AI & Machine Learning

Collect Training Data
for Large Language Models

Building AI models requires massive amounts of high-quality training data. Spider crawls the web at scale, delivering clean, structured content ready for model training—without the infrastructure headaches.

Get Started API Documentation

The Challenge

Building web scrapers from scratch is time-consuming
Anti-bot measures block traditional crawlers
Raw HTML requires extensive cleaning and parsing
Scaling infrastructure is expensive and complex

The Spider Solution

One API call to crawl entire websites
Built-in anti-bot bypass with 99.5% success rate
Clean markdown output ready for LLMs
Unlimited concurrency—crawl at any scale

Features for AI Training

LLM-Ready Markdown

Get clean markdown output with proper formatting, headings, and structure—ready to feed directly into your training pipeline.

Content Chunking

Automatically split content into optimally-sized chunks for embedding models and context windows.

Metadata Extraction

Extract titles, descriptions, authors, dates, and structured data alongside the main content.

Batch Processing

Submit thousands of URLs in a single request. Process entire datasets efficiently.

Streaming Results

Stream results as they arrive. Start processing before the crawl completes.

Deduplication

Automatic URL normalization and deduplication to avoid duplicate content in your dataset.

Quick Start

Crawl a website for training data Python

from spider import Spider

client = Spider()

# Crawl and get markdown content
result = client.crawl(
    "https://example.com",
    params={
        "return_format": "markdown",
        "limit": 1000,  # Max pages to crawl
    }
)

# Each page ready for training
for page in result:
    content = page["content"]
    url = page["url"]
    # Add to your training dataset...