Master n8n AI Agents: Build & Sell AI Agents and Automations

In this lecture, we build an email classifier workflow using n8n Workflow. The system automatically analyzes incoming emails, categorizes them, and generates appropriate responses. The workflow applies labels like course support, inbound leads, and paid collaboration, enabling you to prioritize emails efficiently. It uses Gmail triggers, text classifiers, and personalized responses to streamline your email management, ensuring prompt replies within minutes. The lecture includes a practical example and provides a ready-to-use workflow that can be customized to fit individual business needs.

In this lecture, we demonstrate how to create a workflow using n8n to discover the technology stacks of various companies, serving as an alternative to Clay. The process involves sourcing company domains from a Google Sheet, using BuiltWith to identify the tech stack, and scraping this data with Jina AI. This method significantly cuts down costs compared to Clay. The workflow includes nodes for triggers, Google Sheets, HTTP requests, loops, and basic LLM models for organizing the gathered data. The complete step-by-step setup helps automate tech stack discovery efficiently and affordably.

This tutorial explains how to identify and convert anonymous visitors on your website into leads using an inbound-outbound system. The process is facilitated by n8n workflows and the AI Agent to personalize email outreach. First, it guides connecting RB2B with your website, then linking Slack with n8n, and finally enriching collected data through DropContact or similar services. The tutorial emphasizes the verification of email addresses to ensure data accuracy before adding leads to outbound campaigns.

In this lecture, we demonstrate how to build an ultimate company research workflow using n8n and various AI tools. The process involves scraping reviews from Trustpilot, analyzing web data using Jina AI, and extracting company information from LinkedIn using Nubela ProxyCurl. Data is summarized through an LLM chain for sentiment analysis and then compiled into a Google Sheet. The workflow aims to provide a comprehensive view of a company's online presence, customer sentiments, and business profile, facilitating an in-depth company analysis.

In this lecture, Lead Gen Man aka Manthan demonstrates how to automate LinkedIn connection requests with hyper-personalized messages using n8n and AI agents. The process starts by sourcing prospect data from Google Sheets. Browserflow is then employed to check if the prospect is already connected on LinkedIn. For new connections, the workflow enriches the prospect's data from LinkedIn and uses AI to craft a personalized message. Finally, the workflow sends the connection request through Browserflow and updates the Google Sheet to reflect the new request status.

This lecture introduces an automated workflow for scraping LinkedIn job postings using n8n and an AI Agent. Users input a LinkedIn job search URL, and the system extracts job details while enriching contact information. It identifies unique specific individuals, collects emails, generates personalized icebreakers with OpenAI, and stores all data in Google Sheets. The workflow can filter and clean company names, avoid duplicate job posts, and verify email addresses. Ideal for staffing agencies or job seekers, the script emphasizes efficiency and minimizes manual applications.

This tutorial demonstrates the use of an AI agent integrated with n8n to create hyper-personalized email copies or LinkedIn messages for different niches and use cases, such as webinars, product promotions, or podcast invites. It showcases how to source data from a Google Sheet and employ AI to generate personalized content, ensuring professionalism by cleaning up company names. The process includes defining custom prompts to tailor messages for specific audiences, illustrating flexibility for various industries. Additionally, it highlights testing and refining the workflow for optimized results.

This session explains how to automate inbound lead qualification using n8n and an AI agent. It starts with a form submission on a website for collecting the lead's name, email, website, and LinkedIn profile. The workflow then scrapes data from the person's LinkedIn profile, the company's LinkedIn page, and their website for enrichment purposes. The enriched data is sent to an AI agent, which evaluates if the lead is a good fit, scoring them as qualified or unqualified. This process eliminates the need to manually assess leads, saving time and improving efficiency.

In this lecture, Manthan introduces an ultimate AI-powered lead generation ai agent built using n8n. The agent automates the entire lead generation process by first finding profiles based on keywords and location. It enriches these leads with personal and company data, verifies emails, and categorizes them based on the company's fit. Qualified leads are then added to email and LinkedIn campaigns. The process also includes generating personalized icebreakers to avoid spam. Manthan demonstrates the workflow step-by-step and explains each module used in n8n, ensuring data collection, enrichment, and automated campaign integration.

This lecture explains how to replace an entire SDR team with an AI SDR agent using n8n. The workflow involves three sub-workflows: URL scraper, text scraper, and email scraper. It automates the process of finding companies, extracting valid email addresses, and scraping essential web and social media data. The AI agent uses tools like OpenAI LLM and various APIs, ensuring all tasks are performed at minimal cost. The final data is validated, formatted, and ready for cold email campaigns. This solution is scalable, efficient, and cost-effective, eliminating the need for expensive enrichment tools.

