Exa
How It Works

GTM Intelligence Demo

Turn one domain into a cited, scored account list with decision makers.

1

Have Exa Define Your ICP

Enter a domain. Exa uses deep search with a structured output schema to extract a full company profile.

Try:
2

Build prospect list based on ICP

Exa runs parallel deep searches from multiple angles, casting a wide net to find potential fits.

Prospect list
Identify a company in Step 1 above to populate this list.
3

Enrich & Score

One deep search call per company extracts structured intelligence, growth signals, and a personalized fit rating. Every field here is a fragment from the open web, cited.

Ranked prospects
Build the prospect list in Step 2 to run enrichment.
4

Find decision makers

Use Exa people search to find the right stakeholders at the highest-fit accounts.

Decision makers
Enrich the prospect list in Step 3 to surface the right people.
5

Always Enrich

Keep your pipeline intelligence fresh — automatically.

Your enrichment data is only as good as the moment you captured it. Exa Monitors continuously re-run your queries on a schedule — so when a prospect raises a Series B, doubles headcount, or launches a new product, you know about it before your competitors do.

Day 1

Jan 6

Initial enrichment completed across 30 TAM companies

Week 2

Jan 13

New $55M Series B raised from 8VC

Month 1

Feb 6

Engineering team grew 40% — 12 new hires in 3 weeks

Month 3

Apr 6

Launched enterprise API platform with SOC 2 compliance

from exa_py import Exa

exa = Exa(api_key)

# Re-enrich weekly — always-fresh data
monitor = exa.create_monitor(
    query="Company profile for stripe.com",
    output_schema=company_schema,
    schedule="weekly",
    webhook_url="https://your-app.com/webhook"
)
Explore Exa Monitors →