Workflow Templates

This workflow provides automated access to the Settyan Flash V2.0.0 Beta.10 AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for other generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete other generation process using the Settyan Flash V2.0.0 Beta.10 model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: Advanced AI model for automated processing and generation tasks. Key Capabilities Specialized AI model with unique capabilities** Advanced processing and generation features** Custom AI-powered automation tools** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Settyan/flash-v2.0.0-beta.10 AI model Settyan Flash V2.0.0 Beta.10**: The core AI model for other generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Other Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Specialized Processing**: Handle specific AI tasks and workflows Custom Automation**: Implement unique business logic and processing Data Processing**: Transform and analyze various types of data AI Integration**: Add AI capabilities to existing systems and workflows Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #aiprocessing #dataprocessing #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

This workflow provides automated access to the Settyan Flash V2.0.2 Beta.10 AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for other generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete other generation process using the Settyan Flash V2.0.2 Beta.10 model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: Advanced AI model for automated processing and generation tasks. Key Capabilities Specialized AI model with unique capabilities** Advanced processing and generation features** Custom AI-powered automation tools** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Settyan/flash-v2.0.2-beta.10 AI model Settyan Flash V2.0.2 Beta.10**: The core AI model for other generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Other Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Specialized Processing**: Handle specific AI tasks and workflows Custom Automation**: Implement unique business logic and processing Data Processing**: Transform and analyze various types of data AI Integration**: Add AI capabilities to existing systems and workflows Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #aiprocessing #dataprocessing #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

This workflow provides automated access to the Settyan Flash V2.0.0 Beta.0 AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for other generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete other generation process using the Settyan Flash V2.0.0 Beta.0 model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: Advanced AI model for automated processing and generation tasks. Key Capabilities Specialized AI model with unique capabilities** Advanced processing and generation features** Custom AI-powered automation tools** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Settyan/flash-v2.0.0-beta.0 AI model Settyan Flash V2.0.0 Beta.0**: The core AI model for other generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Other Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Specialized Processing**: Handle specific AI tasks and workflows Custom Automation**: Implement unique business logic and processing Data Processing**: Transform and analyze various types of data AI Integration**: Add AI capabilities to existing systems and workflows Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #aiprocessing #dataprocessing #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation

Task: Make sure that data is in the right format before injecting it into a database/spreadsheet/CRM/etc. Why: Spreadsheets and databases require the incoming data to have the same fields as the headers of the destination table. You can decide which fields you would like to send with the database and rename them by using the set node Main use cases: Change fields names to match a database or a spreadsheet table structure Keep only the fields that are needed at the destination table