In this lecture, Lead Gen Man or Man(than) guides users through building a Google Maps lead generation AI agent using n8n. The workflow involves scrapping data from Google Maps, enriching it with additional information, and storing it in Google Sheets. Detailed steps include setting up API requests, using OpenAI and Perplexity AI for data extraction, and ensuring proper data management with unique IDs. The final output includes leads with detailed business information, including email addresses and personalized background details.

In this lecture, we build a company’s internal people finder using n8n and AI Agents to identify and contact C-level executives and other decision-makers. The example demonstrates a step-by-step workflow, starting with a manual trigger or Webhook, followed by data extraction from Google Sheets, domain identification using JavaScript code, and the use of Apolloio and Prospeo for data verification and email address extraction. The gathered data is then integrated into cold email campaigns and LinkedIn automation. By following this process, users can efficiently reduce costs and avoid heavy fees associated with tools like Clay. [Paid Apollo API/Plan Required]

This lecture demonstrates how to build an Apollo scraper using n8n and an AI agent. The scraper retrieves prospect data from Apollo.io, enriches it with validated email addresses, and adds it to a cold email campaign. The AI agent converts natural language queries into Apollo URLs, which are then scraped using Apify actors. Verified email addresses are added to a campaign in Smart Lead. The process is detailed step-by-step, from setting up the OpenAI model and n8n workflow to using API calls and validating emails.

In this lecture, Manthan walks through creating a sales call preparation AI agent using n8n. The agent automates researching and prospecting details about individuals who book meetings. Using just the name and email address, the agent gathers comprehensive information including company details, LinkedIn profile, and recent news, and sends a detailed report to your Gmail. The workflow consists of three sub-workflows: analyzing the company's website, researching LinkedIn, and fetching news with Perplexity. Manthan explains the setup and integration of various tools and APIs like OpenAI, Jina AI, Rapid API, and more, to build this efficient automation.

Learn how to import files and workflow with prompts, nodes, and how to configure your credentials

This session demonstrates a workflow in n8n for conducting comprehensive company research using only an email address. By extracting the domain from the email, the AI Agent gathers detailed information such as company overviews, business profiles, SWOT analysis, and competitor analysis from sources like Crunchbase and industry reports. The gathered data is then summarized and added back to the original Google Sheet with updated status. The process can handle multiple entries, running each through the same research loop with the help of open router integration for Perplexity AI.

The session explains how to use an AI agent within n8n to automate the candidate screening process. It covers setting up triggers, downloading CV attachments from Gmail, analyzing PDF content, and uploading data to Google Sheets. The AI agent classifies emails, extracts relevant information, and scores candidates based on experience and fit for the job role. The example demonstrates the efficiency of this automated workflow in handling large volumes of job applications quickly and accurately.

Open AI has introduced a GPT-4 search preview that can automate web searches through an API. This video demonstrates an n8n workflow using the AI Agent to analyze domains and extract information such as customer type, free trials, case studies, blogs, and integrations. The data is then cleaned and mapped into a Google Sheet. The presenter highlights this method as more efficient than tools like Jina AI and Deep Seek.

This session explains how to leverage n8n and AI agents to filter specific data points such as headcount time series and decision makers from a company's profile. It details the process of using URLs and company IDs to retrieve information about decision makers like CEOs or CTOs and their LinkedIn profiles. Additionally, the script demonstrates creating hyper-personalized LinkedIn messages by scraping LinkedIn posts and integrating this data using the Google Gemini chat model and OpenAI. The lecture is taking example automating personalized messaging for events such as AI webinars for reference, feel free to customize it according to your own business needs and preference.

In this lecture, Lead Gen Man provides valuable tips to streamline workflows with 8 n8n tips and tricks. You will love these hacks to save hours and keep your sanity intact:)

In this lecture, you'll learn how to automate company enrichment inside HubSpot using Coresignal's native n8n node. Every time a new company is added to your CRM, from a website form, meeting booking, or manual entry — this workflow automatically pulls 500+ data points (industry, headcount, location, revenue, founding year, and more) from Coresignal and writes them straight back into the HubSpot record.

