This article provides a complete, practical walkthrough of the Telegram Googlecalendar Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Build a Smart AI Phone Assistant Using n8n and Retell AI: Automate Call Handling, Booking, and RAG-Based Support
   
   Meta Description:  
   Discover how to create a fully automated AI phone agent using n8n and Retell AI. Learn how to set up call summarization, appointment scheduling, and smart information retrieval using GPT-4, Google Calendar, Telegram, and Qdrant vector databases.
   
   Keywords:
   n8n, AI phone agent, Retell AI, GPT-4o, OpenAI, Qdrant, RAG system, Google Calendar automation, Telegram bot, AI customer service, vector store, call automation, Langchain, Google Drive, Twilio integration
   
   Article:
   
   Create a Fully Functional AI Phone Agent Using n8n and Retell AI
   
   In a world where AI continues to reshape customer engagement and service automation, having a phone-based AI assistant makes incredible business sense. From booking appointments to providing accurate product information, AI phone agents allow companies to streamline support tasks without sacrificing quality. With n8n as a powerful low-code automation tool, building such an intelligent phone agent has never been easier.
   
   This article explores a real-world n8n workflow integrating Retell AI, OpenAI’s GPT-4o, Qdrant, Google Calendar, and Telegram to create an autonomous AI phone assistant capable of handling voice interactions intelligently.
   
   🧠 What the Workflow Does:
   This automated flow builds a voice-enabled AI agent with two primary capabilities:
   
   1. 📅 Appointment Booking
   It extracts relevant date/time info from calls and books events directly into Google Calendar.
   
   2. 🔍 Retrieval-Augmented Q&A (RAG)
   When a customer asks questions about products or services, the agent retrieves relevant documents from Qdrant (a vector database), interprets user queries using GPT-4, and delivers well-informed answers.
   
   Workflow Overview:
   
   Step 1 – Prepare the Knowledge Base for RAG  
   Using Google Drive and Qdrant, documents are indexed and embedded using OpenAI embeddings. Files are downloaded, converted into vectors, and stored for quick semantic search capabilities through Retrieval-Augmented Generation (RAG).
   
   Step 2 – Configure Retell AI Agent  
   Create an agent on Retell AI with a system prompt customized for voice-based interaction. Set the webhook URLs (provided by n8n) for handling intelligent RAG responses and appointment availability.
   
   Step 3 – Handle Incoming Calls  
   - When a user calls the AI phone number (provisioned via Twilio through Retell AI), the transcript and metadata are sent to a webhook (n8n_call).
   - A filter node monitors Retell AI’s end-of-call events (such as call_ended or call_analyzed).
   
   Step 4 – Analyze Call Transcript with GPT-4  
   A structured LLM chain receives the transcript and uses GPT-4o Mini to summarize key points, extract details like name, email, and call objective. The inference is parsed into a structured object using Langchain's Output Parser.
   
   Step 5 – Notifications and Scheduling  
   - Telegram Node: The call summary and key fields are sent via a Telegram message to a pre-defined chat for monitoring or alerts.
   - If an appointment is part of the call, the system converts the provided date using GPT and schedules the event in Google Calendar using the appropriate credentials.
   
   Step 6 – Enable Real-Time Question Answering (RAG) via Chat  
   A separate webhook (n8n_rag_function) enables real-time information retrieval on demand. When a query is detected, it:
   - Converts the query into vector embeddings using OpenAI.
   - Fetches relevant knowledge chunks from Qdrant using vector similarity.
   - Feeds the content into GPT-4 for response generation using a defined system prompt (e.g., product support, policy help).
   
   This format ensures highly accurate, context-aware responses while keeping the response flow under control.
   
   🛠️ Tech Stack and Third-Party APIs Used:
   
   1. Retell AI – For voice agent, voice-to-text, and webhook triggers  
   2. OpenAI GPT-4o – For transcript summarization, RAG response generation, and formatting dates  
   3. Qdrant – A vector database to store and retrieve semantic document embeddings  
   4. Telegram API – For sending live call summaries to enterprise chat  
   5. Google Calendar API – To book appointments automatically based on phone call context  
   6. Google Drive API – To retrieve and process business documents into vectors  
   7. Twilio (via Retell AI) – To provision phone numbers and manage call routing  
   8. Langchain – To fine-tune GPT behavior, enable structured outputs, vector search, and tools  
   
   🎯 Business Use Cases
   
   - Customer support hotlines for e-commerce or services
   - Real estate or consultancy agencies handling bookings
   - Smart IVR systems with knowledge search
   - Retail product assistants using RAG on catalogs
   - Support summary logging with auto-notifications
   
   🔐 Privacy Note:  
   Ensure privacy compliance when handling call recordings and personal data. Always inform customers that the call is being monitored and analyzed by AI.
   
   Conclusion:
   
   With a minimal setup and the use of free credits from Retell AI and OpenAI, you can create a powerful AI phone agent that not only speaks to customers but actually understands, records, acts, and responds intelligently. Combined with n8n’s flexible automation capabilities, this system is perfect for modern businesses seeking scalable support solutions.
   
   So go ahead — transform how your business handles phone inquiries. Let AI take the call.
   
   —  
   Need help setting this up? Our AI assistant can guide you through every step.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.