Description Process new resumes from Google Drive, extract structured candidate data with AI, save to Google Sheets, and auto-create a ClickUp hiring task. Gain a centralized, searchable candidate database and instant task kickoff—no manual data entry. 🚀 What This Template Does Watches a Google Drive folder for new resume PDFs and triggers the workflow. 📂 Downloads the file and converts the PDF to clean, readable text. 📄 Analyzes resume text with an AI Resume Analyzer to extract structured candidate info (name, email, phone, experience, skills, education). 🤖 Cleans and validates the AI JSON output for reliability. 🧹 Appends or updates a candidate row in Google Sheets and creates a ClickUp hiring task. ✅ Key Benefits Save hours with end-to-end, hands-off resume processing. ⏱️ Never miss a candidate—every upload triggers automatically. 🔔 Keep a single source of truth in Sheets, always up-to-date. 📊 Kickstart hiring instantly with auto-created ClickUp tasks. 🗂 Works with varied resume formats using AI extraction. 🧠 Features Google Drive “Watch for New Resumes” trigger (every minute). ⏲ PDF-to-text extraction optimized for text-based PDFs. 📘 AI-powered resume parsing into standardized JSON fields. 🧩 JSON cleanup and validation for safe storage. 🧰 Google Sheets append-or-update for a central candidate database. 📑 ClickUp task creation with candidate-specific titles and assignment. 🎯 Requirements n8n instance (cloud or self-hosted); recommended n8n version 1.106.3 or higher. 🔧 Google Drive access to a dedicated resumes folder (PDF resumes recommended). 📂 Google Sheets credential with edit access to the candidate database sheet. 📈 ClickUp workspace/project access to create tasks for hiring. 📌 AI service credentials for the Resume Analyzer step (add in n8n Credentials). 🤖 Target Audience HR and Talent Acquisition teams needing faster screening. 👥 Recruiters and staffing agencies handling high volumes. 🏢 Startups and ops teams standardizing candidate intake. 🚀 No-code/low-code builders automating hiring workflows. 🧩 Step-by-Step Setup Instructions Connect Google Drive, Google Sheets, ClickUp, and your AI service in n8n Credentials. 🔐 Set the Google Drive “watched” folder (e.g., Resume_store). 📁 Import the workflow, assign credentials to all nodes, and map your Sheets columns. 🗂️ Adjust the ClickUp task details (title pattern, assignee, list). 📝 Run once with a sample PDF to test, then enable scheduling (every 1 minute). ▶️ Optionally rename the email/task nodes for clarity (e.g., “Create Hiring Task in ClickUp”). ✍️

This n8n template empowers IT support teams by automating document ingestion and instant query resolution through a conversational AI. It integrates Google Drive, Pinecone, and a Chat AI agent (using Google Gemini/OpenRouter) to transform static support documents into an interactive, searchable knowledge base. With two interlinked workflows—one for processing support documents and one for handling chat queries—employees receive fast, context-aware answers directly from your support documentation. Overview Document Ingestion Workflow Google Drive Trigger:** Monitors a specified folder for new file uploads (e.g., updated support documents). File Download & Extraction:** Automatically downloads new files and extracts text content. Data Cleaning & Text Splitting:** Utilizes a Code node to remove line breaks, trim extra spaces, and strip special characters, while a text splitter segments the content into manageable chunks. Embedding & Storage:** Generates text embeddings using Google Gemini and stores them in a Pinecone vector store for rapid similarity search. Chat Query Workflow Chat Trigger:** Initiates when an employee sends a support query. Vector Search & Context Retrieval:** Retrieves the top relevant document segments from Pinecone based on similarity scores. Prompt Construction:** A Code node combines the retrieved document snippets with the user’s query into a detailed prompt. AI Agent Response:** The constructed prompt is sent to an AI agent (using OpenRouter Chat Model) to generate a clear, step-by-step solution. Key Benefits & Use Case Imagine a large organization where every IT support document—from troubleshooting guides to system configurations—is stored in a single Google Drive folder. When an employee encounters an issue (e.g., “How do I reset my VPN credentials?”), they simply type the query into a chat interface. Instantly, the workflow retrieves the most relevant context from the ingested documents and provides a detailed, actionable answer. This process reduces resolution times, enhances support consistency, and significantly lightens the load on IT staff. Prerequisites A valid Google Drive account with access to the designated folder. A Pinecone account for storing and retrieving text embeddings. Google Gemini* (or *OpenRouter**) credentials to power the Chat AI agent. An operational n8n instance configured with the necessary nodes and credentials. Workflow Details 1 Document Ingestion Workflow Google Drive Trigger Node:** Listens for file creation events in the specified folder. Google Drive Download Node:** Downloads the newly added file. Extract from File Node:** Extracts text content from the downloaded file. Code Node (Data Cleaning):** Cleans the extracted text by removing line breaks, trimming spaces, and eliminating special characters. Recursive Text Splitter Node:** Segments the cleaned text into manageable chunks. Pinecone Vector Store Node:** Generates embeddings (via Google Gemini) and uploads the chunks to Pinecone. 