Employee Database Management via Telegram using OpenAI and Airtable
Who is this for? This workflow is perfect for: HR professionals seeking to automate employee and department management Startups and SMBs that want an AI-powered HR assistant on Telegram Internal operations teams that want to simplify onboarding and employee data tracking --- What problem is this workflow solving? Managing employee databases manually is error-prone and inefficient—especially for growing teams. This workflow solves that by: Enabling natural language-based HR operations directly through Telegram Automating the creation, retrieval, and deletion of employee records in Airtable Dynamically managing related data such as departments and job titles Handling data consistency and linking across relational tables automatically Providing a conversational interface backed by OpenAI for smart decision-making --- What this workflow does Using Telegram as the interface and Airtable as the backend database, this intelligent HR workflow allows users to: Chat in natural language (e.g. “Show me all employees” or “Create employee: Sarah, Marketing…”) Interpret and route requests via an AI Agent that acts as the orchestrator Query employee, department, and job title data from Airtable Create or update records as needed: Add new departments and job titles automatically if they don’t exist Create new employees and link them to the correct department and job title Delete employees based on ID Respond directly in Telegram, providing user-friendly feedback --- Setup View & Copy the Airtable base here: 👉 Employee Database Management – Airtable Base Template Telegram Bot: Set up a Telegram bot and connect it to the Telegram Trigger node Airtable: Prepare three Airtable tables: Employees with links to Departments and Job Titles Departments with Name & Description Job Titles with Title & Description Connect your Airtable API key and base/table IDs into the appropriate Airtable nodes Add your OpenAI API key to the AI Agent nodes Deploy both workflows: the main chatbot workflow and the employee creation sub-workflow Test with sample messages like: “Create employee: John Doe, john@company.com, Engineering, Software Engineer” “Remove employee ID rec123xyz” --- How to customize this workflow to your needs Switch databases: Replace Airtable with Notion, PostgreSQL, or Google Sheets if desired Enhance security: Add authentication and validation before allowing deletion Add approval flows: Integrate Telegram button-based approvals for sensitive actions Multi-language support: Expand system prompts to support multiple languages Add logging: Store every user action in a log table for auditability Expand capabilities: Integrate payroll, time tracking, or Slack notifications --- Extra Tips This is a two-workflow setup. Make sure the sub-workflow is deployed and accessible from the main agent. Use Simple Memory per chat ID to preserve context across user queries. You can expand the orchestration logic by adding more tools to the main agent—such as “Get active employees only” or “List employees by job title.” --- Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiAuto-respond to Gmail inquiries using OpenAI, Google Sheet & AI agent
Who is this for? This workflow is ideal for: Customer support teams looking to reduce manual response time SaaS companies that frequently receive product inquiries E-commerce stores with common customer questions about orders, shipping, and returns What problem is this workflow solving? Manually responding to repetitive customer emails is inefficient, prone to inconsistency, and time-consuming. This workflow solves the issue by: Automatically replying to real customer inquiries 24/7 Ensuring every response is consistent, friendly, and based on approved knowledge Preventing responses to non-inquiries like newsletters or confirmations Logging every interaction for traceability, analysis, and compliance What this workflow does This AI-powered Gmail auto-responder intelligently handles inbound emails with the following steps: Monitors your Gmail inbox for new incoming emails in real time Classifies each email as either an “Inquiry” or “Not Inquiry” using GPT-4 Gets context from a Google Sheets FAQ database The context will be used to determine the most accurate and helpful response Generates a professional reply only if it’s a valid inquiry (e.g., pricing, refund, product details) Builds a context-aware, helpful response using verified knowledge only Sends the reply to the original sender automatically Logs everything to a Google Sheet — original email, AI response, timestamp, and email address Example Use Case: An email comes in: "Hi, I want to know your pricing and refund policy." The workflow: Detects it’s an inquiry Finds the pricing and refund FAQs in your Google Sheet Sends back a professional response like: "Hi! Thanks for reaching out. Our pricing starts at \$99/month. Refunds can be requested within 30 days of purchase. Let us know if you have more questions!" Logs the interaction to your “Enquiry\_Log” tab Setup Copy the Google Sheet template here: 👉 Gmail Auto-Responder – Google Sheet Template This contains: A FAQ_Context tab (your knowledge base) An Enquiry_Log tab (interaction logs) Connect your Gmail account to