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B2B Lead Gen via AI Monitoring

Signage & Outdoor Ads2026
93%Lead Accuracy
12hSaved / Month
6 DaysDev Time

The Overview

We developed an automated monitoring system that turns chaotic news streams into a structured database of hot leads. It scans 15+ sources, filters strictly for openings and renovations using LLMs, and alerts the sales team instantly.

The Challenge

The owner spent 3 hours/week manually analyzing news sites. Any missed news about a store opening meant a lost contact and contract.

In the competitive signage and outdoor advertising industry, being the first to know about a new store opening or renovation is critical. The business owner was manually scanning local news sites, municipal planning permissions, and retail blogs every week. It was a tedious, 3-hour weekly ritual that often resulted in missed opportunities because it was impossible for one person to check every source daily. By the time they found a lead manually, competitors had often already made contact.
Initial Concept & Wireframes

The Solution

An automated AI-scout that scrapes 15+ target resources 24/7. DeepSeek LLM analyzes content to detect specific triggers (opening, redesign), filtering out 70% of noise. Relevant leads are sent to Telegram instantly.

We developed a 24/7 market monitoring bot that gives the client a superhuman speed advantage. The system scrapes 15+ target local news sources and RSS feeds every hour to detect change signals. Instead of simple keyword matching (which produces too much noise), we use a Large Language Model (DeepSeek) to semantically analyze article content. It distinguishes between a "store closing" (irrelevant) and a "grand opening" (opportunity). When a high-confidence match is found, the lead details—including location and potential contact info—are instantly delivered to a private Telegram channel for immediate action.

Architecture

System Architecture Diagram

Impact

Problem3 hours/week manual search
Solution100% automated 24/7
ProblemMissed opportunities
SolutionInstant alerts on Telegram
ProblemUnstructured noise
SolutionFiltered hot leads

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