2 Chat Query Workflow Chat Trigger Node:** Receives incoming user queries. Pinecone Vector Store Node (Query):** Searches for relevant document chunks based on the query. Code Node (Context Builder):** Sorts the retrieved documents by relevance and constructs a prompt merging the context with the query. AI Agent Node:** Sends the prompt to the Chat AI agent, which returns a detailed answer. How to Use Import the Template: Import the template into your n8n instance. Configure the Google Drive Trigger: Set the folder ID (e.g., 1RQvAHIw8cQbtwI9ZvdVV0k0x6TM6H12P) and connect your Google Drive credentials. Set Up Pinecone Nodes: Enter your Pinecone index details and credentials. Configure the Chat AI Agent: Provide your Google Gemini (or OpenRouter) API credentials. Test the Workflows: Validate the document ingestion workflow by uploading a sample support document. Validate the chat query workflow by sending a test query and verifying the returned support information. Additional Notes Ensure all credentials (Google Drive, Pinecone, and Chat AI) are correctly set up and tested before deploying the workflows in production. The template is fully customizable. Adjust the text cleaning, splitting parameters, or the number of document chunks retrieved based on your support documentation's size and structure. This template not only enhances IT support efficiency but also offers a scalable solution for managing and leveraging growing volumes of support content.

🚀 HR Resume Screening Workflow — Smart Hiring on Autopilot 🤖 🎯 Overview: "This workflow builds an AI-powered resume screening system inside n8n. It begins with Gmail and Form triggers that capture incoming resumes, then uploads each file to Google Drive for storage. The resume is downloaded and converted into plain text, where two branches run in parallel: one extracts structured contact details, and the other uses an AI agent to summarize education, job history, and skills while assigning a suitability score. A cleanup step normalizes the data before merging both outputs, and the final candidate record is saved into Google Sheets and Airtable, giving recruiters a centralized dashboard to identify top talent quickly and consistently.” 🔑 Prerequisites: To run this workflow successfully, you’ll need: Gmail OAuth** → to read incoming resumes. Google Drive OAuth** → to upload and download resume files. Google Sheets OAuth** → to save structured candidate records. Airtable Personal Access Token** → for dashboards and record-keeping. OpenAI / OpenRouter API Key** → to run the AI summarizer and evaluator. ⚙️ Setup Instructions: Import the Workflow Clone or import the workflow into your n8n instance. Add Credentials Go to n8n → Credentials and connect Gmail, Google Drive, Google Sheets, Airtable, and OpenRouter/OpenAI. Configure Key Nodes Gmail Trigger → Update filters.q with the job title you are hiring for (e.g., "Senior Software Engineer"). Google Drive Upload → Set the folderId where resumes will be stored. Google Sheets Node → Link to your HR spreadsheet (e.g., “Candidates 2025”). Airtable Node → Select the correct base & table schema for candidate records. Test the Workflow Send a test resume (via email or form). Check Google Sheets & Airtable for structured candidate data. Go Live Enable the workflow. It will now run continuously and process new resumes as they arrive. 📊 End-to-End Workflow Walkthrough: 🟢 Section 1 – Entry & Intake Nodes: 📧 Gmail Trigger → Polls inbox every minute, captures job application emails, and downloads resume attachments (CV0, CV1, …). 🌐 Form Trigger → Alternate entry for resumes submitted via a careers page or job portal. ✅ Quick Understanding: Think of this section as the front desk of recruitment - resumes received either by email or online form, and the system immediately grabs them for processing. 📂 Section 2 – File Management Nodes: ☁️ Upload File (Google Drive) → Saves the incoming resume into a structured Google Drive folder, naming it after the applicant. ⬇️ Download File (Google Drive) → Retrieves the stored resume file for further processing. 🔎 Extract from File → Converts the resume (PDF/DOC) into plain text so the AI and extractors can work with it. ✅ Quick Understanding: This is your digital filing room. Every resume is safely stored, then converted into a readable format for the hiring system. 🤖 Section 3 – AI Processing (Parallel Analysis) Nodes: 🧾 Information Extractor → Pulls structured contact information (candidate name, candidate email and candidate phone number) using regex validation and schema rules. 