exa-entities

name	exa-entities
description	Exa.ai company and people search for lead generation, competitive intelligence, and data enrichment. Use when searching for companies, finding people profiles, building lead gen tools, or implementing Websets for data collection at scale. Triggers on: Exa company search, Exa people search, category company, lead generation, company research, profile search, LinkedIn profiles, Websets API, data enrichment, company lookup, find companies, competitive intelligence, recruiting, talent search, 1B profiles.
license	MIT
metadata	{"author":"ejirocodes","version":"1.0.0"}

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