AI-Powered Niche Lead Intelligence & Pre-Call Automation System

Overview

This system was built to solve a common problem faced by niche creators, consultants, and service-based businesses: lead discovery and content research are fragmented, manual, and time-consuming. Valuable signals are scattered across platforms such as business directories, social media, and video platforms, while pre-call preparation relies heavily on guesswork. The AI-Powered Niche Lead Intelligence System centralizes these workflows into a single automated intelligence layer that converts raw web data into structured, actionable insights.

Problem Statement

Most niche businesses struggle with three core challenges:

• Identifying high-intent leads across multiple platforms requires manual scraping, filtering, and validation.

• Understanding what content performs well within a niche involves hours of transcript review, post analysis, and pattern recognition.

• Pre-consultation calls are often inefficient because relevant context, pain points, and intent are not captured in advance.

These inefficiencies lead to wasted time, inconsistent lead quality, and unfocused sales or consultation calls.

Solution Architecture

The system implements a multi-source intelligence pipeline orchestrated through n8n. Custom scrapers collect business and creator data from platforms such as YellowPages and Instagram, while external APIs are used to ingest data from YouTube and LinkedIn. This information is normalized and stored in a structured format, enabling downstream AI processing.

Content transcripts, captions, and metadata are analyzed using NLP and generative AI models to extract engagement signals, summarize themes, and identify repeatable content patterns within a specific niche. A recommendation engine transforms these insights into actionable suggestions, helping users understand what works and how to replicate high-performing strategies.

AI-Driven Pre-Call Intelligence

To further streamline operations, the system includes an AI-powered introductory call workflow that engages users immediately after a call is booked. This automated interaction captures intent, pain points, and contextual information before the main consultation. In parallel, a RAG-based chatbot on the website assists users during the discovery phase by providing real-time, context-aware responses.

Call transcripts and chatbot interactions are automatically summarized and converted into structured research briefs. These briefs equip business owners with relevant insights before live calls, allowing them to focus on high-impact discussions rather than information gathering.

Data & Automation Layer

All workflows are orchestrated through n8n, ensuring consistent execution and scalability. Scraped data, AI-generated insights, transcripts, and summaries are stored in a centralized database, enabling traceability and reuse across workflows. This architecture supports easy extension to additional platforms, niches, or downstream systems such as CRMs and analytics dashboards.