---
type: source
title: "Get Qualified Leads While you Sleep with AI"
description: "Instead of building a website lead-generation agent from scratch, use a purpose-built no-code platform like Chatling to visually assemble a chatbot that qualifies leads, answers questions from a RAG knowledge base, and collects contact info automatically."
youtube_id: 1I0PvfHjaRE
url: https://www.youtube.com/watch?v=1I0PvfHjaRE
slug: get-qualified-leads-while-you-sleep-with-ai
published: 2024-10-11
duration: "0:18:38"
recency_rank: 154
raw: "../raw/get-qualified-leads-while-you-sleep-with-ai.md"
tags: [no-code, lead-generation, chatbots, rag]
created: 2026-07-21
updated: 2026-07-21
---

# Get Qualified Leads While you Sleep with AI

Cole argues that a lead-generation agent that lives on your website and runs the front end of your business, qualifying leads, answering questions, suggesting products, and capturing contact info, is one of the few genuinely valuable, business-ready uses of AI. He notes that most lead-gen platforms are weak enough that you may as well build the agent yourself in n8n or LangChain, but a handful of purpose-built platforms are worth checking first. He demos one of them, Chatling, to show how much non-trivial machinery (looping questions, multi-select buttons, branching, contact capture) such a platform handles for you.

The bulk of the video is a walkthrough of Chatling's node-based workflow builder, which resembles Voiceflow or Vector Shift: a conversation is a graph running from a start node through blocks that send messages, capture user text into custom variables, get AI responses, present buttons, and loop. Captured variables (selected service, first/second answer) feed forward into later prompts so the agent has conversation context and can qualify the lead across several questions. Cole builds a demo AI-consulting agent, then shows the RAG knowledge base tab, which can ingest a crawled website, a sitemap (great for e-commerce product catalogs), a custom URL list, uploaded documents, raw text, or FAQ pairs.

He then covers appearance/branding customization, a CRM-like conversations view that ties captured contacts to their chats, and embedding the widget on any site via a script tag (floating, inline, or full-screen), demoing it in an online HTML editor. A live end-to-end run shows the agent greeting, asking qualifying questions, answering a product question from the FAQ RAG (GPT-4o mini as the model), and collecting name and email. His closing point: platforms like this preserve full customizability (HTTP request blocks let you call any external API or custom agent), and since a public-facing site chatbot handles no private data, there is no reason to insist on a self-hosted build.

## Concepts covered

- [AI Agent Business Niches](../concepts/ai-agent-business-niches.md)
- [Learn by Building](../concepts/learn-by-building.md)
- [Visual Workflow Builder](../concepts/visual-workflow-builder.md)
- [Context Engineering](../concepts/context-engineering.md)
- [Chat Interfaces](../concepts/chat-interfaces.md)
- [Retrieval-Augmented Generation (RAG)](../concepts/rag.md)
- [Knowledge Bases](../concepts/knowledge-bases.md)
- [Embeddable Agent Widget](../concepts/embeddable-agent-widget.md)
- [HTTP Request Extensibility](../concepts/http-request-extensibility.md)

## Entities

- [Cole Medin](../entities/people/cole-medin.md)
- [n8n](../entities/tools/n8n.md)
- [LangChain](../entities/tools/langchain.md)
- [Voiceflow](../entities/tools/voiceflow.md)
- [Vector Shift](../entities/tools/vector-shift.md)
- [OpenAI](../entities/organizations/openai.md)
- [Zapier](../entities/tools/zapier.md)
- [Shopify](../entities/organizations/shopify.md)

## Key moments

- **[0:00:00]** Framing: most AI ideas waste time, but a website lead-generation agent is a tried-and-true business use case
- **[0:00:34]** Most lead-gen platforms are not good; either build it yourself (n8n/LangChain) or use a strong purpose-built platform like Chatling
- **[0:02:27]** Three chatbot templates: basic AI chatbot, basic lead-gen (no AI), and lead-gen plus AI
- **[0:03:35]** The node-based workflow Builder introduced (similar to Vector Shift / Voiceflow)
- **[0:04:59]** Capturing user responses into custom variables and feeding them into later AI prompts for context
- **[0:06:08]** Walkthrough of the greeting stage and multi-message conversation flow
- **[0:10:27]** RAG knowledge base tab: ingest website link, sitemap, URL list, documents, raw text, or FAQ pairs
- **[0:12:20]** CRM-like conversations view ties captured contacts (email/phone) to their chats
- **[0:12:34]** Embedding the widget via script tag: floating, inline, or full-screen; Zapier integration
- **[0:13:52]** Live end-to-end demo of the deployed lead-gen agent qualifying a lead and answering from RAG
- **[0:16:59]** HTTP request blocks let the workflow call any external API or custom agent (n8n/LangServe)

## Transcript

[Raw transcript](../raw/get-qualified-leads-while-you-sleep-with-ai.md)