the Gmail Trigger and Gmail Send nodes Add your OpenAI API key in the classification and response generator nodes Link the Google Sheet in both the FAQ lookup and logging nodes Test with a sample email — try asking a pricing and refund question to see the complete process in action How to customize this workflow to your needs Adjust tone or brand voice in the AI prompt for a more casual or formal reply Modify classification rules if your use case includes more custom logic Expand the FAQ database to include new questions and answers Add multilingual support by customizing the AI prompt to detect and respond in different languages Integrate CRM or ticketing systems (like HubSpot, Zendesk, or Notion) to log or escalate unanswered queries Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiExtract specific website data with form input, Gemini 2.5 flash and Gmail
What this workflow does This workflow creates an automated web scraper that accepts form submissions, extracts specific data from any website using AI, and emails the results back to you. Step by step: Web Scraper Form Submission provides a web form interface where users submit a URL and specify what data to extract Get HTML from Source URL fetches the complete HTML content from the provided website HTML Extractor processes the raw HTML and extracts the body content for analysis Data Extractor LLM Chain uses Google Gemini AI to intelligently analyze the content and extract only the specific data requested by the user Structured Output Parser formats the AI response into clean JSON structure with standardized format Gmail Send Result delivers the extraction results via email including the source URL, extraction request details, and clean extracted results How to set up Connect your Google Gemini API to the Google Gemini Chat Model node for AI-powered data extraction Connect your Gmail account to the Gmail node for sending result emails Update the recipient email in the Gmail node Customize the extraction prompt in the Data Extractor LLM Chain node based on your specific requirements How to customize this workflow to your needs Switch AI models: Replace Google Gemini with OpenAI, Claude, or other LLM providers in the Chat Model node based on your accuracy requirements and budget preferences Change result delivery: Replace Gmail with Google Sheets for data storage, Outlook for corporate email, Slack for team notifications, or webhook integrations for custom applications Customize extraction prompts: Modify the LLM prompt in the Data Extractor Chain to handle specific data types, extraction formats, or industry-specific terminology for your use case Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiDaily Jira ticket summarizer using GPT-5 and Jira API
Who is this for? This workflow is perfect for: Support teams and customer service departments managing Jira tickets Team leads and managers who need daily visibility into ticket resolution progress Organizations wanting to automate ticket reporting and communication IT departments seeking to streamline support ticket summarization and tracking What problem is this workflow solving? Manual ticket review and reporting is time-consuming and often lacks comprehensive analysis. This workflow solves those issues by: Automating daily ticket analysis by fetching, analyzing, and summarizing all tickets created each day Providing intelligent summaries using AI to extract key insights from ticket descriptions, comments, and resolutions Streamlining communication by automatically sending formatted daily reports to stakeholders Saving time by eliminating manual ticket review and report generation What this workflow does This workflow automatically fetches daily Jira tickets, analyzes them with AI, and sends comprehensive summaries via email to keep your team informed about support activities. Step by step: Schedule Trigger runs the workflow automatically at your chosen interval (or manual trigger for testing) Set Project Key defines the Jira project to monitor (default: SUP project) Get All Tickets from the specified project created today Split Out extracts individual ticket data including key, summary, and description Loop Tickets processes each ticket individually through batch processing Get Comments from Ticket retrieves all comments and conversations for complete context Merge combines ticket data with associated comments for comprehensive analysis Ticket Summarizer (AI Agent) uses OpenAI GPT-5 to generate professional summaries and proposed solutions Set Output structures the AI analysis into standardized JSON format Aggregate collects all processed ticket summaries into a single dataset Format Body creates a readable email format with direct Jira ticket links Send Ticket Summaries delivers the daily report via Gmail How to set up Connect your Jira account by adding your Jira Software Cloud API credentials to the Jira nodes Add your OpenAI API key to the OpenAI Chat Model node for AI-powered ticket analysis Configure Gmail credentials for the Send Ticket Summaries node to deliver reports Update the recipient email in the "Send Ticket Summaries" node to your desired recipient Adjust the project key in the "Set Project Key" node to match your Jira project identifier Configure the schedule trigger