Find a LinkedIn Profile by Name and Company Domain
Most records do not carry a profile URL. They carry a name and a company, which is exactly what this source takes: a full name plus a company name or domain, resolved to the matching professional profile.
{
"session_id": "4f6a…",
"kind": "linkedin_domain",
"company_or_domain": "acme.com",
"full_name": "Jane Doe",
"human": "Matched Jane Doe at Acme Technologies…",
"machine": {
"total_items": 1,
"first_item": {
"fullName": "Jane Doe",
"profileUrl": "https://www.linkedin.com/in/example",
"headline": "Head of Revenue Operations",
"companyName": "Acme Technologies",
"location": "Austin, Texas",
"summary": "…"
}
},
"total_points": 10
}- You send
- A full name plus a company name or domain
- You get back
- The matching profile with headline, company and location
- Coverage
- People with a public profile, worldwide.
- Price
- 10 pts — $10 per 1,000
- Charged only when a profile is matched. An unresolved name is not billed.
Ways to get this data
Three approaches teams use today, and where each one runs into trouble.
| Approach | What it takes | Cost | Trade-off |
|---|---|---|---|
| Searching manually | Search the name, filter by company, judge the match | Free, a minute or two each | Common names make this slow and error-prone |
| Fuzzy matching your own database | Write the matching logic and tune it | Engineering time | You inherit every false positive it produces |
| NeuralVerge | One request | $10 per 1,000, misses not billed | Common names at large companies are genuinely ambiguous — check the match before acting on it |
What you get back
Every field in the response shown above.
| Field | Type | Description |
|---|---|---|
total_items | number | How many candidates matched. |
fullName | string | The matched person's name. |
profileUrl | string | Their profile URL. |
headline | string | Their headline. |
companyName | string | The company on the profile. |
location | string | Where they are based. |
summary | string | Profile summary text. |
How to run it
The same lookup works from the app, the API, or as a tool an agent can call mid-task.
Both parameters are required. `company_or_domain` accepts either a company name or a domain, and the domain is the more precise of the two.
curl -X POST https://api.neuralverge.ai/functions/v1/run-linkedin-domain \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"company_or_domain": "acme.com",
"full_name": "Jane Doe"
}'What teams use it for
Where this field shows up in an actual workflow.
The most common shape of an imported list, resolved to real profiles.
Get the profile URL that the richer sources need as their input.
A match that comes back with a different company is itself the answer.
Resolve several spellings of a name onto one profile.
Coverage, freshness and limits
What this source covers, how fresh it is, and where it stops.
People with a public profile, worldwide.
Resolved at request time.
This source returns personal data. Use it for legitimate business purposes under your own lawful basis, honour deletion and opt-out requests, and check the acceptable use policy for what is out of bounds.
- —Common names at large companies are ambiguous by nature — verify before acting on a match.
- —Someone who has recently changed jobs may match their new company rather than the one you sent.
- —A domain resolves more precisely than a company name.
Questions, answered
No — that is the point of this source. A full name plus a company name or domain is enough, and the profile URL is what you get back.
Related sources
Try linkedin profile by name and domain on your own data
One request format across every source in the catalog.