I excels at creating content on LinkedIn, achieving over 5 million impressions monthly with 65,000 followers. They introduce a strategy using n8n and AI agents to scrape top-performing LinkedIn posts from competitors, allowing users to repurpose proven content. The process includes setting up automation with Google Sheets or Airtable, using scraping tools like Apify, and filtering top posts based on engagement metrics. The workflow aims to help users achieve higher virality and engagement without starting from scratch.

This lecture outlines a simple automation process to identify top-performing Instagram reels from a list of creators using Airtable and Apify. The goal is to help users emulate successful content by scraping data and storing it in Airtable. The script guides through setting up a schedule trigger, retrieving creator data, using APify for scraping, and storing the results. Key steps include creating tables in Airtable, configuring API connections, sorting data by performance metrics, and finally, adding the data to Airtable. The detailed instructions make it easy to replicate the workflow for analyzing competitors' Instagram posts.

The session provides a step-by-step guide on building an automation to find the top tweets with a specific keyword (like 'AI') from Twitter (now called X). The process is fully customizable to suit different time frames and search criteria.

This class demonstrates a workflow leveraging n8n and AI Agents to find and qualify leads from Reddit (Goldmine platform for Leads). The example involves setting up an AI to scrape posts from specific subreddits and identify potential leads based on a set of criteria. The workflow filters posts, assesses them for lead potential, and categorizes them by priority. It shows how to generate an access token, scrape and split posts, loop through them, and use OpenAI to determine lead viability. The results are then populated into a Google Sheet for further action.

Here’s a small breakdown of what it can ACTUALLY do:

- Detects any product with OpenAI image analyzers and writes a perfect style prompt.

- Auto-generates studio-grade images in seconds (no photographer needed).

- Delivers ready-to-post shots for Shopify, Amazon, IG & ads.

- Powered by n8n and ChatGPT Image Generation

- Turn dull catalog pics into high-converting visual assets on autopilot.

In this lecture, Lead Gen Man aka Manthan demonstrates how to quickly create Retrieval-Augmented Generation (RAG) agents using Postgres SQL and Supabase Vector Store in n8n. The tutorial covers connecting AI agents to databases, storing chat histories, and leveraging external data sources such as PDF, DOCX, and CSV files for enhanced AI functionality. Viewers learn to set up accounts, manage credentials, and use embeddings for better data interpretation. The video also explains how to integrate these tools into existing n8n workflows to optimize AI agent performance.

The lecture emphasizes the importance of building on-premise specialized AI infrastructure for enterprise-level clients to ensure data privacy and compliance. It suggests avoiding reliance on external services like OpenAI and Anthropic servers due to potential data breaches and compliance risks. The solution involves using Milvus, an advanced enterprise-grade vector database, and Attu for visual management. Additionally, Ollama is recommended for running large language models locally, eliminating the need for external API keys. The process includes steps to set up Docker, NodeJS, and necessary libraries, followed by practical commands to install and configure Milvus and Attu. The script provides a detailed walkthrough of connecting documents to Milvus, using n8n for workflow automation, and deploying the system for secure, local data management.

Learn how to create a powerful multimodal Retrieval-Augmented Generation (RAG) system with Milvus and n8n. This system processes various input types such as text, image, voice, and PDFs, converting them into embeddings to search in a Milvus database. With the aid of LLMs, it provides context-aware answers and maintains conversation memory. The video covers detailed steps for setting up Milvus and n8n using Docker, showcasing the system's performance in different scenarios including text, voice, image, and document inputs. Discover how Milvus, a high-performance, cloud-native vector database, can handle millions of vector searches for scalable solutions.

This class explains what AI agents are and how they differ from AI automation. Using the example of n8n’s AI agent, it describes the architecture that enables AI agents to plan, remember, and solve complex issues. The key difference highlighted is that AI agents possess memory and can use various tools, unlike the linear execution in AI automation. A real-world example comparing AI voice agents with traditional IVR calls illustrates this difference. The session emphasizes that n8n allows building AI agents without coding, using simple drag-and-drop connections.

Manthan, the lead gen man, demonstrates how to embed n8n chat bots into a website or client funnel, highlighting the ease and flexibility of customization. He shares steps for integrating various tools like Google Calendar, Gmail, and Google Sheets to enhance chatbot functionality. The process covers how to make the chatbot publicly available, using embedded chat mode, and customizing the chatbot's appearance and functionalities. Manthan also shows how to replace default settings using ChatGPT or Perplexity to suit specific brand requirements, ensuring the chatbot fits seamlessly into any site's design and operational needs.

