Business Discovery Tool

A Streamlit-based business discovery tool that scrapes SEEK Business listings using __NEXT_DATA__ parsing. Features an AI-powered recommendation engine that analyzes and ranks business opportunities based on your criteria.

Python Streamlit Web Scraping AI Analysis

Listings

156

Analyzed

Top Picks

Cafe & Restaurant

Hospitality

$280K

E-commerce Store

Online Business

$95K

IT Services Firm

Technology

$450K

Key Features

Intelligent business discovery powered by web scraping and AI analysis

🕷️

Web Scraping Engine

Robust scraper that navigates SEEK Business listings, handling pagination, filters, and dynamic content loading with reliability and speed.

📦

__NEXT_DATA__ Parsing

Extracts structured data directly from Next.js __NEXT_DATA__ JSON payloads — faster and more reliable than traditional DOM scraping methods.

🧠

AI Recommendations

AI-powered analysis engine that evaluates listings against your criteria — price range, industry, profitability, growth potential — and ranks the best opportunities.

🖥️

Streamlit UI

Interactive web interface built with Streamlit. Filter, sort, and explore business listings with real-time updates and visual analytics dashboards.

📊

Data Analytics

Price distribution charts, industry breakdowns, and trend analysis. Visualize market data to make informed investment decisions.

💾

Export & Reports

Export filtered results to CSV or generate PDF reports. Save search criteria and get notified when new matching listings appear.

Tech Stack

Python-powered scraping and analysis with an interactive Streamlit frontend

Python

Core language for scraping, parsing, and data processing

Streamlit

Interactive web UI with real-time updates and widgets

Web Scraping

Requests + BeautifulSoup for HTML and JSON extraction

AI Analysis

LLM-powered evaluation and recommendation engine

Beautiful Soup

HTML parsing and data extraction from web pages

Pandas

Data manipulation, analysis, and export to CSV/Excel

# SEEK Business Scraper
import requests
from bs4 import BeautifulSoup
import json

def scrape_listings(url):
    resp = requests.get(url)
    soup = BeautifulSoup(resp.text)
    
    # Extract __NEXT_DATA__ JSON
    script = soup.find(
        "script", id="__NEXT_DATA__"
    )
    data = json.loads(script.string)
    return data["props"]["listings"]
                        