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

1. Not using category filter - Always set category="company" or category="linkedin_profile" for entity search
2. Expecting structured data - Exa returns web pages; parse text for structured fields
3. Over-broad queries - Add location, industry, or role specifics for better results
4. Ignoring rate limits - Batch requests and implement backoff for large-scale collection
5. Missing domain filters - Use include_domains=["linkedin.com"] for profile-only results