🤖 AI Agent (LangChain + OpenRouter) → Reads the full CV and outputs: 🎓 Educational Qualifications 💼 Job History 🛠 Skills Set 📊 Candidate Evaluation Score (1–10) 📝 Justification for the score ✅ Quick Understanding: Imagine having two assistants working in parallel, one quickly extracts basic contact info, while the other deeply reviews the CV and gives an evaluation. 🛠️ Section 4 – Data Cleanup & Merging Nodes: ✏️ Edit Fields → Standardizes the AI Agent’s output into a consistent field (output). 🛠 Code (JS Parsing & Cleanup) → Converts the AI’s free-text summary into clean JSON fields (education, jobHistory, skills, score, justification). 🔗 Merge → Combines the structured contact info with the AI’s evaluation into a single candidate record. ✅ Quick Understanding: This is like the data cleaning and reporting team, making sure all details are neat, structured, and merged into one complete candidate profile. 📊 Section 5 – Persistence & Dashboards Nodes: 📑 Google Sheets (Append Row) → Saves candidate details into a Google Sheet for quick team access. 🗄 Airtable (Create Record) → Stores the same structured data into Airtable, enabling dashboards, analytics, and ATS-like tracking. ✅ Quick Understanding: Think of this as your HR dashboard and database. Every candidate record is logged in both Google Sheets and Airtable, ready for filtering, reporting, or further action. 📊 Workflow Overview Table: | Section | Key Roles / Nodes | Model / Service | Purpose | Benefit | | --- | --- | --- | --- | --- | | 📥 Entry & Intake | Gmail Trigger, Form Trigger | Gmail API / Webhook | Capture resumes from email or forms | Resumes collected instantly from multiple sources | | 📂 File Management | Google Drive Upload, Google Drive Download, Extract from File | Google Drive + n8n Extract | Store resumes & convert to plain text | Centralized storage + text extraction for processing | | 🤖 AI Processing | Information Extractor, AI Agent (LangChain + OpenRouter) | Regex + OpenRouter AI {gpt-oss-20b (free)} | Extract contact info + AI CV analysis | Candidate details + score + justification generated automatically | | 🛠 Data Cleanup & Merge | Edit Fields, Code (JS Parsing & Cleanup), Merge | n8n native + Regex Parsing | Standardize and merge outputs | Clean, structured JSON record with all candidate info | | 📊 Persistence Layer | Google Sheets Append Row, Airtable Create Record | Google Sheets + Airtable APIs | Store structured candidate data | HR dashboards & ATS-ready records for easy review and analytics | | 🔄 Execution Flow | All connected | Gmail + Drive + Sheets + Airtable + AI | End-to-end automation | Automated resume → structured record → recruiter dashboards | 📂 Workflow Output Overview: Each candidate’s data is standardized into the following fields: Candidate Name Candidate Email Contact Number Educational Qualifications Job History Skills Set AI Score (1–10) Justification 📌 Example (Google Sheet row): 📊 Benefits of This Workflow at a Glance: ⏱️ Lightning-Fast Screening** → Processes hundreds of resumes in minutes instead of hours. 🤖 AI-Powered Evaluation** → Automatically summarizes candidate education, work history, skills, and gives a suitability score (1–10) with justification. 📂 Centralized Storage** → Every resume is securely saved in Google Drive for easy access and record-keeping. 📊 Data-Ready Outputs** → Structured candidate profiles go straight into Google Sheets and Airtable, ready for dashboards and analytics. ✅ Consistency & Fairness** → Standardized AI scoring ensures every candidate is evaluated on the same criteria, reducing human bias. 🛠️ Flexible Intake** → Works with both Gmail (email applications) and Form submissions (job portals or career pages). 🚀 Recruiter Productivity Boost** → Frees HR teams from manual extraction and data entry, allowing them to focus on interviewing and hiring the best talent. 👉 Practical HR Use Case: “Screen resumes for a Senior Software Engineer role and shortlist top candidates.” Gmail Trigger → Captures incoming job applications with CVs attached. Google Drive → Stores resumes for record-keeping. Extract from File → Converts CVs into plain text. Information Extractor → Pulls candidate name, email, and phone number. AI Agent → Summarizes education, job history, skills, and assigns a suitability score (1–10). Code & Merge → Cleans and combines outputs into a structured candidate profile. Google Sheets → Logs candidate data for quick HR review. Airtable → Builds dashboards to filter and identify top-scoring candidates. ✅ Result: HR instantly sees structured candidate records, filters by score, and focuses interviews on the best talent.