In this video, I’ll show you how to run the GPT-OSS AI model locally on your computer with Ollama and connect it to n8n so you can build your own AI agents and automations for free. I’ll walk you through installing Ollama, setting up your model, and integrating it into n8n to create powerful workflows without paying for API credits.

The session discusses how to avoid paying a monthly subscription fee for n8n by self-hosting the tool on your local machine. It explains that paid plans usually offer limited operations and active workflows, while self-hosting allows unlimited usage at no additional cost. Instructions are provided for setting up Nodejs, installing the automation tool, and running it locally. The script also mentions upcoming content on running language models locally to avoid API costs.

In this lecture, you will learn how to run large language models (LLMs) locally using the Ollama platform, avoiding the need for paid API calls. The process involves downloading and installing Ollama, setting it up on different operating systems, and using it to manage open-source LLMs such as Llama3, DeepSeek, and Mistral. The instructor walks through the steps of downloading, installing, and running these models on a local network and shows how to interact with the models in a terminal, similar to using ChatGPT. The lecture highlights the benefits of using open-source models to save costs on API calls and concludes with instructions on managing instances and utilizing past conversation memory with locally run language models.

This video explains how to self-host n8n (for free for the first month) for executing unlimited workflows and unlimited operations without paying a single penny. It covers the cost advantages compared to using hosted services like make.com or Zapier. The video shows deploying n8n using Railway for a minimal monthly fee, highlighting the ease and benefits, including data security. Additionally, different self-hosting options and their technicalities are discussed, with a focus on non-technical setups. In the next lecture, the video will cover what MCP (Model Context Protocols) is and how to use it within n8n.

The lecture introduces the Model Context Protocol (MCP) and demonstrates how to deploy it within n8n from scratch. MCP is a standardization protocol that simplifies connecting AI agents to various web applications like Slack, Google Drive, and Airbnb. The video walks through the process of installing the MCP community node in n8n, setting up the necessary credentials, and using MCP to seamlessly integrate AI agents with different external applications. The presenter provides examples using applications such as Firecrawl and Airbnb MCP servers to automate tasks like web scraping. Viewers are guided through each step, including configuring command arguments and API keys, to ensure successful integration of AI agents with MCP in n8n workflows.

This tutorial guides users on enhancing their Claude desktop application with the Model Context Protocol (MCP), enabling seamless integration with various external tools like Brave Search, Airbnb, and Firecrawl, etc. It provides step-by-step instructions for downloading necessary applications and setting up MCP servers in a development environment like VS Code or Visual Studio Code. The video demonstrates connecting to Brave Search through API keys, managing configurations, and ensuring proper setup by troubleshooting common issues. Additional examples include installing MCP servers for Airbnb and Firecrawl, showcasing their applications in retrieving web data and listings. The guide emphasizes the ease of combining multiple MCP servers to boost the AI agent's functionality and efficiency within the claude application.

In this quick lecture, learn how to update your self-hosted n8n account to the latest version. The video demonstrates updating from version x to y. Follow steps including logging into your hosting service, selecting your project, and redeploying the service. Post update, the lecture verifies the installation of new nodes like MCP server trigger and MCP client trigger. For any questions, students are encouraged to reach out.

The session provides a step-by-step tutorial on creating and personalizing AI humans using Tavus and n8n workflows. Tavus is described as an OS layer for human-AI interaction, allowing the creation of AI humans capable of seeing, hearing, interacting, and taking real-life actions. The script includes a demo interaction with an AI named Charlie, demonstrating its capabilities. Additionally, it covers how to create personalized AI personas and replicas with specific roles, memories, and guardrails, and how to integrate these with n8n for automated, hyper-personalized outreach via cold emails or other communication channels. The tutorial ends with instructions on setting up community nodes and creating video messages personalized with customer data.

Running Local LLMs with LM Studio on n8n for Enhanced Data Security

This video demonstrates how to run local large language models (LLMs) like DeepSeek and Qwen3 for free within n8n workflows to improve data security. The presenter introduces LM Studio, a user-friendly platform for hosting LLMs locally without needing coding skills. Viewers are guided through downloading and setting up LM Studio, exploring LLMs, interacting with the models, and connecting LM Studio with n8n workflows. The tutorial also covers configuring and fine-tuning LLMs for specific use cases and testing the setup to ensure it runs smoothly without incurring costs or compromising privacy.

