Exa Entity Search

Quick Reference

Topic When to Use Reference

Company Search Finding companies, competitive research company-search.md

People Search Finding profiles, recruiting people-search.md

Websets Data collection at scale, monitoring websets.md

Essential Patterns

Company Search

from exa_py import Exa

exa = Exa()

results = exa.search_and_contents( "AI startups in healthcare series A funding", category="company", num_results=20, text=True )

for company in results.results: print(f"{company.title}: {company.url}")

People Search

results = exa.search_and_contents( "machine learning engineers San Francisco", category="linkedin_profile", num_results=20, text=True )

for profile in results.results: print(f"{profile.title}: {profile.url}")

Websets for Lead Generation

Create a webset for company collection

webset = exa.websets.create( name="AI Healthcare Companies", search_query="AI healthcare startups", category="company", max_results=100 )

Monitor for new matches

exa.websets.add_monitor( webset_id=webset.id, schedule="daily" )

Category Reference

Category Use Case Index Size

company

Company websites, about pages Millions

linkedin_profile

Professional profiles 1B+ profiles

personal_site

Individual blogs, portfolios Millions

github

Repositories, developer profiles Millions

Common Mistakes

• Not using category filter - Always set category="company" or category="linkedin_profile" for entity search

• Expecting structured data - Exa returns web pages; parse text for structured fields

• Over-broad queries - Add location, industry, or role specifics for better results

• Ignoring rate limits - Batch requests and implement backoff for large-scale collection

• Missing domain filters - Use include_domains=["linkedin.com"] for profile-only results