This workflow transforms traditional REST APIs into structured, AI-accessible MCP (Model Context Protocol) tools. It provides a unified gateway that allows Claude AI to safely, granularly, and auditibly interact with any business system — CRM, ERP, databases, SaaS — through a single MCP-compliant interface. How it works Receive MCP Tool Request - Webhook ingests tool call from AI agent or MCP client Validate & Authenticate - Verifies API key, checks JWT token, validates MCP schema Tool Registry Lookup - Resolves requested tool name to backend API config and permission scope Claude AI Intent Verification - Confirms tool call parameters are safe, well-formed, and within policy Rate Limit & Quota Check - Enforces per-client tool call limits before execution Execute Backend API Call - Routes to the correct business system API with mapped parameters Normalize & Enrich Response - Standardizes API response into MCP tool result schema Audit & Log - Writes immutable access log for compliance and observability Return MCP Tool Result - Delivers structured response back to the AI agent Setup Steps Import workflow into n8n Configure credentials: Anthropic API - Claude AI for intent verification and parameter validation Google Sheets - Tool registry, rate limit tracking, and audit log SMTP - Alert notifications for policy violations Populate the Tool Registry sheet with your API endpoints Set your MCP gateway API key in the validation node Activate the workflow and point your MCP client to the webhook URL Sample MCP Tool Call Payload { "mcpVersion": "1.0", "clientId": "agent-crm-001", "apiKey": "mcp-key-xxxx", "toolName": "crm.get_customer", "parameters": { "customerId": "CUST-10042", "fields": ["name", "email", "tier"] }, "requestId": "req-abc-123", "callerContext": "User asked: show me customer details" } Supported Tool Categories CRM Tools** — get_customer, update_contact, list_deals ERP Tools** — get_inventory, create_order, update_stock Database Tools** — query_records, insert_record, update_record Communication Tools** — send_email, post_slack, create_ticket Analytics Tools** — run_report, fetch_metrics, export_data Features MCP-compliant schema** — works with any MCP-compatible AI agent Granular permission scopes** — read/write/admin per tool per client Claude AI intent guard** — blocks malformed or policy-violating calls Rate limiting** — per-client quota enforcement Full audit trail** — every tool call logged for SOC2 / ISO 27001 Explore More Automation: Contact us to design AI-powered lead nurturing, content engagement, and multi-platform reply workflows tailored to your growth strategy.

Quick overview This workflow ingests a local PDF into Qdrant with Ollama embeddings, then supports hybrid retrieval by querying Qdrant with both dense vectors and BM25 sparse vectors from an n8n chat trigger. How it works Starts manually to read a PDF from disk and extract its text content. Checks whether the Qdrant collection exists and creates it with a 768-dimension dense vector and a BM25-based sparse vector field if needed. Splits the extracted text into chunks, adds metadata, generates dense embeddings with Ollama (nomic-embed-text), and inserts the documents into the Qdrant vector store. Scrolls all stored points from Qdrant, builds a per-point BM25 sparse vector payload from each point’s content, and updates Qdrant vectors without overwriting existing fields. Triggers on an incoming chat message, generates an embedding for the query via Ollama’s embeddings HTTP API, and runs a Qdrant hybrid search that fuses dense and BM25 results using RRF. Setup Configure Qdrant credentials (REST API and Vector Store) and ensure the workflow points to the correct Qdrant URL/collection name (default: collection "testing"). Set up Ollama credentials and ensure the nomic-embed-text:latest model is available, and update the embeddings endpoint URL if your Ollama host is not http://host.docker.internal:11434. Place the source PDF on the n8n host and update the file path in the disk read step (default: /tmp/n8n_Self_Hosted_Enterprise_Terms_and_Conditions.pdf). Enable the chat trigger and use its webhook/chat entry point to send queries into the workflow.

