How Fused.io Uses ScrapeGraphAI for Data Science

Are you tired of spending hours on manual data analysis tasks that hold you back? Imagine having the ability to transform slow and laborious data analysis into lightning-fast results, all with just a few clicks.

Fused.io is an innovative solution that leverages AI-powered data analytics, built on top of serverless Python compute. By harnessing the power of artificial intelligence, Fused.io empowers users to ask questions about any dataset, receiving instant insights and intelligent recommendations in response.

What is Fused.io?

We're proud to present our collaboration with Fused.io, an AI-powered data analytics platform built on top of serverless Python compute. Experience the power of intelligent queries by asking questions about any dataset and receive instant insights supported by AI.

Built on a scalable engine designed for Python, Fused seamlessly integrates cutting-edge AI capabilities and data science tools right at your fingertips.

Imagine having your very own professional AI expert right inside your browser, ready to assist with all your data science needs. It will save you hours by automatically performing data analytics in seconds.

The ScrapeGraphAI Integration

ScrapeGraphAI serves as the foundation for Fused.io's advanced web scraping capabilities, enabling seamless and efficient extraction of high-quality data from individual pages.

By harnessing the power of AI-driven insights, ScrapeGraphAI empowers users to extract relevant information with unprecedented accuracy and speed, unlocking new possibilities for data-driven decision-making and applications.

Use Case Scenarios

Individual Page Scraping

This use case scenario is used when the page URL is known and contains the content you need for extracting structured data from single pages.

In this way, it's possible to create your own dataset for making analytics from there.

Here's a simple example listing all the blogs on the Fused page:

import fused  
  
df = fused.run(  
    "fsh_3A1QcdR5kJEwmDSkYxc934",  
    url = "https://docs.fused.io/blog/", 
    query = "Give me all the blogs, authors and publish date",
    pagination_pages=2  
)  
 
df.head()

The code is used for getting all the required information given a URL and a query for displaying in the dashboard.

Fused.io Dashboard showing scraped blog data

As you can see, all the articles from the URL provided in the code snippet were scraped and visualized on the dashboard, showing titles, authors, and publication dates in a clean, organized format.

Batch Scraping Multiple Pages

The second use case is used when you need to extract structured data from multiple URLs at the same time. This is particularly useful for:

Competitor analysis: Scraping multiple competitor websites simultaneously
Market research: Gathering data from various sources across different domains
Content aggregation: Collecting information from multiple blogs or news sites
Price monitoring: Tracking product prices across different e-commerce platforms

Here's how you can implement batch scraping with Fused.io:

import fused
 
# List of URLs to scrape
urls = [
    "https://docs.fused.io/blog/",
    "https://example.com/news/",
    "https://competitor.com/insights/"
]
 
# Scrape multiple pages in batch
results = []
for url in urls:
    df = fused.run(
        "fsh_3A1QcdR5kJEwmDSkYxc934",
        url=url,
        query="Extract all articles with titles, authors, and dates",
        pagination_pages=3
    )
    results.append(df)
 
# Combine all results
combined_df = pd.concat(results, ignore_index=True)

Why Fused.io Chose ScrapeGraphAI

There are several compelling reasons why Fused.io integrated ScrapeGraphAI into their platform:

1. Natural Language Processing

Instead of writing complex CSS selectors or XPath expressions, users can simply describe what they want in plain English. This makes data extraction accessible to non-technical users.

2. Adaptive Intelligence

When websites change their structure, ScrapeGraphAI's AI adapts automatically, reducing maintenance overhead and ensuring consistent data extraction.

3. Handles Dynamic Content

Modern websites rely heavily on JavaScript to load content. ScrapeGraphAI handles these dynamic elements seamlessly, extracting data that traditional scrapers would miss.

4. High Accuracy

The AI-powered approach delivers more accurate results compared to traditional scraping methods, reducing the need for manual data cleaning and validation.

Real-World Applications

Fused.io users leverage this integration for various data science applications:

Market Research

Competitor analysis: Track competitor pricing, product launches, and marketing strategies
Industry trends: Monitor news and blog posts across multiple industry sources
Customer sentiment: Analyze reviews and social media mentions

Business Intelligence

Lead generation: Extract contact information from business directories
Product research: Gather specifications and pricing from multiple vendors
Financial data: Monitor stock prices, earnings reports, and market indicators

Content Strategy

SEO research: Analyze competitor content strategies and keyword usage
Content inspiration: Discover trending topics and popular content formats
Performance tracking: Monitor content performance across different platforms

Best Practices for Data Extraction

When using Fused.io with ScrapeGraphAI, follow these best practices:

1. Be Specific with Queries

Instead of vague requests like "get all data," be specific about what you need:

✅ "Extract product names, prices, and availability status"
❌ "Get everything from this page"

2. Handle Pagination

Use the pagination_pages parameter to extract data from multiple pages:

df = fused.run(
    "fsh_3A1QcdR5kJEwmDSkYxc934",
    url="https://example.com/products/",
    query="Get all products with names and prices",
    pagination_pages=5  # Scrape first 5 pages
)

3. Validate Your Data

Always check the quality of extracted data:

# Check for missing values
print(df.isnull().sum())
 
# Verify data types
print(df.dtypes)
 
# Sample the data
print(df.head())

4. Respect Rate Limits

Add delays between requests when scraping multiple URLs:

import time
 
for url in urls:
    df = fused.run("fsh_3A1QcdR5kJEwmDSkYxc934", url=url, query="...")
    time.sleep(1)  # Wait 1 second between requests

Performance Benefits

The integration between Fused.io and ScrapeGraphAI delivers significant performance improvements:

10x faster data extraction compared to traditional scraping methods
Reduced development time from hours to minutes for data collection tasks
Higher success rates with fewer failed extractions
Automatic retry logic for handling temporary failures

Getting Started with Fused.io

Ready to experience the power of AI-powered data extraction? Here's how to get started:

Sign up for Fused.io: Create your account and get your API key
Install the Python client: pip install fused
Start with simple queries: Begin with single-page extractions
Scale gradually: Move to batch processing as you become comfortable

# Your first extraction
import fused
 
df = fused.run(
    "your-api-key",
    url="https://example.com",
    query="Extract the main content and metadata"
)
 
print(df.head())

Conclusion

For those entering the world of data analytics in 2025, we highly recommend considering Fused.io as an everyday carry tool. Whether you're a business executive or a Ph.D. researcher, understanding and working with this platform can provide a significant competitive edge.

Here are some use cases Fused can help you with:

Quickly visualizing datasets with Python and their AI Assistant, without complicated setups
Exploring large amounts of data without having to worry about infrastructure
Bringing all your data into a single place no matter where it comes from
Quickly exploring open data from various sources

In summary, Fused.io is an indispensable resource for anyone involved in data analytics. By incorporating this platform into your toolkit, you'll have a 10x data scientist on your team.

The integration with ScrapeGraphAI makes data extraction not just possible, but effortless. Instead of spending hours wrestling with complex scraping code, you can focus on what matters most: analyzing your data and extracting valuable insights.

Try out Fused.io directly for yourself and experience the future of data analytics powered by AI.