to run daily at your preferred time for automatic reporting Customize the JQL query in Jira nodes to filter tickets based on your specific requirements Test the workflow using the manual trigger to ensure proper ticket fetching and AI analysis Review email formatting in the "Format Body" node and adjust as needed for your reporting style How to customize this workflow to your needs Modify AI prompts: customize the ticket analysis prompt in the "Ticket Summarizer" node to focus on specific aspects like priority, resolution time, or customer impact Adjust ticket filters: change the JQL queries to filter by status, priority, assignee, or custom date ranges beyond "today" Add more data points: include additional ticket fields like priority, status, assignee, or custom fields in the analysis Customize email format: modify the "Format Body" node to change the report structure, add charts, or include additional formatting Set up different schedules: create multiple versions for different reporting frequencies (hourly, weekly, monthly) Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiWorkflow error logging and alerts with Google Sheets and Gmail
What this workflow does This workflow creates a comprehensive error monitoring system for your n8n instance by automatically capturing workflow failures, logging them to Google Sheets, and sending immediate email notifications. Step by step: Error Trigger automatically activates whenever any workflow in your n8n instance encounters an error or failure Google Sheets - Create Error Log captures and stores comprehensive error details in a spreadsheet including workflow information, node details, timestamps, and full error stack traces Gmail - Send Notification dispatches immediate email alerts with formatted error summaries containing workflow names, failed nodes, error descriptions, and direct links to failed executions How to set up Copy the Google Sheets template structure from this link: https://docs.google.com/spreadsheets/d/11-vLBAKolEvaL0qQDjckHmvC1S6_hxHbgSP8CLyngSs/edit?gid=0gid=0 - This step is crucial as it provides the correct column structure for error logging Connect your Google Sheets account to the Google Sheets node and update the document ID to point to your copied error logging spreadsheet Connect your Gmail account to the Gmail node for sending error notifications Update the Gmail recipient email from "n8nlogtemplate@yopmail.com" to your preferred notification email address Customize email subject and message format according to your notification preferences and organizational needs Test the workflow by intentionally creating a small error in a test workflow to verify the logging and notification system works correctly Monitor your error logs regularly through the Google Sheets document to identify patterns and recurring issues How to customize this workflow to your needs Add multiple notification recipients: modify the Gmail node to send alerts to different team members or create separate nodes for different notification channels (Slack, Discord, etc.) Customize error filtering: add conditional logic to only log certain types of errors or exclude specific workflows from monitoring Enhance error categorization: add additional columns to your Google Sheets template for error severity levels, affected systems, or resolution status tracking Set up error escalation: create time-based triggers that send follow-up notifications for unresolved errors after specific time periods Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiAutomate agile project setup with GPT-5 Mini, Jira & form interface
Who is this for? This workflow is perfect for: Agile development teams and project managers who need to quickly set up Jira projects Product managers who want to convert feature ideas into structured user stories and tasks Software development agencies that need to rapidly create detailed project structures for clients Scrum masters seeking to automate the initial project setup and backlog creation process What problem is this workflow solving? Creating comprehensive Jira projects with detailed user stories and sub-tasks is time-consuming and often inconsistent. This workflow solves those issues by: Automating project creation from basic feature descriptions to fully structured Jira projects Generating professional user stories following Agile best practices with proper "As a [user], I want to [goal], so that [benefit]" formatting Creating detailed sub-tasks covering design, development, testing, and documentation phases What this workflow does This workflow transforms raw project ideas into fully structured Jira projects with comprehensive user stories and sub-tasks using AI-powered analysis and automated Jira integration. Step by step: Form Trigger collects project name and feature descriptions through a web form Project Naming uses GPT-4.1 mini to clean and professionalize the project name while generating a unique project key Create Project establishes a new Jira project with proper software development template and configuration Get Status ID retrieves project details and available issue types for story creation Jira Story Generator analyzes project features using AI to create structured user stories with sub-tasks Create Story generates