Fakhar Khan
Automation expert specialized in n8n. I design and build AI-powered workflows that streamline operations, automate lead generation, and enhance customer engagement. Passionate about low-code automation and integrating tools like OpenAI, WhatsApp, Slack, and CRMs. Organizer of n8n events in Pakistan, helping businesses scale with smart, efficient automation systems.
Templates by Fakhar Khan
Restaurant reservation management with OpenAI GPT and Google Sheets
How it works Receives chat messages from customers requesting table reservations. Uses an AI Agent with OpenAI Chat Model to understand and process requests. Checks table information, availability, and existing reservations from Google Sheets. Calculates guest counts and reservation timing using the Calculator node. Updates table availability and reservation records in real-time. Handles reservation changes, including updates and cancellations. Set up steps Add credentials for OpenAI (Chat Model) and Google Sheets. In the AI Agent node, link: Chat Model → OpenAI Chat Model node. Memory → Simple Memory node. Tools → Calculator and Google Sheets nodes for reservation data handling. Configure Google Sheets nodes: Get Table Information (read sheet) Get Table Availability (read sheet) Get Table Reservations (read sheet) Update Table Availability (update sheet) Update Reservations (append sheet) Cancel Reservations (delete sheet) Ensure your sheets have consistent column names for table IDs, dates, times, and guest counts. Test by sending a reservation request through the chat trigger and verify updates in the Google Sheets.
By Fakhar KhanMulti-agent healthcare assistant with WhatsApp, GPT-4 & Google Sheets
Multi-Agent AI Healthcare Assistant Demo ⚠️ EDUCATIONAL DEMONSTRATION ONLY - NOT FOR PRODUCTION MEDICAL USE ⚠️ A comprehensive demonstration of n8n's advanced multi-agent AI orchestration capabilities, showcasing how to build sophisticated conversational AI systems with specialized agent coordination. 🎯 What This Demo Shows Advanced Multi-Agent Architecture: Main Orchestrator Agent - Traffic controller and decision maker Patient Registration Agent - Specialized data collection and validation Appointment Scheduler Agent - Complex multi-step booking workflows Medical Report Analyzer - Document processing and analysis Prescription Medicine Analyzer - Medicine verification and safety checks Technical Learning Objectives: Multi-agent coordination patterns Conditional agent routing and tool selection Memory management across conversations Multi-modal input processing (text, audio, images, documents) Complex state management in AI workflows External system integration (Google Sheets, WhatsApp, OpenAI) 🏗️ Architecture Highlights Multi-Modal Processing Pipeline: Text Messages → Direct agent processing Audio Messages → Transcription → Text processing → Audio response Images → Vision analysis → Context integration Documents → PDF extraction → Content analysis Agent Specialization: Each agent has focused responsibilities and constraints Intelligent document classification and routing Context-aware tool selection Error handling and recovery mechanisms Memory & State Management: Session-based conversation persistence Context sharing between specialized agents Multi-step workflow state tracking 🔧 Technical Implementation Key n8n Features Demonstrated: @n8n/n8n-nodes-langchain.agent - Main orchestrator @n8n/n8n-nodes-langchain.agentTool - Specialized sub-agents @n8n/n8n-nodes-langchain.memoryPostgresChat - Conversation memory n8n-nodes-base.googleSheetsTool - External data integration Complex conditional logic and routing Integration Patterns: WhatsApp Business API integration OpenAI GPT-4 model orchestration Google Sheets as data backend PostgreSQL for conversation memory Multi-step document processing 📚 Learning Value For n8n Developers: Enterprise-grade workflow architecture patterns AI agent orchestration best practices Complex conditional logic implementation Memory management in conversational AI Multi-modal data processing techniques Error handling and recovery strategies For AI Engineers: Agent specialization and coordination Tool calling and function integration Context management across conversations Multi-step workflow design Production workflow considerations ⚙️ Setup Requirements Required Credentials: OpenAI API Key (GPT-4 access recommended) WhatsApp Business API credentials Google Sheets OAuth2 API PostgreSQL database connection External Dependencies: Google Sheets database (template structure provided) WhatsApp Business Account PostgreSQL database for conversation memory 🚨 Important Disclaimers Educational Use Only: This is a DEMONSTRATION of n8n capabilities NOT suitable for actual medical use NOT HIPAA compliant Use only with fictional/test data Production Considerations: Requires proper security implementation Needs compliance review for medical use Consider HIPAA-compliant alternatives for healthcare Implement proper data encryption and access controls 🎓 Educational Applications Perfect for Learning: Advanced n8n workflow patterns Multi-agent AI system design Complex automation architecture Integration pattern best practices Conversational AI development Workshop & Training Use: AI automation workshops n8n advanced training sessions Multi-agent system demonstrations Integration pattern tutorials 🔄 Workflow Components Main Flow: WhatsApp message reception and media processing Input classification and routing Main agent orchestration and tool selection Specialized agent execution Response formatting and delivery Sub-Agents: Registration Tool - Patient data collection Scheduler Tool - Appointment booking logic Report Analyzer - Medical document analysis Medicine Analyzer - Prescription verification 💡 Customization Ideas Extend the Demo: Add more specialized agents Implement different communication channels Integrate with other healthcare APIs Add more sophisticated document processing Implement advanced analytics and reporting Adapt for Other Industries: Customer service automation Educational assistance systems E-commerce support workflows Technical support orchestration --- 🎯 Perfect for: Learning advanced n8n patterns, AI system architecture, multi-agent coordination ⏱️ Setup Time: 30-45 minutes (with credentials) 📈 Skill Level: Intermediate to Advanced 🏷️ Tags: AI Agents, Multi-Agent Systems, Healthcare Demo, Educational, Advanced Workflows
By Fakhar KhanSearch and compare flights with DeepSeek AI and Google Flights API
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works Takes departure city, destination, and travel dates from the user. Searches multiple airlines for flight options and compares price, duration, and stops. Suggests flexible travel dates for better deals. Tracks selected flights and sends real-time price alerts. Provides 24/7 AI-powered travel recommendations. Set up steps Add credentials for your chosen Chat Model (DeepSeek in this case) and SerpAPI (Google Flights). In the AI Agent node, link: Chat Model → DeepSeek Chat Model node. Memory → Simple Memory node (for conversation context). Tool → Google_flights search in SerpApi node. In the SerpApi node, set engine=google_flights and map input fields for departure, destination, and travel dates. Test the workflow by providing a sample itinerary request in the Chat node’s input. Review AI responses to ensure it searches, compares, and returns relevant flight options.
By Fakhar Khan