This lecture explains how to build a free email finder tool using n8n and Lovable. By leveraging n8n logic and writing minimal code, you can replicate the functionality of paid email data providers like Findymail or Lead Magic, etc. The workflow involves inputting a person's name and company domain to generate possible email permutations, which are then verified through an email verification service. The tutorial covers step-by-step instructions from creating the n8n workflow to deploying the Lovable app. It highlights how to use JavaScript for permutations and API calls for email verification, emphasizing that this solution negates the need for expensive email data services.

The tutorial demonstrates creating a spam checker tool using n8n without coding using Cursor or Lovable. The process involves setting up a WebBook to receive data from an AI agent, processing the data with JavaScript, and using tools like Loveable to build and visualize the front end. The spam checker analyzes spam words in subject lines and email bodies, offers suggestions for improvement, and displays results to users. The presenter emphasizes the role of prompt engineering in refining the AI agent's output.

With Claude and Cursor Coding Agents, creating custom AI agents is now as easy as sending a prompt with MCP generated the full n8n workflow in seconds!

Elevate your AI Agent with n8n and OpenAI!

- Use AI agent in n8n and select OpenAI model

- Enter OpenAI API credentials

- Choose from cutting-edge models

Supercharge your AI solutions!

In this lecture, Manthan explains how to connect Google Sheets with an n8n account, both in the Cloud version (easy setup) and the self-hosted version (trickier process). For the Cloud version, users simply need to create new credentials and sign in with their Google account. For the self-hosted version, a detailed process involves using Google Cloud to authorize the URL, creating OAuth client credentials, enabling the Google Sheets API, and finally signing in with Google. After these steps, Google Sheets will be successfully connected to the n8n account.

Note: This video is for self-hosted n8n accounts only!

Note: This video is for self-hosted n8n accounts only!

In this tutorial, you'll learn how to connect Telegram with n8n, create a Telegram bot, set up API credentials, and configure authentication for secure automation. By integrating Telegram with n8n, you can automate alerts, respond to messages instantly.

In this tutorial, Manthan demonstrates how to automate the process of inputting existing leads into email campaign tools like Smartlead, Instantly and Saleshandy without manual intervention. Manthan explains API integration step-by-step, covering how to source lead lists from tools like Google Sheets or Airtable, set up API keys, create campaigns, and populate lead data using HTTP requests. The video highlights the importance of loops for handling large lead lists and customizing payload data.

In this lecture, the presenter explains how to set up a LinkedIn outreach automation campaign using tools like LGM (La Growth Machine) and HeyReach. The process begins by sourcing a lead list from Google Sheets, and integrating this data into LinkedIn outreach campaigns via LGM using HTTP requests. Key steps include creating a new audience in LGM, setting up a loop to manage API limits, and populating audience details like first name, last name, company name, title, and LinkedIn URL.

In this video, learn why data privacy is crucial when using AI agents for processing sensitive information. Discover Chutes AI, a decentralized AI platform offering 60 open-source models at significantly lower costs compared to OpenAI. The video explains how to set up Chutes' TEE (Tested Execution Environment) in n8n, ensuring end-to-end encryption of your data. With Chutes, access models like DeepSeek-R1 at a fraction of the cost and enhance client trust without compromising data security.

The lecture introduces Retell AI, a powerful AI-driven tool designed to handle conversations and objections in real-time using popular language models like GPT-4 or Claude. Retell AI is easy to use, integrates with various business tools, and can conduct tasks from inbound call handling to outbound sales and appointment scheduling. It supports 18 languages and operates at lightning-fast speeds.

Learn how to create an automated AI voice agent that instantly calls leads after form submission using n8n. This powerful workflow captures form data, triggers Retell AI, and makes personalized calls within seconds. You'll master HTTP POST requests, dynamic variable mapping, and custom field integration. Perfect for businesses wanting to boost conversion rates with immediate callbacks that turn hot leads into booked appointments.

Transform your sales process by building an intelligent AI voice agent that handles promotions, upsells, and outbound sales calls. Using a real dental clinic example, you'll configure Retell AI with n8n, integrate Google Sheets for customer data, and customize voice accents and responses. Watch live demonstrations of the AI agent making successful upsell calls that generate real revenue on autopilot.

Slash no-show rates by 80% with an automated AI voice reminder system. This lecture shows you how to build an intelligent agent that calls clients one hour before appointments, confirms attendance, and handles rescheduling automatically. You'll integrate Google Calendar, capture data in sheets, and configure smart wait functions. The complete system updates your CRM in real-time, ensuring perfect appointment management.

This tutorial explains how to integrate the Retell AI API into the n8n workflow.