1. Who this is for This workflow is specifically designed for Recruiters, HR analytics teams, and data-driven talent acquisition professionals seeking deeper insights from candidate resume. Valuable for HR tech developers, ATS/CRM engineers, and AI-driven recruitment platforms aiming to automate candidate research. Helps organizations build predictive hiring models and gain actionable talent intelligence. 2. What problem this workflow solves Recruiters often face information overload when analyzing candidate resume manually reviewing experiences, skills, and cultural fit is slow and inconsistent. Traditional scraping tools extract raw data but fail to produce actionable intelligence like career trajectory, skills alignment, and fit for a role. This workflow solves that by: Automating candidate resume data extraction through Decodo Structuring it into JSON Resume Schema Running deep AI-driven analytics using OpenAI GPT-4o-mini Delivering comprehensive candidate intelligence ready for ATS/CRM integration or HR dashboards 3. What this workflow does This n8n workflow combines Decodo’s web scraping with OpenAI GPT-4o-mini to produce advanced recruitment intelligence. Flow Breakdown: Manual Trigger – Start the workflow manually or schedule it in n8n. Set Input Fields – Define resume URL, location, and job description. Decodo Node – Scrapes the candidate’s profile (experience, skills, education, achievements, etc.). Structured Data Extractor (GPT-4o-mini) – Converts the scraped data into a structured JSON Resume Schema. Advanced Data Mining Engine (GPT-4o-mini) – Performs: Skills Analysis (strengths, gaps, transferable skills) Experience Intelligence (career trajectory, leadership, project complexity) Cultural Fit Insights (work style, communication style, agility indicators) Career Trajectory Forecasting (promotion trends, growth velocity) Competitive Advantage Analysis (market positioning, salary expectations) Summarizer Node – Produces an abstractive and comprehensive AI summary of the candidate profile. Google Sheets Node – Saves the structured insights automatically into your recruitment intelligence sheet. File Writer Node (Optional) – Writes the JSON report locally for offline storage or integration. The result is a data-enriched candidate intelligence report far beyond what traditional resume parsing provides. 4. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Setup Steps Import the workflow JSON into your n8n workspace. Set credentials for: Decodo Credentials account OpenAI API (GPT-4o-mini) Google Sheets OAuth2 In the “Set the Input Fields” node, update: url → Resume link geo → Candidate region or country jobDescription → Target job description for matching Ensure the Google Sheet ID and tab name are correct in the “Append or update row in sheet” node. Click Execute Workflow to start. 5. How to customize this workflow You can adapt this workflow for different recruitment or analytics scenarios: Add Sentiment Analysis Add another LLM node to perform sentiment analysis on candidate recommendations or feedback notes. Enrich with Job Board Data Use additional Decodo nodes or APIs (Indeed, Glassdoor, etc.) to compare candidate profiles to live job postings. Add Predictive Fit Scoring Insert a Function Node to compute a numerical "fit score" by comparing skill vectors and job requirements. Automate Candidate Reporting Connect to Gmail, Slack, or Notion nodes to automatically send summaries or reports to hiring managers. 6. Summary The Advanced Resume Intelligence & Data Mining via Decodo + OpenAI GPT-4o-mini workflow transforms traditional candidate sourcing into AI-driven intelligence gathering. It integrates: Decodo** → To perform webscraping of data GPT-4o-mini** → to interpret, analyze, and summarize with context Google Sheets** → to store structured results for real-time analysis With this system, recruiters and HR analysts can move from data collection to decision intelligence, unlocking faster and smarter talent insights.

