Web Scraping
Parallel
Chat with websites and enrich data using Parallel’s web browsing and data enrichment capabilities
Overview
Parallel provides powerful web browsing and data enrichment capabilities for your agents. Perfect for:- Web research — ask questions and get answers from web content
- Data enrichment — automatically enhance your data with web information
- Entity research — gather detailed information about companies, people, or topics
Chat with Web Action
- What it does: Ask questions and get answers by browsing and analyzing web content in real-time.
Inputs
- Question: The query or question you want answered
- Processor: Choose the model strength for your research needs
Outputs
- Response: The response based on web research
Web Enrichment Action
- What it does: Enriches your data by automatically gathering additional information about entities from the web.
Inputs
- Entity: The thing you want to enrich (company name, person, topic, etc.)
- Enrichment Columns: Choose automatic enrichment or specify custom columns
- Processor: Choose the model strength for processing
Example Enrichment Columns
| Entity Type | Common Columns |
|---|---|
| Companies | Industry, Employee Count, Revenue, Website, Headquarters, Founded Year |
| People | Job Title, Company, LinkedIn Profile, Education, Location |
| General Entities | Description, Category, Related Links, Key Facts |
Outputs
- Enriched Data: Enhanced information about your entity
Processor Selection
Both actions use the same processor options:| Processor | Description | Strength |
|---|---|---|
| Lite | Basic web browsing and research | ⭐ |
| Base | Standard processing with better analysis | ⭐⭐ |
| Core | Enhanced capabilities for complex tasks | ⭐⭐⭐ |
| Pro | Advanced processing with detailed results | ⭐⭐⭐⭐ |
| Ultra | Maximum capability for thorough research | ⭐⭐⭐⭐⭐ |
Core processor provides good balance of speed and detail for most research tasks.
Best Practices
Question Optimization
Question Optimization
- Be specific about what information you need
- Include context when asking about entities
- Use clear, direct questions for better results
- Specify timeframes when relevant
Enrichment Strategy
Enrichment Strategy
- Start with automatic enrichment to see available data
- Use specific columns when you know what you need
- Choose appropriate processor based on entity complexity
- Test with sample entities before processing large datasets
Rate Limit Management
Rate Limit Management
- When looping, set concurrency limits to prevent hitting rate limits
- Reduce parallel requests when processing large datasets
- Monitor for timeout errors and adjust concurrency accordingly