individual Jira stories with proper titles and descriptions Execute Sub-task Workflow automatically creates all associated sub-tasks for each story Gmail Notification sends completion confirmation with project details and direct links How to set up Connect your Jira account by adding your Jira Software Cloud API credentials to all Jira-related nodes Update Jira URL in the "Set Jira URL" node to match your Jira instance (e.g., https://yourcompany.atlassian.net) Add OpenAI API key to the OpenAI Chat Model node for AI-powered story generation Configure Gmail credentials for the notification node and update the recipient email address Update project lead in the Create Project node by replacing the leadAccountId with your user ID Test the workflow using the manual trigger with sample project data Customize story templates in the Structured Output Parser if you need different story formats Set up the sub-workflow by ensuring the Execute Workflow node points to the correct workflow ID How to customize this workflow to your needs Adjust story generation prompts: modify the AI prompts in the "Jira Story Generator" to match your team's specific story writing style or include additional fields Include estimation: add story point estimation logic or time tracking fields to generated stories Switch AI models: replace the OpenAI Chat Model node with other AI providers like Google Gemini, Claude, or local models by using the appropriate n8n AI nodes for different cost and performance requirements Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiAgile project generator with ClickUp task hierarchy using GPT-5 & forms
Who is this for? This workflow is perfect for: Project managers and Agile teams who want to automate project setup and task creation Software development teams looking to standardize their project initialization process Business analysts and product owners who need to quickly convert project ideas into structured task breakdowns Companies using ClickUp for project management who want to leverage AI for intelligent project planning What problem is this workflow solving? Creating comprehensive project structures with detailed tasks and subtasks is time-consuming and often inconsistent. This workflow solves those issues by: Automating project creation from initial concept to fully structured ClickUp project with tasks and subtasks Standardizing task breakdown using AI to generate professional Agile user stories with proper descriptions Eliminating manual setup while ensuring consistency across all projects and teams Improving project planning quality through AI-driven task analysis and structured output What this workflow does This workflow transforms raw project ideas into complete, professional ClickUp projects with AI-generated task breakdowns and subtasks, following Agile best practices. Step by step: Form Trigger captures project details through a web form (Project Name and Full Features description) Project Naming AI Agent uses OpenAI to clean up project names, create professional descriptions, and generate random Jira-style project keys ClickUp Create List establishes the main project list in your ClickUp workspace Task Generator AI Agent analyzes project features and creates detailed task breakdown following Agile user story format Split Out breaks down the AI-generated task array into individual items for processing Loop Over Items processes each main task individually through batch processing ClickUp Create Task creates each main task with descriptions in the project list Split Out Subtasks extracts subtasks from each main task for individual processing Execute Sub-workflow triggers the subtask creation workflow to build parent-child task relationships Gmail Notification sends success notification email with project link and list ID Sub-workflow Loop handles individual subtask creation in ClickUp with proper parent task relationships How to set up Connect your OpenAI account by adding your API key to the OpenAI Chat Model node for AI-powered project analysis Configure ClickUp credentials by adding your ClickUp API key and updating team ID and space ID for your workspace Set up Gmail OAuth2 credential for sending notification emails Update email recipient in the Gmail node from the placeholder email to your actual email address Configure the Execute Workflow node to reference the correct sub-workflow ID for subtask creation Customize the form fields in the Form Trigger node based on your project input requirements Test the workflow with a sample project to ensure proper task generation and ClickUp integration Verify notifications are being sent correctly with proper project links How to customize this workflow to your needs Modify task generation prompts: adjust the AI prompts in the Task Generator node to match your specific project methodology or industry requirements Add custom fields: enhance the form trigger with additional project metadata fields like priority, team assignment, or project type Switch AI models: replace the OpenAI Chat Model node with other AI providers like Google Gemini, Claude, or local models by using the appropriate n8n AI nodes for different cost and performance requirements Need help customizing? Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy Christi