Quick Overview This workflow runs every Monday and reads pending rows from a Microsoft Excel workbook, generates certificate and contract PDFs in bulk with Carbone using templates stored in SharePoint, uploads the files to OneDrive, posts a summary card to Microsoft Teams, and marks the Excel rows as completed via Microsoft Graph. How it works Runs every Monday at 08:00 on a schedule. Fetches the Excel header row via Microsoft Graph and reads the pending rows from the configured Microsoft Excel worksheet. Splits the rows into certificate and contract batches and prepares the data arrays Carbone uses to render documents. If certificate rows exist, downloads the certificate template from Microsoft SharePoint, generates a zipped batch of PDFs with Carbone, extracts the files, and uploads them to Microsoft OneDrive. If contract rows exist, downloads the contract template from Microsoft SharePoint, generates a zipped batch of PDFs with Carbone, extracts the files, and uploads them to Microsoft OneDrive. Posts an Adaptive Card summary (batch ID and document counts) to the configured Microsoft Teams channel. Uses Microsoft Graph $batch requests to update each processed Excel row with Status = Completed and sets ProcessedAt to the current timestamp. Setup Add Microsoft 365 credentials for Microsoft Excel (OAuth2), Microsoft SharePoint, Microsoft OneDrive, and Microsoft Teams, plus a Carbone API credential. In the Config step, replace all placeholder IDs for the Excel workbook/worksheet, SharePoint template file IDs, OneDrive folder IDs, and the target Teams team and channel. Ensure your Excel sheet includes header columns named Status and ProcessedAt (and the fields used in the workflow such as Name, Email, Company, Role, DocumentType, CourseTitle, CompletionDate, and Score). Update the organization/signatory values (issuedBy and issuerName) and make sure your Carbone templates reference the workflow’s certificate and contract fields.

This workflow automates the daily backup of all your n8n workflows to a designated folder in Nextcloud. It ensures that you always have the last 7 days of backups available while automatically deleting older ones to save space. 🔧 Features Scheduled Trigger: Runs automatically once per day (can be executed manually as well). Directory Management: Creates the /N8N-Backup directory in Nextcloud if it doesn't already exist. Backup Collection: Retrieves all workflows from the n8n instance. JSON Conversion: Converts each workflow into a JSON file. Upload to Nextcloud: Saves each backup file into the specified backup directory. Retention Control: Keeps only the latest 7 backups and deletes the rest from Nextcloud. 📌 Notes Make sure to manually create the /N8N-Backup directory in your Nextcloud account before using this flow. Update the Backup Path node if you wish to change the upload directory. Ideal for teams using n8n with self-hosted instances and requiring offsite backup via Nextcloud. 🔒 Requirements n8n instance with access to the Nextcloud node. Valid credentials for your Nextcloud account with API access. Update: 08/11/2025 “Backup Flows to Nextcloud” – Import format fixed Summary: The workflow now exports one clean JSON object per workflow (no arrays, no backup/meta fields), so files can be imported 1:1 via the n8n UI. What changed: Switched from “Convert to File” to a Set node that builds the JSON in binary data. Enabled filters.include = "all" on Get many workflows to include nodes, connections, settings, pinData, and tags. Sanitized filenames and removed IDs/metadata that can break UI imports. Fixed Nextcloud path and binary property mapping (data). Verification: Generated multiple backups and imported each via UI (“Import from file”) without errors. Each file begins with { (single object) and loads with full workflow structure. Notes: Keep “Binary Property” set to data in the Nextcloud node. Filenames are sanitized to avoid special-character issues.